Satyajit Pramanik

Viscosity scaling in hydrodynamic instabilities in porous media

The importance of viscosity scaling in the context of viscous fingering in a finite slice with viscosity dependent diffusivity is investigated theoretically. Choosing the characteristic viscosity classically as either the displacing or displaced fluid viscosity for both more and less viscous slice leads to inappropriate theoretical predictions, which do not support the physics. With an appropriate choice of the characteristic viscosity, we show that the onset of instability and the initial dynamics of the finger patterns are the same for both more and less viscous slices. Our analysis will be helpful in the theoretical understanding of buoyancydriven convection in a variable viscosity layer in vertical porous media or VF with non-monotonic viscosity profiles.

Introduction

Viscous fingering (VF) in various fluid flow problems of industrial and environmental interest, such as oil recovery [START_REF] Homsy | Viscous fingering in porous media[END_REF], pollution remediation [START_REF] Welty | Stochastic analysis of transverse dispersion in density-coupled transport in aquifers[END_REF], CO 2 sequestration [START_REF] Huppert | The fluid mechanics of carbon dioxide sequestration[END_REF], chromatography separation [START_REF] De Wit | Viscous fingering of miscible slices[END_REF][START_REF] Mishra | Influence of miscible viscous fingering of finite slices on an adsorbed solute dynamics[END_REF][START_REF] Rana | Combined influences of viscous fingering and solvent effect on the distribution of adsorbed solutes in porous media[END_REF][START_REF] Rana | Fingering dynamics on the adsorbed solute with influence of less viscous and strong sample solvent[END_REF], etc. have drawn attention of many researchers over many decades. This hydrodynamic instability is featured when a less viscous fluid displaces a more viscous and hence less mobile one in porous media [START_REF] Homsy | Viscous fingering in porous media[END_REF]. Based on the geometry of the interface featuring the instability in the form of finger-like structure, VF problems can be broadly classified into two categories. The first one being the classical Saffman-Taylor instability in two semi-infinite fluids separated by a flat interface [START_REF] Homsy | Viscous fingering in porous media[END_REF], while the other is the displacement of a finite sample, typically in chromatography column [START_REF] De Wit | Viscous fingering of miscible slices[END_REF]. In the latter case, the sample is confined in a rectangular region that can feature VF either at the frontal or rear interface depending on the viscosity contrast in the downstream direction. The influence of positive and negative log-mobility ratio was investigated in the context of solute adsorption on porous matrix [START_REF] Mishra | Influence of miscible viscous fingering with negative log-mobility ratio on spreading of adsorbed analytes[END_REF]. In the absence of adsorption and for constant diffusivity of the solute concentration, Mishra et al. showed that the onset of instability and the subsequent dynamics of the fingers are identical for more and less viscous slices [START_REF] Mishra | Differences in miscible viscous fingering of finite width slices with positive or negative log mobility ratio[END_REF]. Pramanik and Mishra [START_REF] Pramanik | Viscosity scaling of fingering instability in finite slices with Korteweg stress[END_REF] showed that in the presence of the Korteweg stress [START_REF] Pojman | Evidence of an effective interfacial tension between miscible fluids: Isobutyric acid-water and 1-butanol-water in a spinning drop tensiometer[END_REF][START_REF] Chen | Miscible droplets in a porous medium and the effects of Korteweg stresses[END_REF] the fingering dynamics of a miscible slice of more viscosity are identical to that of a less viscosity. This was achieved with an appropriate scaling. In this paper, we are interested to explore whether such dynamics are also possible with concentration dependent diffusivity in absence of the Korteweg stress effect. In this context, we propose a modified viscosity scaling that helps to answer this question when the diffusivity is inversely proportional to the viscosity of the fluid. We structure this paper as follows. Mathematical formulation and numerical solution of the present problem is discussed in Sect. 2, followed by result discussion and conclusion in Sects. 3 and 4, respectively.

Mathematical formulation and numerical solution of the problem

Consider a rectilinear displacement of a finite sample of viscosity µ 2 by another fluid of viscosity µ 1 at a uniform velocity U e x , where e x is the unit vector in the x-increasing direction. The displacing fluid consists of the same sample solvent having no solute concentration in it, i.e. c = 0, while the finite sample has solute concentration c = c 2 . We assume the variation of the diffusion coefficient with concentration is governed by the generalized Stokes-Einstein relation [START_REF] Probstein | Physicochemical hydrodynamics[END_REF][START_REF] Sahu | Double diffusive effects on pressure-driven miscible channel flow: Influence of variable diffusivity[END_REF],

D(c) • µ(c) = constant, (1)
so that D(c) = D 0 /µ(c), where D 0 denotes the diffusion coefficient of an infinitesimally small amount of the displaced fluid in the displacing fluid. Fluids are assumed to be incompressible, miscible and neutrally buoyant. For nondimensionalization we choose D 0 /U, D 0 /U 2 , U, µ ch D 0 /κ, µ l , c 2 as the characteristic length, time, velocity, pressure, viscosity, and concentration, respectively [START_REF] Pramanik | Viscosity scaling of fingering instability in finite slices with Korteweg stress[END_REF].

Here µ l = min{µ 1 , µ 2 }, κ is the permeability of the porous media, and D 0 represents a reference diffusivity. The related dimensionless equations in a frame of reference moving with the velocity U e x can be written as [START_REF] Homsy | Viscous fingering in porous media[END_REF],

∇ • u = 0, ∇p = -µ(c)(u + e x ), ∂c ∂t + u • ∇c = ∇ • (D(c)∇c) , (2)
where D(c) represents concentration dependent dispersion. The viscosity of the fluids depends exponentially on the solute concentration, i.e., µ(c) = e Rf (c) , where R = ln(µ m /µ l ) is the log-mobility ratio and f (c) is c (more viscous slice) or 1 -c (less viscous slice), and µ m = max{µ 1 , µ 2 }. Therefore, the dimensionless form of the concentration dependent viscosity becomes D(c) = 1/µ(c). For two dimensional incompressible flow we define the stream-function ψ(x, y, t), such that u = ψ y , v = -ψ x are the longitudinal and transverse component of the Darcy velocity u. Therefore, we can write (2) as,

∂c ∂t + J(x, y, t) = 0, ∇ 2 ψ = -Rf (c)N (x, y, t). (3)
The nonlinear terms J(x, y, t) and N (x, y, t) in (3) are defined as,

J(x, y, t) = ψ y c x -ψ x c y -e -Rf (c) ∇ 2 c -Rf (c)|∇c| 2 , (4)
N (x, y, t) = (∇ψ + e y ) • ∇c,

where e y is the unit vector in y-direction. Equations (3) are solved using a Fourier pseudo-spectral method [START_REF] Tan | Simulation of non-linear viscous fingering in miscible displacement[END_REF][START_REF] De Wit | Viscous fingering of miscible slices[END_REF] to analyze the influence of variable diffusivity on VF of more and less viscous miscible slices. We apply Discrete Fourier transform (DFT) to c(x, y, t), ψ(x, y, t), J(x, y, t) and N (x, y, t) that converts (3) into differential algebraic equations,

dĉ m,n (t) dt + Ĵm,n (t) = 0, ψm,n (t) = Nm,n (t)/(k 2 m + k 2 n ), (6)
where k m = 2πm/L x , k n = 2πn/L y , m, n = 0, 1, 2 . . ., L x and L y being the dimensionless length and width of the computational domain, respectively. Equation ( 6) is solved using Adams-Bashforth predictor and trapezoidal corrector method in the Fourier space to obtain the Fourier modes at next time step t + ∆t. Inverse DFT has been performed for ĉm,n and ψm,n to update the concentration and stream function at time t + ∆t, c(x, y, t + ∆t), ψ(x, y, t + ∆t). Details of the numerical method used can be found in the paper of Tan and Homsy [START_REF] Tan | Simulation of non-linear viscous fingering in miscible displacement[END_REF].

Results and discussion

First we investigate the influence of variable diffusivity on miscible VF in a finite slice. The spatial structure of a more viscous slice of dimensionless width l = 256 is presented for variable diffusivity (Fig. 1a) and constant diffusivity (Fig. 1b) with R = 2. Figure 1 depicts that the fingering dynamics become more complex for variable diffusivity as compared to constant diffusivity case. In the former case the wavelength of the fingers becomes shorter and the fingers propagate faster, which is readily evident from an early interaction of the fingers with the frontal interface.

Figure 2 shows the spatio-temporal evolution of the solute concentration of more and less viscous slice for R = 2, l = 256 with concentration dependent diffusivity. This figure depicts that, before interacting with the stable interface the fingering dynamics in more and less viscous slices are identical. We also perform simulations for a less viscous slice by considering µ ch = µ 1 [START_REF] Mishra | Differences in miscible viscous fingering of finite width slices with positive or negative log mobility ratio[END_REF], such that µ = e -2c . It is observed that the finger patterns differ significantly in this case (for brevity not shown) as compared to that shown in Fig. 2b. In particular, the onset of instability delays when choosing µ = e -2c , which is attributed to the fast diffusion of the solute concentration as compared to µ = e 2(1-c) . Thus we conclude, in order to compare between two similar flows one should be careful about the choice of the dimensionless values in such a way that they represent the same dimensional values. With the prescribed scaling of the viscosity of the fluids this has been achieved in the case of variable diffusivity VF in finite slice.

The temporal evolution of degree of mixing χ(t) [START_REF] Jha | Fluid mixing from viscous fingering[END_REF] has been investigated for both more and less viscous finite sample of width l = 256. We mentioned in §2 that the displacement of a more or less viscous finite sample is represented by µ(c) = e Rc or µ(c) = e R(1-c) , respectively, where the log-mobility ratio R > 0. Figure 3 depicts that the temporal evolution of the degree of mixing, χ(t), for these two cases are almost identical, even after the interaction of the fingers with the respective stable interface. The displacement of a less viscous finite sample can alternatively be represented by µ(c) = e Rc , R < 0 [START_REF] Mishra | Differences in miscible viscous fingering of finite width slices with positive or negative log mobility ratio[END_REF]. It is shown that at early times, say at t = 500 in Fig. 3, mixing due to diffusion for R < 0 is more than the mixing due to VF for R > 0. However, at later times, for example at t = 1500, VF enhances the fluid-fluid interface and hence the degree of mixing becomes larger for R > 0 than its R < 0 counterpart. This is due to the fact that the dimensionless diffusion coefficient, which depends on the local solute concentration, c. For R = 2, the dimensionless diffusion coefficient is e -2(1-c) , while for R = -2, the dimensionless diffusion coefficient is e 2c . Therefore, when the displacement of a less viscous finite sample is represented by µ(c) = e -2c , the finite slice diffuses faster than that when the displacement is represented by µ(c) = e R (1-c) . This leads to a faster diffusive mixing for µ(c) = e -2c than that for µ(c) = e 2c .

Conclusion

The influence of viscosity scaling on miscible VF in a finite slice with viscosity dependent diffusivity is investigated through numerical simulations. Choosing an appropriate characteristic viscosity we show that the fingering dynamics of a more viscous slice is identical to that of a less viscous one. We believe, the present scaling analysis shall be important to investigate the stability of a variable viscosity buoyantly unstable layer in vertical porous media [START_REF] Manickam | Fingering instabilities in vertical miscible displacement flow in porous media[END_REF] or miscible VF with non-monotonic viscosity profiles [START_REF] Manickam | Stability of miscible displacements in porous media with nonmonotonic viscosity profiles[END_REF], and pave new way to understand fluid mixing in porous media.

Acknowledgement

Author is also grateful to Manoranjan Mishra for fruitful discussion and careful reading of the manuscript. Author gratefully acknowledges the financial support from the National Board for Higher Mathematics, Department of Atomic Energy, Government of India through a Ph.D. fellowship.

Scientific validation

This paper has been unanimously validated in a collaborative review mode with the following reviewers:

-Aǵota Tóth, University of Szeged, -Sarah Klein, Université Paris-Sud.

Fig. 1 .

 1 Fig. 1. Spatial structure of the solute concentration at t = 800 in the moving frame of reference for R = 2, l = 256: (a) variable diffusivity and (b) constant diffusivity.

Fig. 2 .

 2 Fig. 2. Spatial structure of the solute concentration at successive times in the moving frame of reference for l = 256: (a) µ(c) = e 2c and (b) µ(c) = e 2(1-c) .

Fig. 3 .

 3 Fig.3. Temporal evolution of the degree of mixing for l = 256 with µ(c) = e 2c (dashdotted line), µ(c) = e 2(1-c) (continuous line) and µ(c) = e -2c (dashed line). Inset images show the concentration distribution for the last two cases at t = 500 and 1500.


Philippe Ramirez

come   L'archive ouverte pluridisciplinaire

CS-DC 2015

From Fields to Territories to the Planet Social Patterns in Multicultural Environments Matrimonial patterns and trans-ethnic entities Philippe RAMIREZ, CNRS, Centre for Himalayan Studies pramirez@vjf.cnrs.fr

Despite the complexity of their object of study, i.e. human society and culture, anthropologists seldom address complexity per se. In this paper I would like to briefly suggest approaches to deal with certain complex issues involved in the modelisation of social relations within a naturalistic paradigm. What I want to show primarily is how anthropological knowledge might be markedly enhanced by truly confronting the complexity of anthropological phenomena, i.e. by putting culture and social structures back into the natural/physical world, to understand how "it really works". And the condition for performing such an enterprise is close cooperation with other disciplines dealing with the study of complexity. The topic at hand is modelling the origin of a system of surname equivalences in tribal India. But the work being done might have a much broader range, by helping the studies of matrimonial systems to adopt more naturalistic approaches.

Georg Simmel wrote about "large systems", formed of "immediate interactions that occur among men constantly…that have become crystalized…attaining their own laws" (Simmel 1950, 10). The present study aims at understanding how one of these systems evolves "by itself", beside or in conjunction with what the actors say and think about it.

Among several tribal societies of North-East India people recognize that some of their neighbours, belonging to altogether different cultures and ethnicities, and speaking different languages, are actually "similar" because of their surname. "Similar" people are identified by their surnames being "the same". We might translate without too much risk "similar" by "synonymous" or "equivalent", as such surnames refer to clans ("descent groups" in the anthropological parlance), the immediate outcome being that equivalent clans are found across different ethnicities. "Similar" people from different tribes are not bound to any mutual obligation other than the absolute ban of intermarriage: being the same they should not marry, which would amount to an incest, the worst crime in those societies. Thus, being different in terms of ethnicity and culture does not preclude being the same in terms of clan, which is a counter-intuitive idea for many anthropologists and for many North-East Indians as well, especially those belonging to the younger generations. Anthropologists have been taught in universities that tribal societies consist of clans who share a common culture and a common social structure. And young North-Easterners are immersed in a neo-essentialist, ethnicized India where different people are different by all means: how could they be both different and similar?

The initial question which the research described here tries to address is the origin of such a system, with the view that in the absence of a centralized authority such relations may have been the product of processes of self-structuration. Systems displaying similar features (clanic equivalence implying exogamy) have been documented in other areas of the world, although they are globally rare: Western Siberia, North America, North-East Africa (Swanton 1909;Verbov 1936;[START_REF] Goodwin | The Characteristics and Function of Clan in a Southern Athapascan Culture[END_REF][START_REF] Emmons | The Tlingit Indians[END_REF][START_REF] Shternberg | The Social Organization of the Gilyak[END_REF]. Very few systematic studies have been undertaken on the topic, with the exception of Robinne, on the Kachin of Upper Myanmar (Robinne 2007), and Günther Schlee in the Horn of Africa (Schlee 1985). Schlee suggested that the origin of equivalences among ethnically different -but linguistically related-people was a series of segmentation processes dividing original clans into branches with different titles, but who still remembered being related. This scenario cannot hold for the North-East India case, which involves culturally unrelated people who arrived on the scene at various times and from different directions.

My data pertains to three particular ethno-cultural entities, to three "tribes" (tribe being the established term in local English): the Tiwa, Karbi and Khasi, and more particularly to the 2.500 km² or so of low hills on the Meghalaya and Assam states borders where the villages of these tribes are interwoven, each village being monoethnic. The differences among these three tribes are obvious. They speak very dissimilar languages, which either belong to different branches of the Tibeto-Burman family (Karbi, Tiwa) or to the Austroasiatic family (Khasi). The Karbi follow patrilineal descent: clan membership and surnames are inherited on the male line. Khasi follow matrilineal descent. And among the Tiwa, descent is ambilineal: according to where the new couple decides to reside, their children will inherit either their mother's or their father's clan and surname. Social and political structures as well as traditional religions (between 30% and 60% are Christians) are less contrasted, but enough to form three (relatively) different cultures. Finally, in the domain of identity, ethnicities are neatly asserted -which may not have been the case in the past. People have no doubt they belong to one particular tribe and that this tribe has "nothing to do" with the next one.

To fully complete this rough picture of the context, two points have to be added. First, before a sharp population growth during the twentieth century, which led to sedentarization, short distance migrations, driven mostly by slash-and-burn agriculture as well as epidemics, were pervasive. Second, inter-ethnic marriages were less than marginal and are now on the rise. Their precise amount is difficult to assess, as the incoming spouses fully adopt the local culture, and even change their surname, actually on the basis of the interethnic surname equivalences. And in interethnic marriages, exogamy between equivalent surnames is, up to my data, strictly respected.

Most elderly persons know about the existence of surname equivalences. In a particular locality, or family, people cannot list the full equivalence relations linking all the clans; they would only cite a few of them; similarly, they most generally cite one to one equivalences relations between one clan of their own tribe and one of the two other tribes. Strikingly however, when put together, the collected equivalences fully agree and draw a very coherent picture (Figure 1, below). The lines in the diagram should be read as "Surname A is equivalent to surname B", or "people bearing surname A cannot marry people bearing surname B". The diagram includes exogamic relations internal to each tribe, i.e. the clans within each tribe who are forbidden to marry, each cluster forming what anthropologists call a "phratry". One notices the striking correspondence between "internal exogamies" and "external" ones, particularly between the Karbi and Tiwa. Among these two tribes at least, exogamy is transitive across the ethnic boundaries: e() being the relation of exogamy, T n a Tiwa clan and K n a Karbi clan, (T a e(K a )) ^ (K a e(K b )) ⟹T a e(K b ).

Where did such a coherent system come from? The possibility that, as in the Horn of Africa, equivalences are the links which remained after original descent groups split up, can be discarded, as the tribes concerned differ in all aspects. Intentional creation also comes to mind as a possible origin. However, we're among tribal societies, with no overarching centralized authority. We have no signs that the neighbouring Hindu rajas, with whom the tribes had at different times maintained loose alliances, have interfered with their marriage rules -and this seems hardly plausible anyhow. The highest level authorities which could have regulated marriages are the politico-ritual dignitaries responsible for the settlement of disputes and the performance of rituals, but their authority seldom stretched beyond a dozen villages. And even in this case, what would have been the reason for coordinating interethnic marriages?

To me, the most plausible scenario to account for the origin of equivalences is that of selforganization and diffusion. Equivalences would have emerged locally in the context of interethnic marriages, when different matrimonial norms were confronted. They then would have diffused to other localities and/or connected with similar patterns. Presently, among the Khasi and Tiwa, there exist no other matrimonial rule than clan exogamy. On the Karbi side however, informants describe their traditional but vanished ideal rule as a circulative connubium, i.e. cyclical marriages among their five major clans (A->B->C->D->E->A).1 Nowadays, the only norm among the Karbi is the avoidance of symmetrical alliances between local lineages, and this is largely adhered to: after a local lineage (i.e. segment of clan) belonging to clan A have "taken a girl" from a lineage belonging to clan B, upcoming marriages between the two lineages will only be allowed in the same direction; B will not "take a girl" from A and the orientation of the relation will not be allowed to reverse for several generations. Any marriage thus creates an asymmetrical relation between "wife-givers" (WG) and "wife-takers" (WT), all men born in the WG lineage being afterwards addressed by their WT as ong, indistinctly meaning "father-in-law" and "maternal uncle". Thus, when Karbis consider a new matrimonial alliance, they must ensure that existing WG-WT relations will not be jeopardized.

My hypothesis is the following: after a Karbi marries a member of another tribe, a WG-WT is established between the partner lineages. The foreign lineage becomes structurally equivalent to a Karbi lineage and becomes identified with a Karbi surname. This will be taken into consideration in future marriages. After several such interethnic marriages happen in the neighbourhood, a full set of equivalences becomes established between the Karbi clans and the non-Karbi clans. This set of equivalences then spreads to the neighbouring localities. An alternative, more plausible and more complex scenario, is that different sets of equivalences were born in several distant localities and that after a while they coalesced into a unified regional system.

The question is: how much time would it take for such a scenario to be completed in a particular population/area? The core of this scenario can be qualified as a weak emergence. It is extremely simple to simulate for ideal conditions and a single locality: each new marriage generates a new WG-WT relation and forbids its reversal. After n interethnic marriages have taken place between n distinct Karbi clans and n distinct non-Karbi clans, n equivalences are established. This could be a matter of two generations only.

Modelling the same process in a moderately realistic way would however involve a lot of factors, making us enter the realm of complexity (both computational complexity and complex dynamic systems). First, in the real world, there is little chance that three interethnic marriages involving 2x3 distinct clans will happen in a row within one or two generations. The communities involved are villages of a few dozen houses, thus the frequency of matrimonial unions are limited. Considering the time factor brings to the probability that a marriage between two particular lineages takes place, and first of all that it is contemplated by the families. A prospective marriage corresponds to two households situations matching, possibly to the agreement or feelings of the prospective spouses, and to the mere existence of matchable individuals, i.e. at least the availability of a bachelor of the right age: the local population's structure is a critical factor. Furthermore, the probability that a member of a particular clan marries a member of another particular clan depends on the availability of these two clans in the surroundings. Now, considering the small populations at stake, this situation is not obvious. Second, a simulation of the build-up of equivalences in a local isolate does not take into account what occurs outside. Now what would happen if a similar process happens in the next area? There is little chance that the very same equivalence relations will emerge. So, how will contradictions between two sets of equivalence be resolved if a marriage is considered between people living in both areas?

These rather mechanistic issues don't bother most anthropologists. When describing social structures and norms, anthropologists seldom consider their applicability in a realistic context. I believe that the question of the origin of equivalences cannot be settled in a useful manner by considering the social structure and the norms supposed to regulate it in isolation from their biological environment. What would be the point of showing that the asymmetrical marriage rule might generate surname equivalences if there is very little chance that the proper matrimonial configuration appears over several centuries? This is the reason why I decided to solicit the expertise of statisticians, modellers and ecologists, among others, and set up a working group, ATIMODIS, to decipher the processes at stake in the complex relations between marriage rules, space and population dynamics.

For the time being, ATIMODIS has tried to identify which factors might be critical in the modelling of the hypothesis in question. To start with, a series of simple simulations (under GAMA2 ) involving only a small population and a simple set of marriage rules have helped to put into light a very critical factor indeed: the fragility of small populations to even seemingly light marriage constraints. Imposing nothing more than the simple rule of clan exogamy ("one should not marry within one own's clan") to a population of 200 individuals divided into three clans, even with optimistic fertility rates, will considerably endanger its survival in less than three centuries. Going a step further by imposing an asymmetrical marriage rule among the clans ("after A has taken from B, it will not be able to give back") will make the population dramatically collapse and disappear within less than three to four generations. As for the circulating connubium, with three clans exchanging, even when a degree of deviance is allowed for, eligible partners become unavailable after a couple of years, preventing any reproduction.

Although the "small population effect" or "demographic stochasticity" is nothing new 3 , realizing how much any pairing constraint amplified its consequences forced us to somehow let the question of equivalence aside for a while, and focus on the relationships between matrimonial rules and population viability. In which conditions could the prescriptive marriage norms formulated by the Karbi have been applied at all? Our simulations showed that the ideal norm of the circulating connubium, what anthropologists after Lévi-Strauss call the "generalized exchange", with three or five clans exchanging spouses in a single direction, seems impossible to put into practice in a small population when a majority follows the rule. This incited me to go back to the anthropological literature on generalized exchange. Lévi-Strauss himself had noticed that the structural model he proposed was hardly applicable in practice, both because of population size effects (on which he did not elaborate much) and because of the inequalities among the exchanging parties (Lévi-Strauss 1969, chap. introduction). Indeed, Leach and others had criticized him on the ground that nowhere was generalized exchange statistically dominant (Leach 1962). Lévi-Strauss reacted by arguing that generalized exchange is primarily a "model": its "reality" (accuracy) does not consist in its statistical existence but in the fact that it depicts the general trend of all concrete alliances in the long term. As a matter of fact, some scholars, with the limited tools of the time (1960s-1970s), had started to show through simulation both that the rule was impossible to put fully into practice and conversely that in the absence of any other rule than simple exogamy, there was always a proportion of marriages corresponding to the norm of generalized exchange [START_REF] Kunstadter | Demographic Variability and Preferential Marriage Patterns[END_REF][START_REF] Gilbert | Computer Simulation and Analysis of Problems in Kinship and Social Structure[END_REF]. If other aspects of the generalized exchange model still arouse new formalizations and modelizations (e.g. graphs4 ), the study of its demographical context have not benefited from the computational and simulation tools now at our disposal. This is one of the tasks ATIMODIS project wishes to take on.

Although generalized exchange in its full cyclic form has not been documented, cases of populations following prescriptive asymmetrical rules are widespread [START_REF] Leach | The Structural Implications of Matrilateral Cross-Cousin Marriage[END_REF][START_REF] Moore | Oblique and Asymmetrical Cross-Cousin Marriage and Crow-Omaha Terminology[END_REF][START_REF] Löffler | Prescriptive Matrilateral Cross-Cousin Marriage in Asymmetric Alliance Systems: A Fallacy[END_REF][START_REF] Krige | Asymmetrical Matrilateral Cross-Cousin Marriage-the Lovedu Case[END_REF]. If simulations show that asymmetrical rule is so detrimental to the demographic structure, how then could it be explained that populations practising such marriages were able to survive? The issue was seldom taken up by anthropologists. Recently however, starting from this very question, a set of studies in Western Australia have brought a very convincing and stimulating answer, and one which compel us to deeply reconsider our methodology, if not our paradigm: a few exchange of partners among local groups could have been sufficient to maintain their demographic viability even while prescriptive alliance remained dominant [START_REF] Dousset | Assimilating Identities: Social Networks and the Diffusion of Sections[END_REF][START_REF] White | The Indigenous Australian Marriage Paradox: Small-World Dynamics on a Continental Scale[END_REF][START_REF] Denham | Beyond Fictions of Closure in Australian Aboriginal Kinship[END_REF]. Small populations are very rarely complete isolates. Their sustainability cannot be explained without taking into account the inputs from outside, even if these look statistically marginal. Statistically marginal exogamy may prove vital for the survival of small populations.5 "Intermarriage … should be seen as a component of formal marriage system models that opens up local models to form an explicit, culturally recognized, and realistic continentwide meta-model." (White and Denham 2007, 6) Thus the need to move from the level of the village, where most marriages happen, to the regional level, at which inter-villages marriages take place from time to time, in order to understand how the two levels are dynamically connected. In other words, shifting from the (false) local isolate to what ecologists call the meta-population. In this regard, the contribution of the tools used by ecological modelling could be essential for the approach of anthropological complexities such as the interactions between marriage norms and demographics.

The "problem" posed by the negative effects of marriage rules on the demographic dynamics of small populations could in fact be completely reversed. In a functionalist perspective, and at least as a working hypothesis, one could consider prescriptive marriage rules not as a constraint but as an incentive to search for mates outside the groupwhatever groupwhich would counter demographic stochasticity as well as genetic inbreeding.

Modelling the dynamics of asymmetrical marriage rules at the level of meta-populations is however far from being a trivial task. This is where one enters into hardcore complexity (at least to an anthropologist) and where interdisciplinary becomes compulsory. For instance, how did different local matrimonial patterns become a coherent regional pattern? Simulation will obviously be a major component of our approach. The second one will consist in mapping the data available on existing matrimonial links. A set of genealogies I collected in some localities will help to understand the small-scale mechanisms, but hardly any phenomenon of emergence/selforganization. For this purpose, our main corpus will be the Indian electoral rolls, which provide a full size picture of voters with their surnames, including married women and their husband names, and thus of the existing alliances among clans. This set of data has several obvious limitations, among others the inability to show the origin of external spouses, or to show real matrimonial networks. The challenge will be here to devise proper tools that will explore the corpus at successive spatial levels and detect the existence of significant patterns.

For the time being, it is interesting to underline how a very pragmatic problem emerging during simulation, "how to avoid that my population collapses", has led to a deep re-thinking of the general approach. Going back to the literature about the anthropological theory of alliance, I realized that the problem had not been resolved at all, and that other essential issues as the structuration of alliance patterns at higher levels remained almost untouched. An approach in terms of complexity is not an escape out of the classical anthropological debates; indeed it is a constructive return to them.

Scientific Validation

This paper has been unanimously validated in a collaborative review mode with the following reviewers:  Karla de Jesus, University of Porto  Philippe Collard, Université de Nice

Figure 1

 1 Figure 1 Endo-ethnic and interethnic exogamies among Karbis, Tiwas, and Khasi-Bhois of Assam-Meghalaya borderlands. Dots represent patronymic groups (clans), lines represent relations of exogamy. This diagram highlights the convergence of exogamies within ethnic groups (same color clusters) and across them.

On similar norms, see e.g.[START_REF] Needham | Circulating Connubium in Eastern Sumba: A Literary Analysis[END_REF][START_REF] Lehman | The Structure of Chin Society[END_REF]

https://github.com/gama-platform/gama/wiki

See for instance[START_REF] Dyke | Potential Mates in a Small Human Population[END_REF][START_REF] Gaines | Simulating Success or Failure: Another Look at Small-Population Dynamics[END_REF][START_REF] Legendre | Demographic Stochasticity and Social Mating System in the Process of Extinction of Small Populations: The Case of Passerines Introduced to New Zealand[END_REF][START_REF] Engen | Demographic Stochasticity and Allee Effects in Populations with Two Sexes[END_REF][START_REF] Drake | Allee Effects | Learn Science at Scitable[END_REF]). For human populations, a "Minimum Viable Population" of 500 has been suggested by[START_REF] Livi | Considérations Théoriques et Pratiques Sur Le Concept de 'Minimum de Population[END_REF]).

[START_REF] Harary | The Logical Structure of Asymmetric Marriage[END_REF]

This converges with conclusions met by paleo-anthropologists. (Bocquet-Appel and Masset 1982).


Rafaela Carolina Da Silva

• "Multi-Level Modeling" e-track Science Information and the complexity: are we oriented to a transdisciplinary science?

Keywords: Complexity, Transdisciplinarity, Complex Science, Transdisciplinary Science

published or not. The documents may come

The concept of transdisciplinarity is an extent of complex expression in society. Currently, the human, social and phychological contexts are connected and the science needs an answer about this phenomenon. This article conceptualizes the transdisciplinarity as a strategic application of complexity, which is a theorical and methodological concept that bases the transdisciplinarity.

Then, the concepts of transdisciplinarity and complexity connected, since we understand transdisciplinary as fundamental question relat to complex structures inherent in the world. This idea also leads the thinking of a design that considers a new perception of reality. According to Morin (2001, p. 138, our translation), understand the complexity is "[...] at the same time, separate, associate [...] the emergency of levels reality without reducing them to elementary units and general laws".

In this context, "Transdisciplinarity as the prefix 'trans' indicates, indicates that is a relation between the disciplines, across different disciplines and beyond any discipline. This goal is the understanding of this world for which one of the imperatives is the unity of knowledge." (NICOLESCU, 1997, s.n, our translation).

So, the question is: "Is the Information Science oriented to a transdisciplinarity sicence?" It's depends of the object that we are studying. If we study the object and think that the object of Information Science is the information, it can be a transdisciplinary object. We can see that the literature of Information Science hasn't a conceptualization of what information would be. In other hand, if you concept that your object of study are the various types of applications that information professionals realize in the library, so we can discuss other concepts, as multidisciplinarity, pluridisciplinarity and interdisciplinarity.

We can observe the Figure 1, relating interdisciplinarity, pluridisciplinarity and multidisciplinarity, the transdisciplinarity is multireferential and multidimensional, taking concepts of time and history in a transhistorical horizon (Transdisciplinarity Letter, 1994). For Information Science can be considered as transdisciplinary science, there must be a change in the perception of phenomenon, society, reality, ethics, etc. In this perspective, is how the professional exercises his profession that designates if a science is multi/pluri/inter or transdisciplinary.

Finally, this paper aims to propose a discussion about the theme instead of try to conceptualize transdisciplinarity. It's a question that impacts all the world in a complexity system of emotions, rights, rationality, humans relations and contexts.

Scientific Validation

Figure 1 :

 1 Figure 1: Interdisciplinarity, pluridisciplinarity, multidisciplinarity and transdisciplinarity

  This paper has been unanimously validated in a collaborative review mode with the following reviewers:  Paul Rodriguez  Ricardo Fernandes, from Centre of Research, Education, Innovation and Intervention in Sport, Faculty of Sport and Porto Biomechanics Laboratory, University of Porto, Porto, Portugal  Lukasz Lacinski, University of Chicago


Masatoshi Funabashi
email: masafunabashi@csl.sony.co.jp

Peter Hanappe
email: hanappe@csl.sony.fr

Takashi Isozaki
email: isozaki@csl.sony.co.jp

Annemarie Maes

Takahiro Sasaki
email: sasaki@csl.sony.co.jp

Luc Steels

Kaoru Yoshida

Foundation of CS-DC e-laboratory: Open Systems Exploration for Ecosystems Leveraging

Keywords: Food production, agriculture, health, community, ecology, environmental problems, open systems, analytics, simulation, art, citizen science

We established a Complex Systems Digital Campus(CS-DC) e-laboratory "Open Systems Exploration for Ecosystems Leveraging" in view of redesigning sustainable social-ecological systems related to food production ranging over food, health, community, economy, and environment. 6 projects have begun to collaborate in e-laboratory, namely Synecoculture, P2P Food Lab, Open Systems Data Analytics, The Bee Laboratory, Open Systems Simulation and One-Health Food Lab. As a transversal methodology we apply open systems science to deepen scientific understanding and for a continuous amelioration of the management. The projects involve scientists, engineers, artists, citizens and are open to collaboration inside and outside of the e-laboratory. This article summarizes foundational principles of these projects and reports initial steps in operation.

Introduction

Environmental Problems of Agriculture

Humans have engaged in agriculture for over 10,000 years since the dawn of history, but that history has been inevitably based on the trade-off between agricultural production and environmental degradation [START_REF] Carter | Topsoil and Civilization[END_REF] [START_REF] Montgomery | Dirt: The Erosion of Civilizations[END_REF]. Modern agriculture is still situated along the same line, further loading the environment to realize physiological optimum in large-scale monoculture. The excess practice of conventional agriculture is now considered as a major factor of environmental degradation in both terrestrial and marine ecosystems, that threatens the sustainability of our society by triggering irreversible global state shift of the environment [START_REF] Barnosky | Approaching a state shift in Earth's biosphere[END_REF]. Several International organizations provide scientific reports on the environmental degradation caused by intensive practice of conventional agriculture and associated market structure [START_REF]International assessment of agricultural knowledge, science and technology for development (IAASTD) : synthesis report with executive summary : a synthesis of the global and sub-global IAASTD reports[END_REF] [5] [START_REF]World Economic Forum, Realizing a New Vision for Agriculture: A roadmap for stakeholders[END_REF] [7] [START_REF]The environmental food crisis -The environment's role in averting future food crises[END_REF] [9] [START_REF]Investing in smallholder agriculture for food security. A report by the High Level Panel of Experts on Food Security and Nutrition of the Committee on World Food Security[END_REF]. They commonly propose alternative models should take priority on small-scale local farming, environment-constructive method of cultivation, fair distribution and equitable trade.

Sensing Technologies

Recent development of sensing technology has drastically changed the precision and scope of measurement from molecular to ecosystem levels. In the level of ecosystems, remote sensing technologies are extensively applied to the measurement in large-scale agriculture and assessment of ecological state. The application has a wide range such as international assessment of climate change [START_REF] Rosenqvist | A review of remote sensing technology in support of the Kyoto Protocol[END_REF], estimation of river inundation [START_REF] Smith | Satellite Remote Sensing of River Inundation Area, Stage, and Discharge: a Review[END_REF], weed control [START_REF] Thop | A Review on Remote Sensing of Weeds in Agriculture[END_REF], prediction of drought [START_REF] Mcvigar | The Current and Potential Operational Uses of Remote Sensing to Aid Decisions on Drought Exceptional Circumstances in Australia a Review[END_REF], resource management [START_REF] Green | A Review of Remote Sensing for the Assessment and Management of Tropical Coastal Resources[END_REF], agroecosystem modeling [START_REF] Dorigo | A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling[END_REF], forestry planning [START_REF] Homgren | Satellite Remote Sensing for Forestry Planning[END_REF] [START_REF] Lynch | Choose satellites to monitor deforestation[END_REF], estimation of crop biomass [START_REF] Tucker | A critical review of remote sensing and other methods for nondestructive estimation of standing crop biomass[END_REF], and so on. The research trend is focused mainly on 2 areas, conventional agriculture systems and global observation of ecosystems: Sensing of agricultural ecosystems aims to gain specific information necessary for the prediction and control. While sensing of global ecosystems tries to capture global indicators associated with climate change in large scale.

There is however little application on the crossing area, especially on smallscale sustainable agriculture where biodiversity and cultural productivity are firmly related [START_REF] Mader | Soil Fertility and Biodiversity in Organic Farming[END_REF] [START_REF] Burlingame | Proceedings of the International Scientific Symposium BIO-DIVERSITY AND SUSTAINABLE DIETS UNITED AGAINST HUNGER[END_REF]. Prediction model based on remote sensing data do not sufficiently incorporate biodiversity in its models. Small scale farming between natural ecosystems and human disruption realizes rich ecosystems, which is similar to the biodiversity hotspot known as ecotone [START_REF] Walker | Properties of Ecotones: Evidence From Five Ecotones Objectively Determined From A Coastal Vegetation Gradient[END_REF]. The importance of conservation effort of hotspots is due to its instability, which is considered to attribute to the chaotic behavior inherent in ecosystem dynamics [START_REF] Pool | Ecologists Flirt with Chaos[END_REF] [START_REF] Cushing | Chaos in Ecology[END_REF]. Such complexity requires methodologies of complex systems science besides the global measurement by remote sensing. We need to develop a framework to connect between diverse sensing methods and each ecosystem agent, which would provide rich indicators on the dynamics of biodiversity.

Biodiversity Database

Biodiversity is a key concept to assess the environment, evaluate the ecosystems services and measure the effect of human disruption. Biodiversity comprises plural indicators describing the degree of variation, ranging over diversity within species, between species and of ecosystems from all sources [START_REF]Ecosystems and Human Well-being: Biodiversity Synthesis[END_REF]. Sensing of biodiversity in small scale still demands manual labour and classification of species by human. Important conservation issues based on the environmental assessment always require such precise information. Biodiversity and taxonomy database follows international initiative in view to describe the whole species existing on the earth [START_REF][END_REF][27] [START_REF]Japan Integrated Biodiversity Information System[END_REF] [START_REF]EU-project KNEU-Developing a Knowledge Network for EUropean expertise on biodiversity and ecosystem services to inform policy making economic sectors[END_REF][30][31] [START_REF]Global Biodiversity model for policy support[END_REF] [START_REF] Groombridge | World Atlas of Biodiversity: Earth's Living Resources in the 21st Century[END_REF]. These databases are complementary to remote sensing measurement, and both should be assembled to obtain a multiscale interpretation of an ecosystem state. To establish a fine-grained measurement compatible to the concept of biodiversity, we have to proceed from several paths, such as refinement of sensing methods, models of biodiversity, and human observation, through an integrated development of technology, modeling and practice.

Biodiversity is also finely related with local diet and health in traditional food, which is compatible to the growing needs in sustainable agriculture [START_REF]Indigenous Peoples' Food systems & well-being, Food and Agriculture Organization of the United Nations, Center for Indigenous Peoples' Nutrition and Environment[END_REF]. Foods are major factors of health amidst recent life style changes [35] [START_REF]The Global Burden of Non-communicable Diseases, A Report by the World Economic Forum and the Harvard School of Public Health[END_REF]. It is important to explore the relation between environment, food, nutrition, and human health with the use of nutritional and biodiversity database.

Citizen Science and Virtual Platform

Development of information technologies and invention of mobile terminal such as smartphone has introduced a novel realm of interaction in citizen science. Diversity record related to geographical information has become possible to organize participation of individuals on site. The cloud sourcing of data collection is expected to be more accessible to local activities and essential to consider management on the diversity [START_REF] Goodchild | Citizens as sensors: the world of volunteered geography[END_REF]. Integrated expression of environmental data on virtual globe software such as Google Earth is rapidly gaining its popularity. Participatory use of such platform can gather expert knowledge as well as laypeople observation, bridge the gap between professionals and amateurs, and is compelling to raise public awareness on the management including ethical discussion [START_REF] Sheppard | The ethics of Google Earth Crossing thresholds from spatial data to landscape visualization[END_REF]. Virtual platform of environmental information with geographical expression can be a prominent platform to integrate sensing data, biodiversity database, and citizen observation.

Challenge of the e-laboratory: Towards Citizen Prototype of

Sustainable Agriculture -Exploring Ecosystem Agents as a Symbiotic Interface between Human and Nature-Our e-laboratory gathers scientists, engineers, and artists to tackle the sustainability issues in food production and ecosystems management, ranging from urban gardening to agricultural production, from on-the-fly exploration to integrative simulation, from human to environmental health, from data analytics to artistic expression [39]. Sensing technologies, databases, analytics, and citizen science will be combined in order to realize the leveraging of ecosystem services via human activity. The initial projects comprise 6 projects, namely Synecoculture(sec.2), P2P Food Lab(sec.4), Open Systems Data Analytics(sec.3), The Bee Laboratory(sec.5), Open Systems Simulation(sec.6), and One-Health Food Lab(sec.7). Our challenge aims to yield the potentials of self-organizing nature of ecosystems with the bottom-up organization of each project. By exploring ecosystem agents as a symbiotic interface between human and nature, this challenge would consequently be led to develop diverse, parallelly distributed practices of sustainable food production and related scientific domains.

(Masatoshi Funabashi)

2 Synecoculture

An Alternative: Polyculture System with Ecological Optimum

Plants have been one of the main agents that transformed terrestrial environment through surprisingly intelligent adaptation and coevolution [START_REF] Graham | Origin of Land Plants[END_REF]. Ecosystems have been evolved by developing complex networks containing both competitions and symbiotic relations as a result of ecological optimum [START_REF] Putman | Principles of Ecology[END_REF], which formed today's biosphere we live in. Indeed, natural ecosystems compatible to agricultural field such as grassland and forest is known to express symbiosisdominant effect on biomass production with respect to the species diversity [42][43]. Such productivity based on the ecological optimum is not yet sufficiently exploited in agricultural framework. The application of ecological optimum has been partially practiced in agriculture by perennial crops polyculture [START_REF] Glover | Increased Food and Ecosystem Security via Perennial Grains[END_REF][45] [START_REF]Natural systems agriculture: a truly radical alternative[END_REF], no-till farming [START_REF] Huggins | No-Till: the Quiet Revolution[END_REF], natural farming [START_REF] Fukuoka | The One-Straw Revolution: An Introduction to Natural Farming[END_REF], etc. The difficulty of cultivation method lies in the optimization of management cost and the productivity with a context of marketing. The challenge requires strong support of information technologies with open complex systems perspectives [START_REF] Funabashi | IT-Mediated Development of Sustainable Agriculture Systems -Toward a Data-Driven Citizen Science[END_REF].

Considering the bottom-up emergence of biodiversity in ecological optimum, the measurement and control is difficult to achieve in a centralized top-down manner. We propose an alternative way, the organization of citizen science to collect and share the experience of diversified polyculture practice. By sharing the data and knowledge with the use of information technology, citizen science has a possibility to realize both diversity and flexibility of measurement and management, which may be more compatible to the dynamics of ecosystems [START_REF] Funabashi | IT-Mediated Development of Sustainable Agriculture Systems -Toward a Data-Driven Citizen Science[END_REF].

Methodology of Synecoculture

As a polyculture system with ecological optimum, we introduced a novel system of agriculture based on the synthesis of ecosystems, namely "Synecoculture", mainly for the culture of vegetables and fruits [START_REF] Funabashi | Fondation de la Synécoculture: Vers une agriculture de synthèse écologique et rentable, Actes du colloque Transversalités de l'Agriculture Biologique[END_REF]. Synecoculture is a high density mixed polyculture of edible species, that stems from the observation of natural ecotone and biodiversity hotspots. We associate plants according to their symbiotic interactions with soil, environment, and other vegetation, which augments the biodiversity of the culture beyond natural state. The fields overlap with a transition to mature secondary vegetation with human use [START_REF] Newbold | Global Effects of Land Use on Local Terrestrial Biodiversity[END_REF]. The management of culture is based on the diversity and succession, similar to the forest renewal. We first plan the vegetation according to the environmental condition, and let the ecosystem self-organize the products with least human intervention: No tillage, no fertilizer, no chemicals, other than introduction of edible species. We harvest from the formation of ecological niche, in which thinning harvest from mixed and dense vegetation is effective for both year-round harvest and weed control. This system brings us quite diverse products all round year with extended culture seasons and thus suitable for local daily consumption.

Experiments of Synecoculture

Experiments of Synecoculture take place in several fields including professional farms and family gardens in Japan. Edible plant species numbers introduced In the proof of concept experiments are listed in Table 1. The edible species diversity introduced in Synecoculture fields, nothing but on monitored 0.3 ha, exceeds the item number of the traditional Satoyama agriculture in a regional scale, and is compatible in terms of cultivar variety. Although the growth of the plants are distributed in a long-tail and do not necessary survive after competition, human introduction of plant diversity interacts with both local flora and fauna, that creates a unique augmented ecosystem in ecological optimum [START_REF] Funabashi | IT-Mediated Development of Sustainable Agriculture Systems -Toward a Data-Driven Citizen Science[END_REF]. This implies that Synecoculture has a high potential to increase agro-biodiversity even in a small scale. Items produced were sold at a commercial farm(Ise) on site, at local restaurants, including on-line sales of 80 products all over Japan. 1. Edible plant species diversity introduced during Synecoculture experiment in 2010/6-2014/5. Ise, Todoroki, Oiso farms are Synecoculture farms in Mie-ken, Tokyo, and Kanagawa-ken in Japan, respectively. The total experimental surface of these farms are about 0.3 ha. Other citizen farms also exist with their own initiatives. Numbers in parentheses describe the number of species that survived more than one year after introduction or produced the seeds. For a comparison, GIAHS Noto is the UNESCOcertified globally important agricultural heritage system(GIAHS) in Noto peninsula, Japan with 186,600 ha surface covering the northern half of Ishikawa-ken, renowned by its high biodiversity conservation value [START_REF] Hashimoto | Measuring ecosystem services of social-ecological production landscapes of Noto: toward the economics of Satoyama[END_REF].

Exploration of Ecosystem Agents as an Interface

The productivity in ecological optimum is constrained by environmental conditions. Basic physical parameters such as temperature and precipitation are known to be the major determinants of vegetation [START_REF] Kottek | World Map of the Köppen-Geiger climate classification updated[END_REF] [START_REF] Holdridge | Determination of world plant formations from simple climatic data[END_REF]. Sunlight also plays central role in photosynthesis. These parameters vary depending on local geographical condition and existing vegetation. At the same time, actual plant community varies depending on the seed bank, competition, vegetation succession, delayed action of past conditions [START_REF] Verbitskii | Ecological Optimum and Effect of Delayed Action of a Factor[END_REF], etc, within the same climate classification. The bidirectional dependencies between physical conditions and vegetation is an essential basis of ecosystems as complex systems. To treat the local diversity of plant community and make use of it in polyculture system, we need to know about the actual components and dynamics of ecosystems agents besides physical parameters of the environment.

Since ancient times, phenological events such as blossoming of flowers and certain animals' behavior were considered to be key indexes to detect the seasonal phase of ecosystem dynamics. With the development of ecological database, it is possible to link such phenological biodiversity observation with practical prediction and control of ecosystems management, including farming system with ecological optimum. With the aid of database, sensing and communication technology, we can attribute each ecosystem agent to the property of interface for the management of ecosystems. Generally an interface is an element between two systems, which intermediates between inputs and outputs for certain objective. For example, harvest of edible species is the output from ecosystems, while planting, releasing, and introducing them correspond to input. one can consider each ecosystem agent as an interface to sense and make decision of input and output on ecosystem. The functional roles of plants and animals can be used as relational indexes for ecosystem management. With the development of interactive database between biodiversity observation and ecological knowledge, we try to explore and share practical framework to make use of ecosystems agents as an interface of sustainable agriculture.

As an example, Figure 1 shows the comparison between different ecosystems with common species based on the database of Synecoculture [START_REF] Funabashi | IT-Mediated Development of Sustainable Agriculture Systems -Toward a Data-Driven Citizen Science[END_REF]. Geographically distant ecosystems can be compared in terms of biodiversity with a time line, from which we can estimate what kind of species can be commonly introduced, and what is the conditions that makes the difference. In this example, the earlier appearance of the species in Tokyo than in Paris may indicate a correlation with meteorological data such as temperature since spring comes earlier in Tokyo, which provides a candidate of effective physical parameters. In application, the species appearance can be interpreted as the biological reaction to environmental condition in total. When the culture condition is not equivalent and impossible to control each factor in an open environment in operation, the similarity of ecosystem reactions may consequently be an effective index for the management, as is the case in farming folk wisdom. In any region of the world, we can find diverse relations between climate, animals and plants that infer ecologically consistent structure. These include actual causal structure of ecosystems, and also so-called pseudo-correlation in a massive data analysis, the correlation without direct causality but still applicable to the actual management of complex systems. These symbols and relations form certain universal structure in human cognition in various culture, which is pointed out to be essentially common to scientific thinking [56]. To determine the factors that support a species niche is necessary to diversify the polyculture in ecological optimum, which is a complex entanglement that depends on environmental condition, associated biodiversity, farming option, etc. The analysis is further developed in collaboration with Open Systems Data Analytics, which is described in section 3.

Open Systems Data Analytics

There is a growing necessity for dealing with open systems such as computer networks, healthcare, and global climatic changes. The data related to ecology and agriculture are also exponentially increasing, such as biodiversity database, monitoring data of agricultural fields, buying history of products, nutrition profile, geoenvironmental assessments, etc. Such "big data" is gaining greater importance on the future of human society. In Open Systems Data Analytics, we are trying to develop novel analytical tools of massive data that have many variables dependent on each other, using probabilistic graphical models and methodologies of physics [START_REF] Isozaki | Minimum Free Energy Principle for Constraint-Based Learning Bayesian Networks[END_REF] [START_REF] Isozaki | Combining Stage Algorithm for Discovering Causal Models[END_REF].

In open systems, it is difficult to understand and control the whole systems due to their complex interactions and dependencies. Data oriented approaches are effective for understanding open systems when the subsystems are not explicitly defined. From the viewpoint of data analysis, We consider that causal relation inference from observational data is useful for understanding and managing open systems when possible practices of controlled experiments are limited during operation. Although the true cause-effect relationships is difficult to prove completely due to many unobserved variables, it is possible to make effective interventions as we augment the accuracy of the causal relationship inference in the systems [START_REF] Pearl | Causality, Models, Reasoning, and Inference[END_REF]. A causal analysis may thus remain at the level of providing some suggestions for managing systems and repeatedly improve it with the introduction of possibly latent variables and new data .

We therefore apply Tokoro's open systems science [START_REF] Tokoro | What is Open Systems Science?[END_REF] [60] with adaptation to a causal data analysis, and propose a methodology, which we call (a version of) Open Systems Data Analytics, as follows:

1. Define the problem and its domain. More precisely, the definition of causal relationship is adopted from the Reichenbach's principle of causality on the sets of three (or more) variables [START_REF] Reichenbach | The Direction of Time[END_REF]. it is based on the finding of directed Markov patterns in correlation networks for random variables by removing pseudo-correlations with statistical tests.

Analysis of Synecoculture database

In Synecocultur project, polyculture with ecological optimum requires a huge amount of information on biodiversity, interactions, and vegetation succession to optimize as a productive system. Such information contains huge number of parameters, generally sparse, possibly biased, open-ended, etc, because it relies on human observation. Still, it can bring useful information and intriguing insight on the management if powerful algorithmic analysis is combined with appropriate human evaluation. Open Systems Data Analytics can combine massive data analysis tools with diverse feedbacks by humans working on site, so that to maximize the synergy between background knowledge, computational power and human intuition. We apply the methodology to maximally augment educational effect of participants. The aim is different from conventional science that seeks for the strong reproducibility and predictability of phenomena with external observation, but rather to explore multiple choices for a better management from inside of open complex systems in operation, where internal observation is structurally inevitable. We here demonstrate an example of the causal data analysis in Open Systems Data Analytics, the first step of the procedures (1)-( 4). We analyzed biodiversity data obtained from Synecoculture farms and surrounding environment in Japan between 2011/4-2013/3. The data are the binary occurrence records of observations about plants, insects, date, and places, which defines the process (1) and ( 2). The analysis of the process (3) was performed using an algorithm called Combining Stage (CS) [START_REF] Isozaki | A Robust Causal Discovery Algorithm against Faithfulness Violation[END_REF]. From 11911 observations that comprises 1232 variables (1150 plants and animals, 3 years, 12 months, 67 places), 1131 sets of Markov dependency were detected on 611 variables.

Figure 2 Left shows the inferred causal model with a directed graph. We evaluated the suggestion with respect to the observers' experience and classified into 3 categories:

1. Trivial such as the causality between observation places and discarded from the analysis. 2. Unknown to the experience or other literatures, therefore candidates for further observation. 3. Known to the experience or other literatures, therefore validation instance of the model.

We then evaluated the information of 2. the suggestions unknown to experience by the following information quantity I(c) for each unknown suggestion with a strength of inferred causality c:

I(c) = -log #(known suggestions with inferred causality ≥ c) + 1 #(known suggestions) + 1 ,
where #() represents the number of suggestions, and the additions of 1 correspond to count a chosen unknown suggestion itself. The information I(c) for each unknown suggestion is defined as the information of significance (p-value in statistical tests) with respect to the known suggestion distribution as a model.

It represents the amount of information that the model would gain as a reward if the unknown suggestion was revealed to represent plausible dependence by further observation. The I(c) is 0 when there is no known suggestion. It expands the value range as validated known suggestions increase, which reflects the plausibility of the model with respect to the accumulation of human observation and experience.

Figure 2 Right shows the example distributions of unknown, known causality suggestions and distribution of I(c) for each unknown suggestion with respect to the inferred causality. Unknown causality suggestions with high I(c) exist, which are the preferential candidates for future observation. By incorporating these suggestions and by iterating the step 5 of Open Systems Data Analytics, it is expected to modify the observation framework by means of internal observation so that to achieve a better fit between causality analysis and observers' experience.

For further analysis, we plan to add environmental parameters such as temperature, humidity, precipitation, hours of sunlight, etc, in order to incorporate objective measures that do not depend on human subjectivity. Furthermore, since ecosystems inherently contain transient dynamics and farming options could change according to the objective of production, we expect to repeat and integrate the analysis year-by-year to investigate the degree of achievement in the steps 5 and 6. (Takashi Isozaki and Masatoshi Funabashi)

P2P Food Lab

The goal of the P2P Food Lab project is to develop innovative and sustainable solutions for the growing, harvesting, transporting, consumption, and disposal of food. We evaluate new technologies that support new modes of crop production, in particular small-scale and micro agriculture. As we are fully aware that technology alone cannot solve the current crises that our society is facing, including the challenges facing agriculture today [START_REF] De Schutter | Report of the Special Rapporteur on the right to food, United Nations General Assembly[END_REF][START_REF]The State of Food and Agriculture, Food and Agriculture Organization of the United Nations[END_REF][START_REF] Eea | The European environment state and outlook 2015: synthesis report[END_REF][START_REF] Soer | The State of Soil in Europe, A contribution of the JRC to the European Environment Agencys Environment State and Outlook Report[END_REF], P2P Food Lab includes a strong social aspect and aims to build alternative solutions using a bottom-up approach that involves all stakeholders, including citizens. The first phase of the P2P Food Lab project is to design an on-line/offline platform that groups the four main pillars -agriculture, communities, technology, and science, -and to leverage the network effect to engage many people and increase the social impact of the platform.

P2P Food Lab Starter Kit

In our first experiment, during Summer 2014, we developed a "Starter Kit" for micro-agriculture that consisted of a small, Internet-connected greenhouse. A sensor box was placed inside the greenhouse that took daily images of the crops and measured the air temperature, air humidity, and sunlight. The sensor box was built using standard off-the-shelf components such as Arduino, Raspberry Pi and standard webcams. The goal of the connected greenhouse was to create an on-line social network of participants and gardeners, and evaluate the use of sensors for the study of crop growing.

The CitizenSeeds Experiment

The Starter Kit still represented an entry point that was too steep to engage many people. We also found that we needed to give participants clearer guidelines in order to obtain reusable data. Consequently, we simplified the requirements for participation in Summer 2015. In the new experiment, called CitizenSeeds, participants only needed a camera-equipped mobile phone and a 1m 2 plot of land (raised bed or plain soil). We also defined a fixed collection of seeds to plant and a fixed, shared planting schedule. These two elements greatly help in aligning the participants, comparing the data, and stimulating social interaction.

To measure the environmental data (sunlight, air temperature, soil humidity) the participants had the option to use the Flower Power device produced by the Parrot company. They also had the possibility to buy soil for their plot to normalise the soil used in the experiment, however few participants chose this option.

Participants are asked to upload photos of their plot and the vegetables once a week. About 80 people registered of which about 30 contribute to the experiment. A single web page displays the states of the plots and the environmental data of the community ‡ .

Future developments

The Citizen Seeds project seems to have the right level of ingredients to evolve into an on-line platform for micro-agriculture. The main long-term developments that we envision are:

-Distributed organisation: Scaling up from tens of participants to thousands of participants will require the introduction of new organisational scaffolding structures [START_REF] Lane | From Population to Organised Thinking[END_REF]. -Citizen Science: Introduce well-defined protocols for planting and measuring in order to perform scientific experiments with the involvement of many amateur gardeners. Topics of interest to be studied include analysing the effects of crop intermixing [START_REF] Bedoussac | Intercropping 2014. An application of ecological principles to improve nitrogen use efficiency in organic farming systems[END_REF][START_REF] Corre-Hellou | The competitive ability of pea barley intercrops against weeds and the interactions with crop productivity and soil N availability[END_REF][START_REF] Malézieux | Mixing plant species in cropping systems: concepts, tools and models. A review[END_REF][START_REF] Loreau | Partitioning selection and complementarity in biodiversity experiments[END_REF], measuring the evolution of soil biology [START_REF] Abbott | Soil Biological Fertility, A Key to Sustainable Land Use in Agriculture[END_REF][START_REF] Bärlocher | Leaf Mass Loss Estimated by Litter Bag Technique[END_REF], tracing the phenotypical adaptation of varieties to local conditions. -Increase plot size: Develop similar experiments and data sharing for larger plots and with (semi-)professional participants. The biggest interest is to study alternative farming techniques [START_REF] Kremen | Diversified farming systems: an agroecological, systems-based alternative to modern industrial agriculture[END_REF] that have been studied very little by agronomists until now, including synecoculture, permaculture [START_REF] Mollison | Permaculture One: A Perennial Agriculture for Human Settlements[END_REF][START_REF] Bell | The Permaculture Way[END_REF], and bio-intensive micro-farming [START_REF] Jeavons | How to Grow More Vegetables (and Fruits, Nuts, Berries, Grains, and Other Crops) Than You Ever Thought Possible on Less Land Than You Can Imagine[END_REF]. The platform also allows the community explore new technological tools and sensors to monitor and optimise these cropping techniques, using a collaborative approach [START_REF] Campbell | Community food systems: Strengthening the research-to-practice continuum[END_REF][START_REF] Introne | Solving Wicked Social Problems with Socio-computational Systems[END_REF]. ‡ See https://p2pfoodlab.net/CitizenSeeds/experiments/4.html (Peter Hanappe)

5 The Sound Beehive Experiment

Overview

The Sound Beehive Experiment monitors the development of a bee colony on the basis of the sounds it generates, and creates artistic expression mediated by artificial intelligence. For this purpose, we developed a beehive that is equipped with sensors, microphones and cameras. The Sound Beehive is installed in the Urban Bee Laboratory on a rooftop in the Brussels city centre. Data is streamed to repositories and analyzed using statistical techniques and graphic visualizations.

Introduction

An Ethological Approach Honeybees are bio-indicators. They provide a constant stream of information on the environment in which they forage, via their daily activity, and via the pollen and nectar they harvest. Environmental problems such as the use of pesticides can be detected by monitoring the colonies with audio and video tools and by scanning their daily activity over several years [START_REF] Michels | A Beehive Monitoring System Incorporating Optical Flow as a Source of Information[END_REF]. In nearly all industrialized nations, bee colonies are now threatened. The compromised state of the foraging areas for bees is worrisome. By using bees as bio-indicators and by translating the information into artworks, This project aims to make citizens aware of the increasingly negative effects of our lifestyle and methods of industrial production. AnneMarie Maes is a media artist collaborating with computer scientists and engineers to develop art-science projects.

Interested in showing the hidden structures in nature, we try to use innovative technological methods to probe the living world.

Methods

Basic Elements To study the bees in their natural environment, following the footsteps of von Frisch and other ethologists [START_REF] Frisch | The Dancing Bees: An Account of the Life and Senses of the Honey Bee[END_REF], we have built a customized 'sound device'. Microphones inside the beehive enable us to continuously monitor the colony's buzz. Together with outside and inside video monitoring it forms a non-intrusive scanning device for controlling the colony's health and development. We also installed a network of temperature and humidity sensors spread throughout the beehive. The annotated video and audio data are uploaded to our open source video database [START_REF]The Bee Laboratory open source video database[END_REF]. All time-stamped sensor data from the lab's weather station, as well as the temperature and humidity data measured inside the beehive, are made public on [START_REF]The Bee Laboratory open sensor data[END_REF].

Instrumentation Our custom-built audio, video and sensor device is integrated in a Warré beehive (Fig. 5). It is a sustainable beehive in which the colony develops at its own pace. We started to customize our Warré beehive by putting electret microphones in the top cover and by attaching contact microphones in the frames of the brood box. All microphones are connected to pre-amps stored in the rooftop. They are powered by a battery that is located a few meters away from the hive to avoid the creation of electro-magnetic fields.

For recording the video images, we use Raspberry Pi computers. The Raspberry can be easily integrated in complex installations and is equipped with a series of USB and Ethernet connections to function in a network of devices. We integrated two small high-resolution cameras in our setup; one camera to record the activity on the landing platform and a second infrared camera to registrate the activity inside the brooding box.

The analysis of the images gives us information on the relation of the bees to the environment. A beecounter is integrated in order to determine the in/out flux and detect homing problems related to pesticide contamination. The images also give us information about the pollen supply and the development of the colony related to the activity level of forager bees, fanning bees, dead bees and lazy bees on the landing platform.

Sensing of Bee Activity Related to the Environment A bee colony is very responsive to the biotopes of which it is a part. The production of honey is dependent on the flowers we grow, the plants we like, and the garbage or pollution we produce. The colony is also very sensitive to environmental variables such as outside temperature, rainfall and humidity, the wind and hours of sunshine. We therefore compare the behavior of the bees and the development of the colony with the data from the weather station. In our rooftop field lab, we have installed a Libellium agriculture kit [START_REF]Libellium agriculture kit[END_REF], including several environmental sensing devices. E.g., the hours of solar activity, as well as the soil composition, determine the nectar flow of the flowers and their visits by the bees. Nectar secretion increases as pollinators visit the flower.

We set up a database of the pollen contained in the honey of our urban bee colonies and we started to determine the pollen source. By studying the pollen in a sample of honey, it is possible to collect evidence of the geographical location and genus of the plants that the honeybees visited [START_REF][END_REF]. As such, we start to trace green corridors through the city.

Data Processing In January 2015 we started analyzing the recorded files. We scanned the sound files in terms of their brightness, loudness and noise level. For the analysis of the video files, we made use of motion detection via the frame difference method. The analysis of the sound files is a complex matter. We therefore use techniques of Artificial Intelligence in collaboration with the Brussels Free University. We have recorded large amounts of data in order to investigate whether we can detect patterns. All together these data give us plenty of parameters to combine and to play with, to create models and to compare different moments in time and thus to study the behavior of the colony relative to timeline/season and environmental parameters.

Visual Expression of the Sound Beehive

A video shows a graphical rendering of AI analysis of colony behavior combining real audio data with measurements of the microclimate inside the hive: temperature, CO2 and humidity Another video shows 365 days of activity inside a real observation beehive, played back at high speed. The images were recorded with an infrared camera inside the hive and processed using pattern recognition, AI and computer graphics algorithms. These images offer the stunning visual experience of a bee colony in action (Fig. 6). To create an immersive sound installation we the sound files recorded in the hive. The Scaffolded Sound Beehive (Fig. 7) is a wooden sculpture, constructed using open source digital fabrication and mounted on scaffolds of 2,5 meters high. Visitors can enter this upscaled model of the Warré beehive and experience an auditory artistic interpretation of hive activity. We processed the recordings (made in the real beehive) using sophisticated pattern recognition algorithms and artificial intelligence analysis software, and edited the sound files by adding swirling electronic sound clusters to sonify the ebb and flow of swarm activity in the hive.

Art Exhibition

The Sound Beehive immersive installation has been shown at the Institute of Evolutionary Biology (IBE) in Barcelona (May-June 2015) [START_REF]The Sound Beehive installation at the Institute of Evolutionary Biology (IBE) in Barcelona[END_REF], and at the AI and the Arts exhibition for the international conference of Artificial Intelligence in Buenos Aires, Argentina (July 2015) [START_REF]The Sound Beehive installation at the AI and the Arts exhibition for the international conference of Artificial Intelligence in[END_REF]. The enormously positive response of viewers shows clearly that the presentation of scientifically inspired art can have a strong impact and raises awareness of important societal issues, and also that art-inspired science can have a fruitful positive effect to push science in new directions.

(AnneMarie Maes) 6 Open Systems Simulation

Motivation

We as a modern society are facing many urgent yet unsolved problems, including the possible global shortage of natural resources and food, environmental pollution, economic instability, poverty, crisis of medical and health care systems, social insecurity, computer and network fragility, and so on. All of these are problems of open systems, which is literally a system that is open to the outer world and shows temporal development as interactions with the outer world progress [START_REF] Tokoro | Open Systems Science From Understanding Principles to Solving Problems[END_REF]. As a consequence, we can neither have full control over the systems nor restart from the beginning to let them reproduce identical behaviors. Science has had difficulties in handling these kinds of problems because its methods rely on validation or falsification of hypotheses by observing reproducible instances. However, if simulation virtually reproduces an one-time-only-problem, the boundary of applicable range of science can be pushed far beyond. Based on the above insight, an ultimate goal of the open systems simulation is to develop a framework and methods of simulation that can handle open systems problems in a constructive and an operational way.

Practice

Epidemics is an important factor of social-ecological systems that threatens productivity and sustainability. As a specific instance, we have been developing an integrated simulation of infectious disease, especially targeted for influenza [90] [91]. In order to understand the essential aspects of influenza epidemiology, it is not enough to simply look into a particular part such as the micro mechanisms and processes of infection separately in a closed manner. We need to simultaneously take into account surrounding yet further-reaching factors, such as the structure and dynamics of human society, the population dynamics of humans, ecosystems (including those of other species), seasonal conditions, geographical constraints, and so on in order to take an integrated and holistic view. As a first step of our endeavor, we have built a bi-layered model which interconnects macro simulation of epidemic circulation among hosts and micro simulation of viral evolution driven by immunological interaction among hosts and viruses. In the model, we showed possible mechanisms that generate the limited diversity of viruses, which is one of the fundamental yet unexplained temporal behaviors observed in the evolution of real influenza.

(Takahiro Sasaki)

One-Health Food Lab

Under the slogan of "One World, One Health", the Wildlife Conservation Society convened public health experts from around the world to adopt the Manhattan Principles in 2004. The first principle is: "Recognize the essential link between human, domestic animal and wildlife health and the threat disease poses to people, their food supplies and economies, and the biodiversity essential to maintaining the healthy environments and functioning ecosystems we all require." It exemplifies the interdisciplinary movement toward solving the world's complex, interlocking problems, rather than simply taking reactive countermeasures against zoonotic diseases [START_REF]GRF One Health Summit[END_REF]. In One-Health Food Lab, we scientifically examine foods and medicinal herbs, which were produced in different growth conditions and placed in the market, to evaluate their quality and safety to the health of human and other creatures sharing the earth.

Activity in 2014

In 2014, we studied functions, compositions and tastes of common vegetables in relation with their farming methods: Conventional(C), Organic(O) and Natural § (N). In one study on cabbage using a smart taste-sensing system for five different tastes (sweetness, saltiness, sourness, umami and bitterness), bitterness was found to be the one that significantly differentiated N-cabbage from the others and also the most lasting one among the tastes [START_REF] Yoshida | Functional and compositional characteristics of conventionally, organically and naturally grown cabbage and carrots[END_REF]. In another study through § Synecoculture products in section 2.

absorption spectroscopy and metabolome analysis, the UV-absorption level and the phytochemical content were both detected to hold the order N¿O¿C in cabbage or C¿O¿N in carrots [START_REF] Yoshida | Taste analysis on conventionally, organically and naturally grown cabbage. 1st IMEKOFOODS[END_REF]. In addition, antibiotics were found in O-products; pesticides, carcinogens and synthetic drugs were detected independently of the farming method. Through these studies, physiological differences of plants related with their growth environment and their effects on human health as foods and drugs have been partly elucidated.

(Kaoru Yoshida)

Conclusion

With the perspective of open complex systems, 6 projects have begun to collaborate in e-laboratory that independently interact and tackle the urging problems of food production in various aspects of social-ecological systems. The founding philosophy and initial steps of exploration are demonstrated as a progress report. Without any top-down restriction of methodology and expression other than open complex systems, our projects are in open collaboration inside and outside of the e-laboratory, expecting bottom-up convergence of new ideas that could be supported by plural independent scientific paths.

We also expect that with this form of collaboration, new effective methodologies to treat open complex systems might be elaborated, not necessary constrained in food production but applicable to a wide range of open systems problems. When combined with interactive technologies and cloud computation, data analytics and simulation are traditional yet prominent domains to trigger such change in scientific methodologies.

The design of agriculture varies according to the local climate condition, selection of culture species, available resources, preference of consumers, health effect, disease risks, environmental preservation effort, economical state, community dynamics, means of distribution, etc, which are assigned parallelly in each project. We require an integrated approach to widen the choice of possible strategies in order to develop sustainable food production in an ever-changing environment. At the same time, fundamental question such as ecosystems function and health effect of food should maintain scientific objectivity without catering to a specific social activity. From each part to the whole, subsystems related to food production should be redefined while operating as open complex systems, intriguing effective social-ecological change with a scientific support.

This e-laboratory is a challenge that brings us back to the origin of agriculture and question de novo the design of food production ranging from urban gardening to natural state. The methodology and expression vary among projects, though we commonly share the mutual principle of challenge: Human activities from industrial production to citizen initiative should bring positive impacts on nature by augmenting the ecological state, and human society in return benefits from its ecosystem services. Human augmentation of ecosystems, or ecosystems leveraging, that exceeds the conventional reach of agriculture.

A possible outcome from this challenge is the derivation of a protocol that can infer and continuously ameliorate a suitable and sustainable food production system in a wide range of social-ecological condition. This protocol is not a mere ensemble of past data in various environment, but a trial-and-error tutorial that describes how to yield a concrete design of agricultural system in a given transient condition. This corresponds to a meta-algorithm that constantly integrates new data and provides wider choice of exploration in the practice of agriculture. The protocol should be extensively applicable in any arable and social condition, including future climate change. The tailoring of site-specific management system is expected to bring self-sufficient practice for the natural source management in highly variable and diverse farm conditions typical of resource-poor farmers in developing world, which is estimated to be about 1.4 billion people [START_REF] Altieri | Agroecology: the science of natural resource management for poor farmers in marginal environments[END_REF].

The databases, tools, and tutorials developed in each project will gradually be available in public including the CS-DC interfaces.

Acknowledgement

We acknowledge Hidemori Yazaki, Kousaku Ohta, Tatsuya Kawaoka, Kazuhiro Takimoto, and Shuntaro Aotake who worked as research assistant in the sections 2 and 3, Kana Maruyama and Tatsuya Hiroishi in the section 3.

Fig. 1 .

 1 Fig. 1. Comparison of species diversity between different ecosystems on Synecoculture contents management system. Bottom: Observed species in Paris, France on 2013/6/15. Top: Corresponding species observation in Tokyo Japan, whose appearance seasons range over several months.

2 .

 2 Set variables and get their data. 3. Construct a causal model by causal inference algorithm from data. 4. If it is difficult to interpret causal relations in the model, important latent variables probably exist. Infer them and add data of the new variables to the dataset as far as possible. 5. Repeat the procedure (3)-(4) until a satisfactory result (or consensus) is obtained. 6. Do predictions, interventions, and/or construct theories.

Fig. 2 .

 2 Fig. 2. Left: Graph visualisation of the causality suggestion. The circles and the edges denote variables and Markov dependencies between two variables, and the line thickness denotes strength of dependencies quantified by mutual information. For variables A and B in the figure, if A → B, A denotes a cause of B in the sense of Markov dependence. Colours of edges indicate that the suggestion was 1. trivial(green), 2. unknown(red) and 3. known(blue) to the observer's experience. An undirected edge means that there is a Markov dependence but without significant inference of causal direction. Right: Example density distributions of unknown(red line), known(blue line) causality suggestions and information(orange circles) distribution of unknown suggestions.

Fig. 3 .

 3 Fig. 3. From left to right: 1) The first P2P Food Lab greenhouse near Paris, 2) Subsequent version of the greenhouse in Brussels, 3) Sensor box with camera, 4) Screenshot from the web site, 5) Time-lapse of the radishes and weather data, 6) Children from participating school near Paris.

Fig. 4 .

 4 Fig. 4. From left to right: 1) The seeding calendar, 2) A 1.2×1.2m plot with seedlings, 3) Matrix of photos uploaded by participants, 4) Visualisation of recorded environmental data.

Fig. 5 .Fig. 6 .

 56 Fig. 5. Left: Diagram of the instrumented Sound Beehive, Right: the Scaffolded Sound Beehive Sculpture

Fig. 7 .

 7 Fig. 7. Top: streaming activity on the landing platform. Bottom: video-analysis of the activity inside the beehive.


Dimas Novrisal

Nadia Hamani
email: nadia.hamani@u-picardie.fr

A Elmhamedi

Tresna Soemardi

Performance Improvement of Baggage Handling System in the Soekarno Hatta International Airport

Keywords: Modeling, discrete-event simulation, performance measurement

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Globalization has big impact in the airports all over the world. Many international airports increased in large growth of passengers in recent years. There is 2.835 billion passengers of the airplane in the world in 2011 and IATA (International Air Transport Association) standard predicts that it will increased at 4.4 % in 2012, and 4.5% in 2013 [1]. Worldwide international and domestic air transport passenger traffic grew 5.9% to a new high of 5.2 trillion kilometers in the year of 2011 [2]. Nowadays, the globalization increases the importance of airports to worldwide connectivity. Passengers growth in the Airport still strong despite economic slow in many region in the world because global business and tourism depend on the air transport industry [2].

Air transport is the fastest, safest, and comfortable public transportation. Low cost airlines become popular in recent years which make prices affordable and inexpensive. Passengers are growing more and more effecting the airport with hectic rush and long queue in the peak hours. Passengers satisfaction depends on processing time in the system because the less time they spend in the system of the airport, the higher they are satisfied, however, airport must adhere to the standard of the security and safety regulation included proper identification, limited luggage weight, and safety procedures at the security checkpoint [START_REF] Manataki | A generic system dynamics based tool for airport terminal performance analysis[END_REF].

The airport management is a complex system related to the passengers, airplanes and baggage. The passengers are the most important entities in the Airport. The sustainability of airport depends on passengers because passengers are the users of airport service. Passengers' satisfaction has to be the main goal of the airport service. The airport must have adequate facilities and public area to serve the passengers properly. Passengers' satisfaction depends on the performance of airport in serving the passengers.

Performance of facility in the airport can be measured by simulation technique. Many researchers develop simulation technique to measure the capacity of the airport, utilization of each area, passengers waiting time, and passengers processing time in the airport system. Discrete event simulation has been used to measure performance of the system in the departure terminal of SHIA. ProModel simulator version 7.5 of ProModel Corporation is used in order to simulate the system. The study consists of four steps: measurement the performance of existing system, measurement the performance of new system, and compare the performance of two systems. Several scenarios develop to see the reliability of new system with the growth of passengers until 2030 to the capacity of airport.

The results obtained through ProModel Simulator were summarized in two categories; Entity Activity and Utilization of Location. From the results, we conclude that the new system has a better performance than the existing system. The new system can reduce processing time and waiting time.

The scenarios result of new system show that the number passenger of SHIA in the year 2015 to 2020 has a little effect to processing time and waiting time. In the year 2025 to 2030 there is effect of number passenger to waiting time in the airport. This effect will be related to processing time in the system.

After measurement of the performance of the existing system, further work will focus on measure qualitative indicator of baggage handling system at Soekarno-Hatta International Airport. Qualitative indicator related to perception of passenger to the service of the airport. We have to study the qualitative indicators to make a better analysis and understanding of passenger satisfaction.