Patrícia Macedo
email: pmacedo@est.ips.pt

Luis M Camarinha-Matos

Value Systems Management Model for Co-Innovation

Keywords: collaborative networks, value systems, intellectual property, coinnovation

Nowadays innovation and collaboration are strategic issues for enterprises to remain competitive in the global market. Many new developments are carried out with external partners, including universities and research institutions aiming to generate novel solutions in order to improve business performance and sustainability. However, the balance between intellectual property protection and intellectual property sharing is hard to manage. In order to increase the sustainability of innovation networks it is important to provide mechanisms to easily define the profile of the collaboration and to assess the degree of alignment with the potential partners. This paper aims to discuss how these mechanisms can be provided through the implementation of a Core Value Management System in the scope of coinnovation.

Introduction

Nowadays, the strive to achieve innovation correspond to a very costly and risky process, being difficult for companies to innovate in short periods of time in a global market, where customers' needs change quickly and the products/services' life cycles get shorter. This is a particular tough challenge for small and medium enterprises (SMEs). Therefore, many new developments are carried out with external partners, including universities and research institutions with the aim to improve business performance and its sustainability, as well as to reduce risks.

Co-innovation is a new business paradigm where it is assumed that firms or individual persons can establish a partnership with the aim of jointly developing new ideas and new products [START_REF] Gloor | Swarm creativity: competitive advantage through collaborative innovation networks[END_REF]. These kinds of partnerships raise new challenges in the scope of trust management and intellectual property management [START_REF] Flores | A Balanced Scorecard for Open Innovation: Measuring the Impact of Industry-University Collaboration[END_REF][START_REF] Chesbrough | The era of open innovation[END_REF], since the balance between intellectual property sharing and intellectual property protection is hard to manage. Moreover, if partners have different perceptions of outcomes and different notions of the expected behavior, this might, in some cases, lead to some behaviors that compromise collaboration sustainability. For instance, if a firm does not believe in the importance of sharing knowledge, then it can be expected that its behavior will not contribute positively to the development and implementation of new ideas or new technologies in alliance with other firms.

Since a Value System defines the set of values and priorities that regulate the behavior of an organization, it determines or at least constrains the decision-making processes of that organization. Therefore, the identification and characterization of the Value Systems of the network and its members is fundamental when attempting to improve collaboration [START_REF] Macedo | Distinct Approaches to Value Systems in Collaborative Networks Environments[END_REF]. Consequently it is important to develop mechanisms to facilitate the definition of the profile of the co-innovation partnership in terms of values. Moreover, it is also relevant to develop mechanism to assess the degree of alignment between the values required for the partnership and the values hold by the potential partners.

The research performed aimed to address the following question: What would be an adequate modeling framework for supporting effectively the specification and analysis of Value System in collaborative environments?

Even so, this paper presents only part of the results achieved during this research, more specifically, it discusses how the models and methods proposed in [START_REF] Camarinha-Matos | A conceptual model of value systems in networks[END_REF][START_REF] Macedo | A method to analyse the alignment of core values in collaborative networked organisations[END_REF][START_REF] Macedo | Applying Causal Reasoning to Analyze Value Systems[END_REF] can be applied to analyze and assess the level of alignment between the network and the potential partners in terms of collaborative innovation profile.

Contributions to Sustainability

The development of new products and services in a short period of time is a key condition to survive in the global market, however this represents also a big challenge for small and medium enterprises. The co-innovation paradigm brings a new way to conduct innovation, being focused on the cooperation with others to achieve innovations. In order to support this paradigm it is important to provide mechanisms to effortlessly define the values profile required for the innovation network and to assess the degree of values alignment between it and its potential partners. This paper aims at contributing to sustainability under the economic perspective in the way that it proposes mechanisms to deal with some of the challenges of co-innovation, thus leading to better survival of SMEs in turbulent market conditions.

Related Work on Value Systems Management

Early Value Systems management studies have been conducted essentially in social sciences, where scientists have discussed the importance of values management for the success of organizations and the importance of values alignment. For instance, Rokeach and Schwartz [START_REF] Rokeach | The nature of human values[END_REF][START_REF] Schwartz | Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries[END_REF] developed some empirical methods to identify corevalues. Based on this work they proposed organizational core-values taxonomies. From the economic field perspective, the Value System concept has been developed based on the assumption that value means how much (usually money) a product or service is worth to someone. This notion has been introduced by Porter [START_REF] Porter | Competitive Advantage[END_REF], that considered that Value System management comprises the management of the set of activity links where there is value creation, such as the links among a firm and its suppliers, other businesses within the firm's corporate family, distribution channels and the firm's end-user customers. This notion has been extended by Alle [START_REF] Alle | Reconfiguring the Value Network[END_REF] towards supporting a wider notion of value under which the term is associated to "anything that can give rise to exchange", leading to the Value Network Model. In recent years some studies have explored the importance of Value Systems in the context of Collaborative Networks (CN) [START_REF] Macedo | Distinct Approaches to Value Systems in Collaborative Networks Environments[END_REF][START_REF] Zineldin | Towards an ecological collaborative relationship management A "co-opetive" perspective[END_REF][START_REF] Abreu | On the Role of Value Systems and Reciprocity in Collaborative Environments[END_REF]. Furthermore, a set of tools (frameworks, methods and a web application) [START_REF] Macedo | A method to analyse the alignment of core values in collaborative networked organisations[END_REF][START_REF] Macedo | Applying Causal Reasoning to Analyze Value Systems[END_REF] have been proposed based on a Value System Conceptual Model to support the configuration and analysis of Value Systems in collaborative environments. However, such set of tools have just been applied to CNs in general terms, none of them being applied to support coinnovation management in particular.

Core Value System Management Model

In previous works, we have proposed a conceptual model for Value Systems [START_REF] Camarinha-Matos | A conceptual model of value systems in networks[END_REF] in an attempt to provide a unified definition of the concept that embraces not only the notion accepted in Sociology, but also the notions developed in the Economy and Knowledge Management fields for Value Systems. The set of characteristics that each organization (or network of organisations) considers as the most important for itself and that motivate or regulate its behavior are called core-values. Departing from the notion of core-values we have introduced a conceptual model for Core Value System (CVS) [START_REF] Macedo | A method to analyse the alignment of core values in collaborative networked organisations[END_REF], that encompasses the corevalues notion. This concept is a restricted view of the generic Value System model of which it can be considered a specialisation. The UML class diagram presented in Fig. 1 illustrates the structure of the CVS model. Accordingly, a CVS is composed of two subsystems: (i) the core-value objects subsystem, which is represented by the organization or networked organization itself; (ii) the core evaluation subsystem, which represents the elements of evaluation, such as the core-values, the coreevaluation perspective and the functions to evaluate the organization's core-values. The set of core-values of an actor and respective preferences (degree of importance) are represented according to the CVS conceptual model by the core-evaluation perspective, which becomes the main structural element in the proposed approach.

Aiming to provide methods to systematically analyze CVSs in collaborative environments, we have also proposed a set of qualitative reasoning methods [START_REF] Macedo | Applying Causal Reasoning to Analyze Value Systems[END_REF] supported in a framework of analysis based on qualitative causal maps and graphs. The construction of three elementary maps is proposed in this framework.

1. Core-values influence map: Use of causal maps to show how core-values influence positively or negatively each other, and the intensity of the influence. 2. Organizations' core-values map: Use of graphs to show the core-values held by each organization and its degree of importance, as well as the core-values shared by organizations. 3. CN's core-values map: Use of graphs to show the core-values held by the CN and their degree of importance. Departing from these elementary maps, it is possible to aggregate them in order to build maps that evidence the impact of one CVS onto another [START_REF] Macedo | A method to analyse the alignment of core values in collaborative networked organisations[END_REF], facilitating the analysis process. Analysis is one of the components of the CVS management process, which includes the following activities: -Create: CVS are configured. For each CVS, the core-evaluation perspectives have to be defined for the network and for each member. -Update: CVS can be modified. As priorities can change during long-term collaboration activities, there is the need to adjust the degree of importance of the core-values. -Analyse: The created CVS has to be examined in detail, in order to understand which core-values are shared with other partners, and which core-values influence positively or negatively other CVSs. This analysis should cover the network level and the member level. At the network level is analyzed the network CVSs and the impact of the members' CVSs on the network's CVS are analyzed, while at the member level the CVS of each member and the interaction among members' CVSs are analyze. -Assess: A comparative assessment can be made, where the level of fitness between two CVSs is assessed using distinct criteria. This assessment can also cover the network level and the member level, considering in each case the degree of importance of the core-values to infer the level of CVSs alignment.

A web-based tool to support the CVS management was developed (see Fig. 2). Essentially, the CVSs alignment analysis can be performed among network members' CVSs, or between the network's CVS and the CVS of a partner or a potential partner. The tool is divided into four functional components: (i) Corevalues knowledge management -to be used by the knowledge experts in order to specify core-values and their characteristics; (ii) Core Value System Configurationto be used by brokers, network managers or network members in order to define their CVSs; (iii) Core Value Systems Analysis -to be used by brokers, network managers and network members in order to analyze their CVS; (iv) Access management tool -provides features that allow the tool manager to configure accesses to the tool according to the user profiles. [START_REF] Chesbrough | The era of open innovation[END_REF] defends that for firms to be able to successfully implement the co-innovation business model, they have to be capable of sharing their knowledge, being flexible and being responsive. However, Flores et al. [START_REF] Flores | A Balanced Scorecard for Open Innovation: Measuring the Impact of Industry-University Collaboration[END_REF] defend another set of characteristics as being the most important ones for working in an co-innovation business model. Although there is no unique set of common characteristics accepted by the researchers, it is acknowledged that the set of core-values taken by each firm, determine their behaviour in the collaboration process of creation. Therefore, the definition of the set of characteristics required to work in a sustainable way in an innovation network, can be an important step for the sustainability of these networks. As such, the collaborative innovation evaluation perspective will represent this set of required characteristics. The collaborative innovation evaluation is in fact, an instantiation of a core-evaluation perspective, and is defined as:

} , { > < = - wv dv pe innovation co
, where:

• dv is the vector of core-values considered as relevant for the co-innovation process.

[ ]

CV cv cv cv cv dv i n ∈ = : ,.... , 2 1
• wv represents the weights-vector, where each element defines the degree of importance of the corresponding core-value. These preferences can be expressed qualitatively. As previously proposed in [START_REF] Macedo | A method to analyse the alignment of core values in collaborative networked organisations[END_REF] and [START_REF] Macedo | Applying Causal Reasoning to Analyze Value Systems[END_REF], not just the common core-values will be considered as relevant criteria to assess the values alignment between two entities, but also the core-values that influence positively or negatively the core-values specified in the collaborative innovation evaluation perspective will be considered. Thus, the notion of collaborative innovation value profile is introduced to cover this idea. The collaboration innovation value profile of a partner shows which of its core-values are aligned and which are misaligned with the collaborative innovation characteristics required for the partnership. That is indeed, all the core-values belonging to the partner's CVS that meet one of the following criteria: -the core-value belongs to the collaborative innovation evaluation perspective.

-the core-value has a positive influence on a core-value belonging to the collaborative innovation evaluation perspective. -the core-value has a negative influence on a core-value belonging to the collaborative innovation evaluation perspective. The use of the mentioned set of maps based on causal maps and graph theory in the context of the innovation network, will allow us to easily identify the core-values that compose the collaboration innovation value profile of each network member. The three alignment indicators proposed to assess values alignment [START_REF] Macedo | Applying Causal Reasoning to Analyze Value Systems[END_REF]: (i) Shared Values Level; (ii) Positive Impact Level; (iii) Potential for conflict level, may be applied to calculate the Collaborative Innovation Values Profile using just minor adjustments, such as: -A collaborative innovation evaluation perspective has to be configured in the CVS of the innovation network. -A core-evaluation perspective has to be configured in the CVS of each potential partner. -Through the observation of the complete aggregate maps generated for the innovation network, the core-values belonging to each Collaborative Innovation Values Profile are identified. -The Shared Values Level, the Positive Impact Level, and the Potential for conflict level between the network and each partner are calculated, obtaining the level of each core-value in the profile. The example below illustrates how these concepts can be applied.

Illustrative example:

This example intends to illustrate how to apply the Value System Management Model in order to assess the Collaborative Innovation Values Profile Alignment. The data used in this example was obtained through a survey conducted in the scope of a case study done inside the ECOLEAD project [14]. Hence, this example cannot be considered as a full case study, but as a potential application where the scenario and the data used are both real.

The ECOLEAD project was divided into several work packages. Each work package team was created to respond to a specific set of objectives. For this illustrative example the development of some components of the VO Creation Framework (VOCF) prototype is considered. The development of this task can be considered as a co-innovation process, since it comprises the collaborative development of an innovative product carried out by a heterogeneous group of organizations. For this group the following collaborative innovation evaluation perspective was specified: Two Universities, one Research Institute of Applied research, and one SME Network joined the group (for a question of privacy, the partners are not identified). For these four organizations the work package manager has provided the data required for specifying the following core-evaluation perspectives:

Research Institute(RI) Low

Low High

SME Network

Low Moderate None

Applying the qualitative assessment inference methods (described in detail in [START_REF] Macedo | Applying Causal Reasoning to Analyze Value Systems[END_REF]) to evaluate the degree of alignment in terms of co-innovation characteristics of each innovation partner , the results presented in Table 1 can be achieved. Observing these results, it can be noticed that the Research Institute is not aligned with the Innovation Group's collaborative innovation evaluation perspective. Furthermore, if we determine the collaborative innovation values profile (see Table 2) for each potential partner, we realize that group manager should pay special attention to the Research Institute behavior, since it presents some risk. This risk comes due to the fact that it defends Uniqueness (being unique) as an important characteristic, and the Uniqueness core-value has a negative influence on Knowledge Sharing, which is a core-value belonging to the collaborative innovation evaluation perspective, as it is illustrated in the complete aggregate core-values map presented in Fig. 3. Moreover, since this Research Institute is also characterized for acting according to its own interests (Self-interest), it is expected that it often does not be as responsive (Responsiveness) as required. Picking up the results presented in Table 2 a bar chart can be drawn (see Fig. 4) to visually illustrate the collaborative innovation values profile for each partner in the scope of this specific innovation opportunity. This chart evidences that the Research Institute 's collaborative innovation values profile has a negative impact on the collaboration opportunity. Moreover, we can easily notice that Knowledge Sharing is a relevant characteristic that contributes to the sustainability of this collaboration relationship. Responsiveness, Agility and Innovation are also core-values that contribute positively to be aligned with the collaborative innovation values specified for this co-innovation opportunity.

Validation Process

The constructive research method [START_REF] Kasanen | The Constructive Approach in Management Accounting Research[END_REF] was the methodology selected to guide this research process. Following the constructive approach, a concept introduced through previous research can be applied to solve a specific problem, usually through the development of an artifact or a set of artifacts (models, diagrams, frameworks). March and Smith [START_REF] March | Design and natural science research on information technology[END_REF] claim that in this case, "the research contribution lies in the novelty of the artifact and in the persuasiveness of the claims that it is effective. Therefore, in order to validate the subsequent solution, two points have to be demonstrated: (i) that the artifact or set of artifacts proposed solve the domain problem and/or create knowledge about how the problem can be solved; (ii) how the solution proposed is new or better than previous ones. The proposed Value System Management Model shows, to some extent, how it creates knowledge about how the problem can be solved. Moreover, the example presented above shows how the proposed approach solves the domain problem. The consistency of the CVS management model can be claimed, in view of the fact that it applies a set of models and methods previously verified and validated. Additionally, the novelty of the proposed approach can be claimed, because it was a first attempt to apply a Value System Management Model to manage value profiles in order to identify partners that are more adequate to collaborate in innovation process. However, the process of collecting evidences that allow us to claim the general usefulness of the design models and proposed method have to proceed. Thus, the development of a complete case study in the scope of the innovation networks is a future priority step towards that goal.

Conclusions and Future Work

This paper discussed how the implementation of a Core Value Management System can be useful for the establishment and sustainability of partnerships created following the co-innovation paradigm. Departing from a set of previously proposed tools, to specify and analyse Core Value Systems in collaborative environments, it has been described how they can be configured to determine collaborative innovation values profiles; and to assess if a potential partner has a values profile that is aligned with the partnership in terms of the core-values needed to work in such innovation network. This approach has the following advantages: (i) it facilitates the representation of knowledge about the relevant core-values to the partnership in terms of innovation; (ii)it increases the "transparency" about the decision-making processes in the partner selection; (iii) it provides a visual representation of the interaction among partners in terms of core-values, allowing a better communication with the stakeholders.

Despite the work done so far suggests that the artefacts presented have a practical and theoretical relevance, the validation process for its complexity, has not yet been completed. Thus, the implementation of the CVS management model in a co-innovation network will be the next step.

Fig. 1 .

 1 Fig. 1. UML Diagram of the CVS Conceptual Model

Fig. 2 .

 2 Fig. 2. Web-based tool to support CVSs Management

  pe co-innovation <dv 1 ,wv 1 > dv 1 =[Innovation, Knowledge Sharing, Agility, Responsiveness] wv 1 =[high, very high, high, very high].

Fig. 3 .

 3 Fig. 3. Complete Aggregate Map for Research Center

Fig. 4 .

 4 Fig. 4. Innovation Collaborative Values Profiles represented by a bar chart.

Table 1 .

 1 Core-values Alignment Assessment Results

	pe univA <=[innovation,knowledge, reputation,interdisciplinary, quality, knowledgeSharing] ,
	[very_high, very_high, fair, fair, high, high]>
	pe univB <=<=[innovation,knowledge,	reputation,	interdisciplinary,	reliability,
	knowledgeSharing] , [very_high, very_high, fair, high, high, high]>
	pe researchInstitute <=[Innovation, Uniqueness, Self-Interest, Interdisciplinary ], [high, very_high
	,fair, high] >
	pe SMEnetwork <=[Profit, FinancialStability, Responsiveness, Agility,], [very_high, very_high,
	very_high,fair] >
		Shared Values	Positive	Negative
		Level	Impact Level	Impact Level
	UnivA	Moderate	High		None
	UnivB	Moderate	Moderate	None

Table 2 .

 2 Collaborative Innovation Values Profile

			Shared Values	Positive Impact	Negative Impact	Innovation Collaborative profile
	Univ	A	(innovation,high), (knowledgeSharing,very_high)	(innovation,strong), (flexibility,strong)		(innovation,very_high), (knowledgeSharing,very_high) (flexibility, high)
	Univ	B	(innovation,high), (knowledgeSharing,very_high)	(knowledgeSharing,moderate)		(innovation,high), (knowledgeSharing,very_high)
	Research	Institute	(innovation,high)		(uniqueness,high) (self -interest, moderate)	(innovation,high), (uniqueness, negative-high) (self -interest, moderate)
	SME	Network	(agility,high), (responsiveness,very_high)	(responsiveness,moderate)		(agility,high), (responsiveness,very_high)

Acknowledgements: This work was supported in part by the Portuguese "Fundação para a Ciência e a Tecnologia" (Portuguese Foundation for Science and Technology) through a PhD. scholarship.


Asal Kiazadeh

Paulo R Rocha

Qian Chen

Henrique L Gomes

Resistive Random Access Memories (RRAMs) based on Metal Nanoparticles

Keywords: Nanoparticles, resistive switching, non-volatile memory

It is demonstrated that planar structures based on silver nanoparticles hosted in a polymer matrix show reliable and reproducible switching properties attractive for nonvolatile memory applications. These systems can be programmed between a low conductance (off-state) and high conductance (on-state) with an on/off ratio of 3 orders of magnitude, large retention times and good cycle endurance. The planar structure design offers a series of advantages discussed in this contribution, which make it an ideal tool to elucidate the resistive switching phenomena.

Introduction

Non-volatile memories (NVMs) have become a major technology in the storing of digital information. Flash memory is currently the main stream of the non-volatile memory technology and can be found everywhere in our daily life particularly in portable devices. The absence of mechanical parts, lighter weight and lower power dissipation makes flash NVMs ideal for these applications. In flash memories the information is stored in the form of charge contained in a so-called floating gate (FG) completely surrounded by a dielectric (hence the name and located between the channel region and the conventional, externally accessible, gate of a field effect device (FET)). The amount of charge stored on the FG layer can be easily sensed since it is directly proportional to the threshold voltage of the FET. Flash retention relies on charge-storing on a floating gate, and this lays a challenge for the scalingdown. For instance, less than 100 electrons will be stored in 32 nm node, the information will be easily lost due to the leakage through the thin dielectric. Furthermore, as CMOS scaling proceeds, there is an increasing need to simplify and unify different technologies. In fact, to improve system performance, circuit designers often combine several memory types, adding complexity and cost. The unification of these different technologies would allow further scaling and the decrease of the system cost. Many of the memory caches in the hierarchy of today's computer architecture could be eliminated, reducing cost and complexity. Ideally, the ultimate universal memory aims to replace conventional embedded and stand-alone memories. Alternative routes to traditional memories are thus under intense investigation, with new NVM concepts and storage principles being investigated that may overcome the intrinsic limitation of flash and allow unification of existing memories. A variety of next generation NVMs has been proposed, from which Resistive Random Access Memory (RRAMs) are the latest. RRAMs are being intensively investigated by companies and universities worldwide. The main advantages offered by the technology are higher packing density, faster switching speed and longer storage life. The appeal of RRAM is that each element is a twoterminal device. Switching between high and low resistance is achieved by means of an appropriate electrical pulse, and the read-out process consists of applying a (lower) voltage to probe the state of the resistance. This type of element can be incorporated into cross-point arrays. Resistive type memories are usually metalinsulator-metal (MIM) structures which show non-volatile electrically induced resistance variations of up to nine orders of magnitude. Insulating materials can be as diversified as CuO, CoO, ZnO, NiO, TiO 2 , MgO, Al 2 O 3 , SiO 2 , perovskites, among others [START_REF] Hickmott | Low-Frequency Negative Resistance in Thin Anodic Oxide Films[END_REF][START_REF] Hickmott | Electron Emission, Electroluminescence, and Voltage-Controlled Negative Resistance in Al-AlO2-Au Diodes[END_REF][START_REF] Barriac | Study of the electrical properties of Al-Al2O3-metal structures[END_REF][START_REF] Simmons | New Conduction and Reversible Memory Phenomena in Thin Insulating Films[END_REF][START_REF] Sutherland | Theory for Negative Resistance and Memory Effects in Thin Insulating Films and Its Application to Au-ZnS-Au Devices[END_REF][START_REF] Ansari | Memory Switching in Thermally Grown Titanium-Oxide Films[END_REF]. Thin films incorporating metallic nanoparticles (NPs) also show reliable and reproducible switching properties. Nanoparticles can be capped into polymeric materials and stable solutions are readily available [START_REF] Ma | Nonvolatile electrical bistability of organic/metal-nanocluster/organic system[END_REF][START_REF] Paul | Langmuir-Blodgett film deposition of metallic nanoparticles and their application to electronic memory structures[END_REF][START_REF] Silva | Resistive switching in nanostructured thin films[END_REF]. Thin films hosting a well-defined distribution of nanoparticles are easily fabricated by spincoating, printing, or dip-coating techniques offering the prospect of low fabrication cost, mechanical flexibility and lightweight.

Technological innovation for sustainability

Together with development of the microelectronic industry, the research on low power, low cost, and high density memory devices is necessary for the digital systems, especially for the portable systems. For instance, the absence of mechanical parts, lighter weight and lower power dissipation makes flash non-volatile memory ideal for these applications. However, flash retention relies on charge-storing on a floating gate, and this lays a challenge for the scaling-down. In this work we demonstrate a memory device, which makes use of thin polymer film hosting a matrix of silver nanoparticles. With on/off ratio as high as 10 3 , a large retention time and good cycle endurance, the nanoparticles based device is a serious candidate to replace currently available non-volatile memories, and is able to improve all the relevant components as a reliable memory device.

Planar structures have a significant lower intrinsic capacitance than sandwichtype structures commonly reported; therefore, they should have a faster dynamic response. In addition, these co-planar structures have the active layer directly exposed and can be probed by a number of surface analytical techniques to identify and characterize topographical, morphological changes that occur in the devices upon resistive switching.

System Description

The colloidal solution of PolyVinylPyrolidone(PVP) capped-Silver nanoparticles was deposited on top of preformed gold microelectrode arrays fabricated on thermal oxidized silicon wafers. The interdigitated gold microelectrode arrays were separated apart 10 µm and 10.000 µm long. The samples were dried at room temperature for several hours for removal of the solvent. Prior to electrical measurements the samples were also pumped in vaccum to remove further any residual solvent. Electrical measurements were carried out using a Keithley 487 picoammeter/voltage source in dark conditions, high vacuum. Figure 1 shows the device test structure used to measure the electrical properties of the system comprised of nanocrystals in a semi insulating or insulating host matrix. A thin film is formed between the two gold electrodes on top of the insulating silicon dioxide surface by drop casting or by spin coating. During all the measurement the conductive silicon substrate is kept grounded to prevent charging of the SiO 2 layer.

Current-Voltage characteristics

Before the devices show resistive switching behavior, they have to undergo a forming process that is induced by applying a high bias voltage. In practice, forming voltages are typically ~50V. After forming the device exhibits the bistable currentvoltage characteristics represented in Fig. 2. A low conductance state named offstate and a high conductance state designated as on-state. The on-state has a symmetric negative differentially resistance (NDR) region located between 25 and 30 V. The memory can be switched between off and on-state by applying voltage pulses with amplitudes corresponding to the top and bottom of the NDR region, in Fig. 2 about 20 V and 40 V, respectively. The device can be read out non-destructively using voltages < 10V. The programming voltages are larger than those observed in conventional sandwich capacitor-like devices because the distance between electrodes is also significant higher.

The memory characteristics

The nanoparticle based memory is nonvolatile, retaining the programmed conductance state for at least a week without any applied bias as long as they are stored in vacuum or in inert atmosphere. Fig. 3 (a) shows the retention time for both states using a read voltage of 3 V.

Once the device is in a given memory state, it can be reliably read many times without degradation. Shown in Fig. 3

Conclusion

Metal nanoparticles embedded in a polymer matrix exhibit the ability to switch between different nonvolatile conductance states. Programming of the memory states is done using voltage pulses. The memory device concept was demonstrated using a lateral structure with a large gap between electrodes (10µm). This structure needs substantially high programming voltages. However, it is feasible to bring the device dimensions to a nanometer scale and bring the magnitude of the operating voltages to values compatible with CMOS technology.

Since the basic active layer is a soluble polymer, large area arrays of memories can easily be fabricated into flexible substrates, thus opening the prospect for lowcost production of memory arrays for instance for radio-identification tags.

Fig 1 .

 1 Fig 1. Planar device structure with two gold electrodes. The device dimensions are W=10.000µm and L=10µm.

Fig. 2 .

 2 Fig. 2. Current-voltage characteristics showing the high conductance on-state and low conductance off-state.

  (b) is a segment of the current response to write-read-erase-read voltage waveforms. The write voltage (W) is 35 V and the erase (E ) is 50 V. For both states the read voltage (R) is 3V.

Fig. 3 .

 3 Fig. 3. (a) retention time of two memory states has been obtained at 3 volt. (b) typical current response to the write-read-rewrite-read voltage cycles. The write voltage (W) is 35 V and the erase (E) is 50 V. For both states the read voltage (R) is 3V

Acknowledgement. We gratefully acknowledge the financial support received from the Dutch Polymer Institute (DPI), project n.º 703, from Fundação para Ciência e Tecnologia (FCT) through the research Unit, Center of Electronics Optoelectronics and Telecommunications (CEOT), REEQ/601/EEI/2005 and the POCI 2010, FEDER and the organic chemistry laboratories in Algarve University.


Christopher Durugbo
email: c.durugbo@cranfield.ac.uk

Ashutosh Tiwari
email: a.tiwari@cranfield.ac.uk

Jeffrey R Alcock
email: j.r.alcock@cranfield.ac.uk

Modelling Information Flow for Collaboration

Keywords: information flow, complex networks, conceptual modelling, collaboration, delivery phase, microsystems technology

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

Introduction

Recently, the study of social networks has offered a useful avenue for the analysis of information flow with a view to improving organisational factors and requirements such as capacity, productivity, efficiency, flexibility, and adaptability [START_REF] Boccaletti | Complex networks: Structure and dynamics[END_REF][START_REF] Schultz-Jones | Examining information behavior through social networks: An interdisciplinary review[END_REF]. Consequently, models of information flow of social networks have been proposed by analysts to explore minor and major roles of individuals in an organisation [START_REF] White | Connecting organizations: Developing the idea of network learning in interorganizational settings[END_REF].

This research is motivated by the need to enhance collaboration during delivery phases for production through a model of information flow. Collaboration is an important organisational requirement that means working together in group(s) to achieve a common task or goal through teamwork, decision-making and coordination [START_REF] Durugbo | Modelling Collaboration using Complex Networks[END_REF]. Enhancing collaboration during delivery offers opportunities for improving the efficiency, quality and sharing of information, leading to sustainable operations [START_REF] Durugbo | Modelling Collaboration using Complex Networks[END_REF]5].

The aim of this paper is to model complex networks for collaboration during delivery. In order to accomplish this, a case study of complex networks for the delivery of MST, will be undertaken to analyse information flow. §2 and §3 present the contribution of the paper to sustainability and the research background respectively, whereas §4 introduces a model of information flow used in §5 for a case study within an MST firm.

Contribution to sustainability

This paper seeks to contribute to sustainable operations for organisations through a case study that makes use of a conceptual model of information flow to study the relationship between collaboration and delivery information flow. Sustainability is used here, from an economic perspective, to mean maintaining profitable operations.

Research background

In [START_REF] Durugbo | Modelling Collaboration using Complex Networks[END_REF], the state-of-the-art in the use of social network analysis (SNA) for modelling collaboration was analysed and the authors concluded that current models lacked visualisations for characterising formal relationships that symbolise collaboration roles and responsibilities. This is because SNA only considers individuals or groups of individuals as entities within social networks in terms of relationships, social roles and social structure [5,[START_REF] Valente | Collaboration and competition in a children's health initiative coalition: A network analysis[END_REF]. However, during collaborations, people/ teams are interconnected and tasks/processes are linked [START_REF] Durugbo | Modelling Collaboration using Complex Networks[END_REF].

Interconnections for social networks have been the subject of research that have been used to model scale-free, hierarchical and random [START_REF] Barabasi | Network Biology: Understanding the Cell's Functional Organization[END_REF] properties and networks of organisations and communities. Social networks are also characterised by quantities that distinguish between structural interconnectedness and prominence of vertices. These quantities include [START_REF] Durugbo | Modelling Collaboration using Complex Networks[END_REF]: 1. Distance -sum of links along the shortest path between vertices, 2. Reachability -establishes if vertices are linked directly or indirectly, 3. Density -compares number of actual links to possible links between vertices, 4. Degree centrality -number of vertices directly connected to a vertex, 5. Closeness centrality -inverse of the distance between a vertex and vertices in a network, and 6. Betweenness centrality -amount of times a vertex connects vertices to each other.

The need to include and analyse networks made up of tasks is evident in current studies by authors such as Batallas and Yassine [START_REF] Batallas | Information leaders in product development organizational networks: Social network analysis of the design structure matrix[END_REF], in which the analysis of social networks is complemented with design structure matrices for analysing tasks and Collins et al. [START_REF] Collins | Analyzing Product Development Task Networks to Examine Organizational Change[END_REF] that examined task networks for product development. These studies have mainly concentrated on isolating and analysing social and task networks separately or making use of one technique to analyse the other. An inspection of these techniques suggests that potentially some links and flows may be omitted. For instance, a human operator working as part of a team may access or transfer some information necessary for collaboration (such as number of products to be manufactured) with a manufacturing process. This interaction may not require the participation of a team member or may be accessed by another team member through the process without a direct link to the original source of the information i.e. the first human participant.

A model of information flow for organisational collaboration

The focus of this paper is to make use of a model of information flow, shown in Fig. 1, to analyse collaborative delivery in an MST company.

As described in [START_REF] Durugbo | Modelling Collaboration using Complex Networks[END_REF], mathematically, a collaborating organisation, can be modelled as a connected, partitioned, non-overlapping hypergraph G = (V, E) containing a graph for characterising the collaborative social network of individuals/groups G s = (V s , E s ) and a directed graph for characterising the collaborative activity network of processes/tasks G p = (V p , E p ). V s represents social vertices of collaborating individuals, teams or organisations, and V p represents activity vertices for processes that are required to achieve a common goal that could not be achieved by the independently collaborating individuals. E s and E p correspond to edges between teams (or individuals) and processes. In the proposed model, processes become part of a collaboration based on the set of interface edges T showing connections between human participants and processes i.e. T associates V s with V p . Consequently G is defined by Using the proposed information structure, the information behaviour for organisations can be characterised using key SNA measures of clustering coefficient, closeness and degree centrality. These quantities were selected because they reflect interconnectedness within groups, individual connections for relationships and activity of individuals respectively [5,[START_REF] Valente | Collaboration and competition in a children's health initiative coalition: A network analysis[END_REF].

V = V s ∪ V p and V s ∩ V p = Ø. Similarly, E = E s ∪ E p ∪ T and E s ∩ E p ∩ T = Ø.
The degree centrality (Dc i ) is a ratio of number of directly connected vertices to the number of possible vertices in a network and can be computed as:

[ ]

1 deg - = N Dc i i (1)
Where, N is the number of vertices in the network and [deg] i is the number of vertices directly connected to i.

The clustering coefficient assesses the density between vertices and represents the tendency for vertices to cluster together. If a vertex i, connects to b i neighbours, and the number of possible edges between the vertices is given as b i (b i -1)/2, then the clustering coefficient (Cc i ) of i can be computed as:

( )

1 2 - = i i i i b b n Cc (2)
Where n i is the number of edges between b i neighbours.

The closeness between vertices defines the order with which one vertex collaborates with another vertex. It is computed as the inverse of the geodesic distance (d ij ) between a pair of vertices i and j. d ij is the number of edges along the shortest path between i and j. Closeness (c ij ) can be calculated as:

∑ ∈ ≠ = N j i ij ij d c 1 (3)
For instance, if a vertex i connects directly to another vertex j, then the closeness of i to j is given as 1, if collaboration is established as a result of connecting to a third vertex k acting as a hub i.e. dictator collaboration [START_REF] Durugbo | Modelling Collaboration using Complex Networks[END_REF], then i has a closeness of 0.5 to j.

Case Study

Company B is an MST company based in the United Kingdom with a targeted global market. It operates with 14 staff for the delivery of microfluidic and microoptical based products and services as business-to-business solutions for customers that are mainly original equipment manufacturers or an academic institution. Products delivered by Company B include microlens arrays for flat panel displays, and lab-ona-chip microfluidic devices for industrial automation, cell analysis and drug delivery.

In this section, the research method and findings of the case study to analyse delivery information flow in Company B is described. The implications of the findings for sustainable operations are also identified.

Research Methodology

An analytical research methodology [START_REF] Kumar | Research methodology[END_REF] was adopted for the case study in two steps.

Firstly, the information structure of Company B was analysed through an initial semi-structured telephone interview with the customer support manager (CSM) at Company B that lasted 25 minutes. This interviewee was provided by the company director at Company B following initial telephone conversations to request permission to carry out the study. The director designated the CSM as personnel responsible for managing the flow of information during MST delivery and the main question posed to the CSM to initiate the semi-structured interviews was: 'What are the processes and information flow for the delivery phase in your company?, Secondly, using the data provided by the CSM, face-to-face interviews were then conducted on-site with 7 other available company personnel involved in the delivery process to analyse information flow using the proposed model. In other to populate the model, interviewees were asked to validate the description provided by the CSM. Interviewees were also asked to identify processes and other personnel that they were connected to during delivery for decision making, teamwork, and coordination.

Research Findings

The interviews with personnel at Company B revealed that decision-making within G s is a directed graph that involves the entire social vertices within V s . Incident edges are mainly outwards from the subset of V s containing social vertices of the management group (Ba to Bd) as shown in Fig 2a. Teamwork for the social network for Company B is an undirected graph with clusters formed among groups of social vertices for V s whereas coordination within Company B is also an undirected graph involving the entire network. An aggregation of the social networks in Fig. 2a and the 19 (.01-.19) processes described by the CSM (that was validated by the participants of the face-to-face interviews) resulted in the information structure for Company B, as shown in Fig. 2b. Activity vertices .01 (request product), .10 (request clarification), .15 (confirm receipt) and .17 (request service) are carried out by the customer whereas .13 (dispatch product) is the responsibility of the courier provider. For collaboration within Company A, the 14 available staff i.e. the social vertices Aa-Ea, are connected to the remaining 14 processes through 57 internal interface edges.

Management processes, associated with vertices Aa and Ba-Bd, form a subset of V p consisting of activity vertices .02 (acknowledge request), .09 (deliver drawings), .14 (confirm dispatch) and .16 (request feedback). Similarly, engineering and science processes, associated with social vertices Ca-Ce and Da-Dc, form a subset of V p involving activity vertices .04 (agree materials), .05 (agree consumables), .06 (order materials), .07 (order consumables), .08 (produce drawings), .11 (clarify design), .12 (prepare product), .18 (provide service) and .19 (modify product). The accounting process associated with Ea is activity vertex .03 (update account).

While the maximum number of edges in a fully connected social network (G s ) of 14 social vertices can be computed as G s (G s -1)/2 i.e. 91, the maximum number of interface edges to the 14 activity vertices within G p (.02-.09, .11, .12, .14, .16, .18 and .19) on which collaboration is based, can be calculated as G s × G p i.e. 196.

As shown in Fig 2b, vertex Aa connects to 13 social vertices and 4 activity vertices. Consequently the values of Dc i for vertex Aa within the G s and G can be computed from eqn. (1) as 13/(14 -1) = 1.000 and (13+4)/(14+(14 -1)) = 0.630. Since, the social vertices directly connected to Aa form 54 edges with each other and 57 interface edges with directly connected activity vertices, the value of Cc i for Aa within the social G s and G can be calculated from eqn. (2) as 54/91 = 0.593 and (54+57)/(91+196) = 0.387 respectively. Similarly, the values of c ij within G s and G can be determined from eqn. (3) as 1/(13×1) = 0.077 and 1/((13×1)+((4×1) +((19 -4)×2))) = 0.021. Values of Dc i , Cc i and c ij for the social vertices in Company B have been computed using a similar approach and are shown in Table 1. indicate possible weak individual connections for relationships across the organisation. Nonetheless, the average value of Cc i is higher when analysed for social vertices within working groups (such as activity vertices Da-Dc), indicating stronger connections for teams as opposed to the entire organisation. This finding correlates with existing studies in which it is suggested that small and medium enterprises (SMEs) within high-tech firms, such as Company B, are effective at working together for innovation [START_REF] Trumbach | Technology mining for small firms: Knowledge prospecting for competitive advantage[END_REF].

Implications for sustainable operations

Two important lessons for sustainable operations were learnt from the case study involving considerations for dichotomies based on small-scale R&D (research and development) vs. large-scale manufacturing, and hierarchical vs. flat structures.

Firstly, although Company B applies a small-volume-large-variety production business model, on-going efforts to expand operations for large scale production poses major challenges for coordination, decision-making and teamwork. Further analysis following discussions with the company director of Company B revealed that this challenge is a major cause for disagreements and conflicts that has currently severed ties and friendships within the company, impacting on collaboration levels.

Secondly, further discussions with personnel also revealed a split between management staff wanting fewer organisational layers to ease the flow of information and engineering personnel favouring hierarchies for structure in processes. However, non-management personnel (such as vertex Da) have been able establish links across the divide through negotiation and interpersonal contact. In contrast, some experienced management personnel (such as Bc and Bd) have not been able to effectively collaborate in Company B, a situation which according to the company director is due to the split between R&D and manufacturing, and poor interpersonal skills. These lessons reinforce the importance of trade-offs for MST firms [START_REF] Durugbo | Survey of media forms and information flow models in microsystems companies[END_REF] that offer avenues for maintaining collaboration as well as business driven and simplified information flow.

Conclusions

In this paper, a model of information flow for collaboration is proposed as a combination of social networks involving decision-making, coordination and teamwork of human entities and activity networks containing non-human entities such as production processes, technologies and systems. The model also applies measures of degree centrality, clustering coefficient and closeness from social network analysis (SNA) to assess the level of collaboration within organisations. Useful insights from a case study of delivery within a microsystem technology (MST) firm, based on the proposed model, suggested that high-tech small and medium enterprises can be effective at collaborating for delivery. For the case study, social vertices (i.e. participants in collaborations) were assessed using the SNA measures from: a sociological perspective for the social network and an organisational perspective for the entire (social and activity) network. Findings from the study also suggested that effective collaborative delivery requires trade-offs for strategising capabilities for operations and for managing organisational layers that enable expansion.

Fig. 1 :

 1 Fig.1: A model of information flow for organisational collaboration[START_REF] Durugbo | Modelling Collaboration using Complex Networks[END_REF]

Fig. 2

 2 Fig. 2 (a) Social networks for decision-making, coordination and teamwork in Company B, and (b) Information structure for Company B

Table 1 .

 1 Social network measures for social vertices within the social network (G s ) and entire network (G) of Company B (degree centrality -Dc i , clustering coefficient -Cc i, closenessc ij ).

	Social vertices	Dc i	Within G s Cc i,	c ij	Dc i	Within G Cc i,	c ij
	Aa	1.000	0.593	0.077	0.630	0.387	0.021
	Ba	1.000	0.593	0.077	0.667	0.387	0.022
	Bb	1.000	0.593	0.077	0.667	0.387	0.022
	Bc	0.462	0.231	0.050	0.222	0.150	0.017
	Bd	0.538	0.286	0.053	0.593	0.220	0.020
	Ca	0.538	0.275	0.053	0.519	0.226	0.020
	Cb	0.385	0.165	0.048	0.407	0.160	0.019
	Cc	0.385	0.165	0.048	0.185	0.139	0.017
	Cd	0.462	0.231	0.050	0.481	0.185	0.019
	Ce	0.462	0.231	0.050	0.407	0.209	0.019
	Da	0.923	0.582	0.071	0.593	0.380	0.020
	Db	0.462	0.231	0.050	0.370	0.150	0.017
	Dc	0.462	0.231	0.050	0.222	0.150	0.017
	Ea	0.231	0.033	0.043	0.148	0.073	0.015
	Overall average	0.593	0.317	0.057	0.437	0.229	0.019
	With an overall average Dc i value of 0.593 (59.3%) and 0.437 (43.7%) for G s and
	G from

Table 1 ,

 1 this study suggests a significant level of interconnectedness within Company B. Similarly, the values of c ij (0.057 and 0.019 for G s and G) suggest high activity of personnel within Company B. This is because if all Company B's personnel were fully active, i.e. each vertex can connect directly to other vertices, then the average values of c ij for Company B would be 0.080 and 0.037 for G s and G respectively. In Company B's current state, this represents 74.1% and 51.3% of potential activity within G s and G respectively. However, low values of Cc i (0.317 and 0.229 for G s and G)

Acknowledgments. The authors would like to extend their sincere thanks to the Engineering and Physical Sciences Research Council (EPSRC), for its support via the Cranfield Innovative Manufacturing Research Centre (CIMRC), towards the work carried out in the preparation of this paper.


José Augusto Prado

Carlos Simplício
email: carlos.simplicio@ipleiria.pt

Jorge Dias

Robot Emotional State through Bayesian Visuo-Auditory Perception

Keywords: Bayesian Approach, Auditory Perception, Robot Emotional State, Vocalization

In this paper we focus on auditory analysis as the sensory stimulus, and on vocalization synthesis as the output signal. Our scenario is to have one robot interacting with one human through vocalization channel. Notice that vocalization is far beyond speech; while speech analysis would give us what was said, vocalization analysis gives us how was said. A social robot shall be able to perform actions in different manners according to its emotional state. Thus we propose a novel Bayesian approach to determine the emotional state the robot shall assume according to how the interlocutor is talking to it. Results shows that the classification happens as expected converging to the correct decision after two iterations.

Introduction

In the context of human robot interaction, a core problem is how to reduce the estrangement between humans and machines. In order to do this, recently researchers are investigating how to endow the robots an emotional feedback. There has never been any doubt about the importance of emotions in human behavior, especially in human relationships. The past decade, however, has seen a great deal of progress in developing computational theories of emotion that can be applied to building robots and avatars that interact emotionally with humans. According to the main stream of such theories [1], emotions are much intertwined with other cognitive processing, both as antecedents (emotions affect cognition) and consequences (cognition affects emotions). In our scenario, a pre-defined story board exists, which the human and the robot shall follow, though removing the importance of what is said and focusing the experiments on the detection of emotion. In the simplest case, robot will mimic the detected emotion.

Contribution to Sustainability

Schroder et. al. [START_REF] Schroder | The semaine api: Towards a standards-based framework for building emotion oriented systems[END_REF] presented the SEMAINE API as a framework for enabling the creation of simple or complex emotion oriented systems. Their framework is rooted in the understanding that the use of standard formats is beneficial for interoperability and reuse of components. They show how system integration and reuse of components can work in practice. An implementation of a dialogue system was done using a 2D displayed avatar and speech interface. More work is needed in order to make the SEMAINE API fully suitable for a broad range of applications in the area of emotion-aware systems [START_REF] Schroder | The semaine api: Towards a standards-based framework for building emotion oriented systems[END_REF]. Classifying emotions in human dialogs was studied by Min [3] presenting a comparison between various acoustic feature sets and classification algorithms for classifying spoken utterances based on the emotional state of the speaker. Later, Wang [START_REF] Wang | Recognizing human emotion from audiovisual information[END_REF] presented an emotion recognition system to classify human emotional state from audiovisual signals. The strategy was to extract prosodic, mel-frequency Cepstral coefficient, and formant frequency features to represent the audio characteristics of the emotional speech. A face detection scheme based on HSV color model was used to detect the face from the background. The facial expressions were represented by Gabor wavelet features. This proposed emotional recognition system was tested and had an overall recognition accuracy of 82.14% of true positives. Recently, Cowie [START_REF] Cowie | Recognition of emotional states in natural human-computer interaction[END_REF] it was described a multi-cue, dynamic approach to detect emotion in video sequences. Recognition was performed via a recurrent neural network.

Our approach presents a novel probabilistic model for emotion classification based on vocalization analysis and Bayesian Networks applied for Human Robot Interaction. Our prototype robot can be seen in figure 1. Furthermore, we propose a model for integration of two modalities (visual and aural), more specifically facial expression analysis following Ekman [START_REF] Ekman | What the face reveals: basic and applied studies of spontaneous expression using the facial action coding system (FACS)[END_REF] and vocalization analysis.

Emotional States

Spinozza [START_REF] Spinoza | [END_REF], during the seventeenth century, proposed a definition of how human emotions behave. His work was recently continued and extended by Damasio [START_REF] Damasio | Looking for Spinoza[END_REF] [START_REF] Damasio | The feeling of what happens[END_REF] who proposed an approach with the joint behavior of four groups of emotional states: three of them are related to the lost of some capability of communication. A fourth group, associated to success, was also considered. Each group contains the social emotion and the Emotional Competent Stimulus (ECS) for that emotion. Damasio did not define ECS for the neutral state. Here we propose the addition of a fifth group where the neutral state is. The four groups of emotional states proposed by Damasio [START_REF] Damasio | The feeling of what happens[END_REF], and plus the neutral state added by us, can be summarized as follow: fear, anger, sad, happy and neutral. According to Damasio [START_REF] Damasio | The feeling of what happens[END_REF], the emotional state can be influenced by what is happening with the individual's, and also to interlocutor emotional state. Taking this into account, our system is composed by analysis and synthesis (see figure 2). In the analysis part, we are determining what are the vocal expressions produced by the human. Later in the synthesis part, the emotional state is established and the reaction is synthesized. A combination with an input from human's emotional state, which is given by facial expression analysis following Ekman [START_REF] Ekman | What the face reveals: basic and applied studies of spontaneous expression using the facial action coding system (FACS)[END_REF], is also proposed on the synthesis part.

Bayesian Modeling

The Bayesian approach is characterized by assigning probabilities to characterize the degree of belief associated with the state of the world. Bayesian approach defines how new information should be combined with prior beliefs and how information from several modalities shall be integrated. Bayesian decision theory defines how our beliefs should be combined with our objectives to make optimal decisions. Fig. 2. Analysis and synthesis' system schema.

Figure 2 shows the system implementation modules. Auditory perception feature extraction and the Bayesian model are described on section 4.1. Synthesis will be briefly presented in section 4.2.

Human Vocalization Analysis

In our model of auditory perception, the vocalization analysis classifies a vocal expression. The robot needs to be capable of classifying among the possible vocal expressions, which are in the same scope as the facial expressions as defined by Ekman [START_REF] Ekman | What the face reveals: basic and applied studies of spontaneous expression using the facial action coding system (FACS)[END_REF]: {anger, fear, happy, sad, neutral}.

Vocalization Analysis

All waves are effectively combinations of sinusoids. The Fourier transform takes a waveform and turns it into a function describing which sinusoids are present in the waveform. So, as one can see in figure 3, a digitalized sound wave comes with positive and negative values. However, it is only in the frequency of oscillation of the signal that sound can exist. Obviously, a single sample cannot represent any oscillation. it has 49679 samples and 3.1049 seconds of duration. At right a FFT of the interval from 1 to 2 seconds; after applying the correlation method presented by Sondhi [START_REF] Sondhi | New methods of pitch extraction[END_REF] it is possible to get the perceived frequency.

In order to classify emotions from a waveform, first it is necessary to extract features from it. Here we define which features we are going to extract and also the Bayesian network to structure the relationship among them (figure 4).

There are several methods to extract pitch [START_REF] Sondhi | New methods of pitch extraction[END_REF][14] [START_REF] Cook | An automatic pitch detection and MIDI control system for brass instruments[END_REF][16]: zero-crossing, autocorrelation function, cepstrum, average magnitude differential function, comb transformation, FIR filter method of periodic prediction. Lopes [START_REF] Lopes | VTLN through frequency warping based on pitch[END_REF] [12] [START_REF] Lopes | On the use of pitch to perform speaker normalization[END_REF] extensively studied vocal tract's length normalization using pitch's features for it.

Auditory Perception Bayesian network

To classify the vocal expressions performed by the human, a Bayesian network was developed. The structure of this network of two levels is illustrated in figure 4. A vocal expression will be classified after a sentence finish. In other words, for the Bayesian network, the time 1 is just after sentence 1 is completed, time 2 is just after sentence 2 is completed; and so one. This is independent of each sentence's (real time) duration. Now it is implemented over Matlab and off line, so we don't need a state switching since the sentences are recorded separated. In future, to determine the state switching, we expect to use a silence detector as presented by Hoelper [START_REF] Hoelper | Voiced/unvoiced/silence classification for offline speech coding[END_REF]. If the silence period is bigger than a threshold (3 seconds), this event may trigger the state switching. In the Bayesian network's first level there is only one node. The global classification result obtained is provided by the belief variable associated with this node: V_E∈{angry, fear, happy, sad, neutral}; where the variable name stands from Vocal Expression. Considering the structure of the Bayesian network, the variables in the second level have as parent this one in the first level: V_E.

In the second level there are four belief variables,

• PT∈{short, normal, long} is variable which a belief is related with Pitch. Pitch represents the perceived fundamental frequency of a sound. We are using the pitch extraction by autocorrelation method proposed by Sondhi [START_REF] Sondhi | New methods of pitch extraction[END_REF]. The voice pitch changes significantly along a sentence and an important part of our voices are un-pitched, however, since the conversation follows a pre-defined story board, the mean pitch of the sentence will help to distinguish the emotional state that was there when this very sentence was spoken. • SD∈{short, normal, long} is variable which a belief is related with Sentence Duration. Since we know the sampling frequency (sfreq) of the acquired sound, and we also know the beginning and the end of each sentence, consequently the number of samples (nsam) then it is trivial to determine the duration in seconds by . This variable contributes to the classification. By example, when a person speaks the same sentence with a happy emotion it usually speaks faster than with a sad emotion. For some emotional states the duration might be exactly the same, but then the other variables will contribute for the disambiguation.

• VL∈{low, medium, high} is a belief variable which stands for Volume Level. This variable is actually the energy y of the signal, which for a continuous-time signal x(t) is given by . • SR∈{zero, one, two, three_or_more} is the belief variable which stands for Sentence Repetition. It is associated with the number of sentences repetitions that the interlocutor may perform. The value of this is given by the comparison of the previous three variables along four previous times.

The following equations illustrate the joint distribution associated to the Bayesian Vocal Expressions Classifier:

.

(1)

The last equality can be done only if it is assumed that belief variables PT, SD, VL and SR are independent.

From the joint distribution, the posterior can be obtained by the application of the Bayes' Formula as follow:

(2)

Robot Vocalization Synthesis

According to figure 2, the Decision Process receives as input H_ES (the Human Emotional State), which is given by the external facial expression classifier and V_E (the inferred Vocal Expression). It will take a decision according to these inputs and to the MEMORY contents. It is assumed that the robot will initially internalize the vocal expression of the person, thus V_E implies on a robot pre-emotional state (R_pES). The Decision Process will then combines R_pES with the H_ES in order to determine R_ES (the final emotional state that the robot will assumes). This fusion is proposed in order to determine the robotic emotional state in similar way of that established by Damasio [START_REF] Damasio | Looking for Spinoza[END_REF] for human beings. As a consequence of the Bayesian framework, the prior knowledge will determine the balance of the fusion. This brings up to which side the decision will fall: in one side the robot is more confident in its own emotional state (from vocalization analysis); in another extreme the robot is less confident and uses the human emotional state (from facial expression analysis).

Results

Results of learned likelihoods for Auditory Perception. After teaching the system, by pointing which is the correct Vocal Expression for a given input, is obtained a histogram table exactly as shown at Table 1. This histogram is the likelihood knowledge for the Bayesian algorithm to perform the inferences later: the joint distribution (see eq. 1) contains all the information needed.

Results of Bayesian Network for Auditory Perception.

The robot is able to infer over the likelihoods (see eq. 2) when interacting to the user. The expected results for the ANALYSIS part are correct classifications of vocal expressions according to what is expected. Convergence is also expected to appear among the time, since both are Dynamic Bayesian Networks. Figure 6 shows results of the Bayesian inference during five iterations with the following constant evidences:

Pitch=long, SentenceDuration=short, VolumeLevel=low, SentenceRepetition=zero.

Conclusions and Future Work

This work presented a novel approach to determine robot emotional state through vocal expressions, according to philosophic references on how humans do it for themselves. The results show that correct classifications are done: the inferred emotional state is correct during an interaction between a robot and a human. This approach turns interaction more inclusive and reduces the estrangement between humans and machines. Our approach endows the robot to say the same sentence with different characteristics, according to its emotional state. We just presented one example of an utterance in sad; however, we are preparing a dataset with different sentences uttered in all the five emotional states here considered. The current implementation of our Bayesian network is with limited values and it shows a proof of concept; however, we expect to experiment it with a larger scope of possibilities for each variable.

As the proposed model is simple, it is advantageous in particular contexts; specially multimodal fusion; where a quick (less complex) form of predicting an emotional state is better than a large model of human emotional processing.

Fig. 1 .

 1 Fig. 1. Our prototype robot.

Fig. 3 .

 3 Fig. 3. Sample recorded speech waveform of an utterance, sad. The x axis is the number of samples while the y axis is the amplitude in dB. A sampling frequency of 16000Hz was used;

Fig. 4 .

 4 Fig. 4. Bayesian network Auditory Perception.

Fig. 5 .

 5 Fig. 5. Synthesis Bayesian Network.

Fig. 6 .

 6 Fig. 6. Results for Classification of a Vocal Expressions (Sad) -The convergence happens after the second iteration.

Table . 1

 . . Learning for Analysis of Vocal Expressions.

	V_	PT			SD			VL			SR
	E
		low	med hig	shor	nor	lon	low	med hig	0	1	2	3+
				h	t	m	g			h
	Ang 0.8	0.1	0.10 0.10	0.10	0.80 0.1	0.1	0.80 0.9	0.0	0.0	0.0
			0					0	0		7	1	1	1
	Neu	0.1	0.8	0.10 0.80	0.10	0.10 0.1	0.8	0.10 0.9	0.0	0.0	0.0
			0					0	0		7	1	1	1
	Sad	0.1	0.1	0.80 0.80	0.10	0.10 0.8	0.1	0.10 0.9	0.0	0.0	0.0
			0					0	0		7	1	1	1
	Hap	0.l	0.8	0.10 0.25	0.50	0.25 0.1	0.8	0.10 0.9	0.0	0.0	0.0
			0					0	0		7	1	1	1
	Fear 0.3	0.3	0.33 0.33	0.34	0.33 0.3	0.3	0.34 0.0	0.2	0.3	0.4
		4	3					3	3		1	3	3	3


Eduardo Bock
email: eduardo_bock@yahoo.com.br

Pedro Antunes

Beatriz Uebelhart

Tarcísio Leão

Jeison Fonseca

Diolino André Cavalheiro

Santos Filho

José Roberto Cardoso

Bruno Utiyama

Juliana Leme

Diolino Santos Filho

Cibele Silva

Aron Andrade

Celso Arruda

Design, Manufacturing and Tests of an Implantable Centrifugal Blood Pump

Keywords: Artificial Organs, Blood Pumps, Ventricular Assist Devices

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

Introduction

A novel Implantable Centrifugal Blood Pump has been developed for long term circulatory assistance with a unique impeller design concept [START_REF] Bock | New Centrifugal Blood PumpWith Dual Impeller and Double Pivot Bearing System:Wear Evaluation in Bearing System, Performance Tests, and Preliminary Hemolysis Tests[END_REF]. This feature was called dual impeller because it allies a spiral-shaped cone [START_REF] Andrade | Characteristics of a blood pump combining the centrifugal and axial pump principles[END_REF] with vanes to improve blood flow characteristics around the top inflow area to avoid blood clot due to stagnant flow (Fig. 1).

A series of previous studies demonstrated significant advantages from spiral shaped impeller design, providing axial characteristics to the flow in Left Ventricle Assist Devices [START_REF] Bock | New Centrifugal Blood PumpWith Dual Impeller and Double Pivot Bearing System:Wear Evaluation in Bearing System, Performance Tests, and Preliminary Hemolysis Tests[END_REF]. The axial force component can avoid stagnant flow formation. Therefore, this principle can help to avoid thrombus related with blood stagnation [START_REF] Yamane | A comparative study between flow visualization and computational fluid dynamic analysis for the sun medical centrifugal blood pump[END_REF].

This work presents results from Design, Manufacturing and Tests of an Implantable Centrifugal Blood Pump wear evaluation in double pivot bearing system, hydrodynamic performance tests with mock loop circuit, and preliminary normalized hemolysis tests. The double pivot bearing system has been used and studied in the last decade showing simplicity and reliability [START_REF] Ohara | Baylor Gyro pump: a completely seal-less centrifugal pump aiming for long-term circulatory support[END_REF]. Recent studies evaluated the particle release from a centrifugal pump with double pivot bearing system composed of alumina ceramic (Al2O3) and ultrahigh molecular weight polyethylene (UHMWPE). This pivot bearing system was tested under severe conditions showing very small risk of releasing debris particles to blood [START_REF] Bock | New Centrifugal Blood PumpWith Dual Impeller and Double Pivot Bearing System:Wear Evaluation in Bearing System, Performance Tests, and Preliminary Hemolysis Tests[END_REF][START_REF] Takami | In vitro study to estimate particle release from a centrifugal blood pump[END_REF].

Contribution to Sustainability

The Design Process

The design process was conducted according with current medical, social and financial needs of cardiac patients in Brazil. It is part of a multicenter and international study with objective to offer simple, affordable and reliable devices to developing countries since local health systems, both public and private health care, cannot afford the available technologies. The authors have expectation that this pump will become a promising Technological Innovation for Sustainability in Brazil. Its simplicity is illustrated in (Fig. 2) showing two different options for motors and pump.

Performance tests

Performance tests were conducted with several different prototypes, some of them machined in translucent materials and titanium, other made with Selective Laser Sintering (SLS) in Nylon and ABS polymer (Fig. 3 shows some pictures of prototypes).

In order to verify the viability of different materials, wear tests were made with several pivot bearings. Mainly, two types of defect were found, abrasive wear and surface fatigue. Previous tests with this system were performed with pumps working in mock loop circuits.

In order to study the wear phenomenon in each component of double pivot bearing, an isolated wear station was assembled to repeat this condition. In vitro performance tests were made in order to characterize hydraulic performance curves for the pump.

These tests can provide important information about the pump's capability and function ability. The generated curves can be used as a tool to predict which rotation is necessary to provide specific pressure and flow [START_REF] Takami | Eccentric inlet port of the pivot bearing supported Gyro centrifugal pump[END_REF].

During performance tests, two different types of pump's inlet port were compared, with 45° and 30° of inlet angle. Finally, two isolated normalized tests of hemolysis with human blood were performed producing four values of normalized index of hemolysis (NIH), obtained from variation of plasma free hemoglobin (PFH), measured by a tetramethylbenzidine (TMB) assay method (Catachem, Bridgeport, CT, USA).

Materials and methods

Wear Evaluation in Double Pivot Bearing System. A wear test station was assembled with the purpose of measuring isolated wear rate. It makes it possible to vary the shear stresses in consequence of charge applied to the system. The main idea was to evaluate wear using mass measurements and quantifying the bearing's material debris released in blood during the pump's operation [START_REF] Bock | New Centrifugal Blood PumpWith Dual Impeller and Double Pivot Bearing System:Wear Evaluation in Bearing System, Performance Tests, and Preliminary Hemolysis Tests[END_REF].

Adapting a milling machine, the wear test station was assembled with rotation controller, water lubrication, depth controller, and applied charge measurement system. The wear tests were divided into three steps. In the first step, all bearings were weighted in a precision scale with divisions of 0.1 mg. After that, each pair of male and female bearing was tested. Two types of pairs were tested, ceramic-polymeric pairs and ceramic-ceramic pairs. After the tests, the pairs were weighted again to measure the wear loss in mass.

The polymers chosen were nylon, UHMWPE, and Teflon (polytetrafluorethylene). The ceramics chosen were zirconium dioxide (ZrO2), silicon nitride (Si3N4), carbon, and alumina (Al2O3).

All pieces tested had their contact surfaces polished and roughness controlled to assure an average of 0.1 to 0.5 mm. Each test was performed under the following conditions: room temperature 21°C, 9.8 N of charge applied at 4000 rpm for a total of 40 000 revolutions.

Hydrodynamic Performance Tests with Mock Loop Circuit. A performance test circuit was assembled with one hanging flexible reservoir sac (Flexible Sac, 3M, St. Paul, Minnesota, USA), two pressure probes, one pressure monitor, one ultrasonic flowmeter with 3/8″ probe (Transonic Systems, Ithaca, NY, USA), pump and controller, acquisition PCI slot, and a laptop with Labview software (National Instruments, Austin, TX, USA).

The mock loop circuit was set with water solution with 37% of volume filled with glycerin to simulate the blood viscosity and density. The hanging flexible reservoir was filled with 0.4 L and placed 0.5 m above the pump. The pressure gauges were connected 0.3 m from pump inlet and outlet ports. The ultrasonic flowmeter transducer was located 0.15 m from pump outlet. Total length of each tubing from pump inlet and outlet to reservoir sac was 1.0 m, Fig. 4. The mock circuit was set horizontal to the table for easy adjustment of pump afterload using a screw clamp. Any air was removed from the circuit before the data acquisition [START_REF] Hansen | Miniaturized all-in-one rpm controllable actuator for gyro centrifugal blood pump[END_REF]. Normalized Index of Hemolysis (NIH) Tests. According to ASTM Standard Practices F1830 and F1841, the hemolysis test was divided into five steps: collection and preparation of blood, mock loop setup, 6 h test, PFH measurement, and NIH calculation.

Flexible Reservoir Pressure and Flow Transducers

Implantable Centrifugal Blood Pump

Blood was drawn from human volunteer using a large bore needle into a 500 mL blood bag with heparin to avoid clot formation during all procedures. No negative pressure exceeded 100 mm Hg and the blood temperature was controlled between 2°C to 8°C.

A test loop was assembled with 2 m of flexible 3/8″ polyvinyl chloride tubing, a flexible reservoir with sampling port, an ultrasonic flowmeter with probe, a pressure monitor with probes, a thermistor with thermometer, and the blood pump (similar to performance station shown in Fig. 4). Blood had the hematocrit range between 28% to 32% controlled by hemodilution with phosphate-buffered saline.

Temperature was adjusted to 37°C. The pump rotation was adjusted to provide 5L/min flow rate. A screw clamp was set around flexible tubing at the pump outlet side to produce the required pressure conditions for left ventricle assist devices (100 mm Hg). In each 6 h test, seven samples were collected T0,T1,T2,T3,T4,T5, and T6, and their respective PFH was measured.

Results

Ranking. The results of wear evaluation in different materials tested were sorted by loss of mass, and a ranking list of 10 best results was plotted in Figure 5. Values express the total loss of mass caused by wear in pairs and its total weight, with standard deviation of 0,000022 for measures. Performance curves. A diagram (Flow vs. Pressure Ahead, as shown in Figure 6) was plotted with each pump curve superimposed in order to better understand the differences between both hydrodynamic performances. PFH releasing. PFH value was measured for each sample. With this PFH variation in time T0, T1, T2, T3, T4, T5, and T6 is possible to represent hemoglobin releasing in plasma during the experiment. This progressive alteration in PFH levels in blood is caused by trauma imposed by pump.

Discussion

As described in previous studies [START_REF] Bock | New Centrifugal Blood PumpWith Dual Impeller and Double Pivot Bearing System:Wear Evaluation in Bearing System, Performance Tests, and Preliminary Hemolysis Tests[END_REF], the bearing composed of alumina with UHMWPE showed the best results in wear evaluation trials with ceramic-polymeric pairs [START_REF] Takami | Material of the double pivot bearing system in the Gyro C1E3 centrifugal pump[END_REF]. Four pairs had the minimum mass loss (0.1 mg): alumina with UHMWPE, silicon nitride with silicon nitride, carbon with UHMWPE, and carbon with nylon.

Pivot bearing systems composed only of ceramic are known to have higher vibration during pumping applications instead of shock absorption experienced in ceramic-polymeric pivot bearing systems [START_REF] Ohara | Baylor Gyro pump: a completely seal-less centrifugal pump aiming for long-term circulatory support[END_REF][START_REF] Hansen | Miniaturized all-in-one rpm controllable actuator for gyro centrifugal blood pump[END_REF].

The pump with inlet angle of 45° showed best performance results compared with other pumps built with inlet angle of 30°. Slight differences among curves were found in rotations beyond 1800 rpm when the curves from 30° pump decrease pressure ahead versus flow. Inlet port's angle is a problem to deal with when designing centrifugal blood pumps, especially the eccentric inlet port [START_REF] Andrade | Flow visualization studies to improve the spiral pump design[END_REF][START_REF] Nosé | Design and development strategy for the rotary blood pump[END_REF].

As described by several authors, NIH for LVAD should be between 0.004 to 0.02 mg/100 L to be considered satisfactory and antitraumatic blood pump [START_REF] Bock | New Centrifugal Blood PumpWith Dual Impeller and Double Pivot Bearing System:Wear Evaluation in Bearing System, Performance Tests, and Preliminary Hemolysis Tests[END_REF][START_REF] Takami | Eccentric inlet port of the pivot bearing supported Gyro centrifugal pump[END_REF][START_REF] Nosé | Design and development strategy for the rotary blood pump[END_REF]. After calculations, the preliminary hemolysis tests showed an NIH value of 0.0054 ±2.46x10 -3 mg/100 L.

Conclusions

The pair composed of alumina and UHMWPE was chosen to be the materials of the double pivot bearing system in order to avoid vibration problems.

The dual impeller centrifugal blood pump had proven to be a promising LVAD. The hydraulic characteristics are similar to other reported curves from established, durable, and reliable devices.

The authors' expectation is that this pump will become a promising Technological Innovation for Sustainability.

Fig. 1 .

 1 Fig.1. The new Implantable Centrifugal Blood Pump for cardiac assistance is shown with its double pivot bearing system composed by male and female bearings.

Fig. 2 .

 2 Fig. 2. The design process was lead according to current needs of cardiac patients who cannot afford Left Ventricular Assist Device technology. The reduced number of parts is shown in two different options of motor attached with pump's rotor by a magnetic coupling.

Fig. 3 .

 3 Fig. 3. Different types of prototypes obtained by SLS or Machined in different types of materials from translucent polymers to titanium.

Fig. 4 .

 4 Fig. 4. Simple mock loop circuit assembled for data acquisition during performance tests. Two pumps were tested with different inlet angles, 45° and 30°. The angles were chosen according to similar devices. The pump speed rotations were fixed at 1200, 1400, 1600, 1800, 2000, and 2200 rpm. The software plotted a curve for each rotation, and for each pump. With screw clamp open, the first point collected was the maximum flow for each pump speed. Closing the screw clamp, the pump afterload increases as the flow decreases, and the next points are collected each 0.5 L/min, successively until 0.0 L/min is achieved, when the clamp is totally closed. The pump speed rotations were fixed at 1200, 1400, 1600, 1800, 2000, and 2200 rpm. The software plotted a curve for each rotation, and for each pump. With screw clamp open, the first point collected was the maximum flow for each pump speed. Closing the screw clamp, the pump afterload increases as the flow decreases, and the next points are collected each 0.5 L/min, successively until 0.0 L/min is achieved, when the clamp is totally closed.

Fig. 5 .

 5 Fig. 5. Ranking of materials under wear tests.

Fig. 6 .

 6 Fig. 6. Performance curves showing hydrodynamic characteristics for both pumps.

Acknowledgments

The authors are grateful to Dr. Yukihiko Nosé for enormous collaboration to this project. Also, it is mandatory to thank all colleagues from Baylor College of Medicine (BCM), Federal Institute of Technology (IFSP) as well as CNPq, HCor and Adib Jatene Foundation (FAJ) for partially supporting this research.