Mitsuru Nakazawa
email: mitsuru.nakazawa@rakuten.com

Masahumi Muta
email: masafumi.muta@rakuten.com

Kazuki Ookawara
email: okawara.kazuki@entcomp.esys.tsukuba.ac.jp

Soh Masuko
email: so.masuko@rakuten.com

ECEC2017: The Workshop on E-Commerce and Entertainment Computing

Keywords: E-Commerce, Entertainment Computing, Workshop

Online e-commerce has been growing continuously. According to eMarketers latest forecasts, worldwide retail e-commerce sales will reach $4 trillion USD by 2020. In addition, using cutting-edge technologies such as augmented reality (AR), virtual reality (VR), mixed reality (MR), sensing technology, image processing, robotics and online payment technology, new shopping experiences that enhance offline or online shopping, or integrate the two types of shopping experiences are being introduced. In this workshop, new concepts and recent progress in shopping experiences are discussed from various perspectives. The workshop will include invited talk sessions by world-leading innovators, and interactive poster and demonstration presentations of submitted papers and abstracts.

Introduction

Before the emergence of the Internet, shopping was limited to brick-and-mortar stores, where consumers went to see, touch and purchase physical items (offline shopping). However, after the Internet emerged, it became possible for consumers to engage in a new shopping experience, i.e., online shopping. Online shopping has profoundly changed how we purchase goods. Now we can view and purchase products from a large number of online stores anytime from anywhere. According to eMarketers latest forecasts [START_REF] Emarketer | Worldwide Retail Ecommerce Sales Will Reach $1.915 Trillion This Year[END_REF], worldwide retail e-commerce sales will reach $4 trillion USD by 2020.

Recently, many cutting-edge technologies such as augmented reality (AR), virtual reality (VR), mixed reality (MR), sensing technology, image processing, robotics and online payment technology have been rapidly refined. Using these technologies, novel services that enhance conventional offline or online shopping have been introduced, e.g., robot reception in a store [START_REF] Nestle | Nestle to use humanoid robot to sell Nescafe in Japan[END_REF] and AR furniture shopping [START_REF] Cnet | iPhone's futuristic AR dream starts with Ikea[END_REF][START_REF] Murakami | Mobile Virtual Interior Stylization from Scale Estimation[END_REF]. Moreover, for better coordination of the two types of shopping experiences, there have been some attempts to encourage online shopping in an offline store and vice versa, i.e., Offline-to-Online and Online-to-Offline (O2O). In the near future, it is expected that consumers will not be conscious of the difference of the two, which look like smoothly integrated [START_REF] Bandara | Ubira: A Mobile Platform for an Integrated Online/Offline Shopping Experience[END_REF].

O2O

• Acquiring virtual currency after offline shipping [START_REF]McDonalds and Rakuten Announce Rakuten Point Card Partnership to Improve Customer Convenience[END_REF] • In-store pick-up service for online orders [START_REF] Rakuten | Rakuten and Lawson to Collaborate to Launch Convenience Store Pickup Service[END_REF] • Digital signage for off/online shopping [START_REF]Digital Signage Today[END_REF] • …

Enhanced offline shopping

Enhanced online shopping

• Virtual mirror [START_REF] Fitnect | 3D Virtual fitting dressing room / mirror[END_REF] • Robot reception [START_REF] Nestle | Nestle to use humanoid robot to sell Nescafe in Japan[END_REF] • Cashier-free store [START_REF] Amazon | Amazon Go[END_REF] • Popularity visualization [START_REF] Masuko | AR-HITOKE: Visualizing Popularity of Brick and Mortar Shops to Support Purchase Decisions[END_REF] • …

• AR Home shopping [START_REF] Cnet | iPhone's futuristic AR dream starts with Ikea[END_REF][START_REF] Murakami | Mobile Virtual Interior Stylization from Scale Estimation[END_REF] • VR store shopping [START_REF] Trillenium | Trillenium VR showroom[END_REF] • 3D Body avatar [START_REF] Fits | Fits.me[END_REF] • Easy-order gadgets [START_REF] Google | Start shopping with the Google Assistant on Google Home[END_REF][START_REF] Amazon | Amazon Dash Button[END_REF] • …

Core technologies

AR/VR/MR, Sensing technology, Image processing Robotics, Online payment technology, etc. In this section, we introduce related work of enhanced offline and online shopping, and O2O services. Figure 1 represents the overview of related work.

Enhanced offline shopping

To make offline shopping more convenient or entertaining, various attempts have been made in an physical store by using cutting-edge technologies. In a fashion store, a virtual mirror was installed by using AR technology so that a customer can try on as many items as they want without putting off their clothes [START_REF] Fitnect | 3D Virtual fitting dressing room / mirror[END_REF]. In an electronics retail store, intelligent movable robots were assigned to eliminate the shortage of professional explainers who have much knowledge of its products [START_REF] Nestle | Nestle to use humanoid robot to sell Nescafe in Japan[END_REF]. In a grocery store, [START_REF] Amazon | Amazon Go[END_REF] proposed a cashier-free system by making the best use of vision sensing and pattern recognition technology to realize a store with no lines and no check out. In a sales event of a department store, to easily understand the popularity of each event store, 3D-animated human-shaped icons appeared on a paper map representation in a large display monitor based on hourly point of sales (PoS) data [START_REF] Masuko | AR-HITOKE: Visualizing Popularity of Brick and Mortar Shops to Support Purchase Decisions[END_REF]. Purchasing behavior data such as PoS data and a customer flow map are valuable for not only customers but also retailers who hope to optimize their store layout [START_REF] Abeja | ABEJA PLATFORM for Retail[END_REF].

Enhanced online shopping

Although even conventional online shopping is convenient in term of anytime anywhere shopping, it is originally less sense of reality because an intangible product is displayed in not actual size on a 2D web browser. To solve such lack of reality, AR technology has been often employed. For example, [START_REF] Cnet | iPhone's futuristic AR dream starts with Ikea[END_REF][START_REF] Murakami | Mobile Virtual Interior Stylization from Scale Estimation[END_REF] proposed an AR home shopping experience where actual size furniture appears on a smartphone display. VR technology, which allows a user to secure a higher immersion feeling, is another approach to put more reality in online shopping. [START_REF] Trillenium | Trillenium VR showroom[END_REF] developed a VR showroom that enables a user to dive into a virtual store that looks exactly like a physical one. In online clothes shopping, technology of 3D body shape estimation can be also utilized. To determine if an article of clothing suits customer's body or not on a website, [START_REF] Fits | Fits.me[END_REF] displayed a clothing 3D model with a representative 3D body shape, which is generated from body shape estimation using anatomical information (e.g., height and weight).

Another enhancement of online shopping is to save customer's trouble in ordering goods. Recently, some Internet-of-things gadgets that allow an user to order goods by voice recognition [START_REF] Google | Start shopping with the Google Assistant on Google Home[END_REF] or just pushing a button [START_REF] Amazon | Amazon Dash Button[END_REF] have been released.

O2O services

To draw potential customers from offline to online shopping or vice versa, some O2O services have been launched. For examples, [START_REF] Rakuten | Rakuten and Lawson to Collaborate to Launch Convenience Store Pickup Service[END_REF] started in-store pick-up service for online orders. In [START_REF]McDonalds and Rakuten Announce Rakuten Point Card Partnership to Improve Customer Convenience[END_REF], an user got rewarded with virtual currency that can be used in online shopping after offline shopping. [START_REF]Digital Signage Today[END_REF] released a digital signage display that can order goods on-line in case of that they are sold out in the physical store.

Overview of ECEC2017

Although many services beyond conventional offline and online shopping have already been proposed as described in Section 2, we believe that shopping experiences will keep evolving based on upcoming new technologies. Therefore, to discuss new concepts and current progress in shopping experiences, we will hold this workshop. It will include invited talk sessions and an interactive poster and demonstration session. In the invited talk sessions, world-leading innovators will give a talk about their specialized fields of VR shopping [START_REF] Rakuten | Getting Real About VR in e-commerce: Rakuten Virtual Boutique[END_REF], Retail analysis [START_REF] Abeja | ABEJA PLATFORM for Retail[END_REF], Image processing for e-commerce [START_REF] Simo-Serra | Research[END_REF] and Drone business [START_REF] Rakuten | SoraRaku: Drone Delivery[END_REF]. The interactive poster and demonstration session will cover the following topics:

-Gamification of shopping experiences -Entertainment psychology and shopping experiences -Shopping attractions -Online-to-offline, Omni channel with entertainment -Use of wearable/smart devices for shopping -Physical shopping interfaces -Augmenting real-world shopping experiences using VR/AR/MR technologies -Image/Video processing for e-commerce -Best practices in e-commerce and entertainment

We look forward to discussion with you toward future shopping at ECEC2017.

Fig. 1 .

 1 Fig. 1. Overview of enhanced offline and online shopping, and O2O services


D M Fonseca
email: davi.fonseca@ntnu.no

Yves Méheust

Jon O Fossum
email: jon.fossum@ntnu.no

Kenneth D Knudsen

K J Maloy

K P S Parmar

K J Måløy

Phase behavior of platelet-shaped nanosilicate colloids in saline solutions ─ a small-angle X-ray scattering study

Keywords: Platelet-shaped colloids, nematic ordering, phase diagram, SAXS

Phase behavior of platelet-shaped nanosilicate colloids in

saline solutions -a small-angle X-ray scattering study.

Introduction

Colloidal suspensions of 2:1 clay particles in aqueous salt solutions make ideal model systems for the study of interactions between platelet-shaped particles. Indeed, the particleparticle interaction consists of (i) the van der Waals attraction and (ii) the electrostatic repulsion between the particles' electric double layer (McBride & Baveye, 2002). The extension of the latter repulsion can be easily tuned by changing the electrolyte concentration [START_REF] Israelachvili | Intermolecular and Surface Forces[END_REF]. This complex particle-particle interaction combined with the strong particle anisotropy results in rich phase behaviors. The phase diagram of the monodisperse synthetic 2:1 clay Laponite dispersed in saline solution, in particular, has been the subject of much attention (Mourchid et al., 1998;Bonn et al., 1999;Lemaire et al., 2002). Such dispersions are now well-known for the existence of a spontaneous nematic arrangement of the platelets at given salt-and particle-concentrations (Mourchid et al., 1998;Lemaire et al., 2002;van der Beek & Lekkerkerker, 2003).

Another synthetic clay, Na-fluorohectorite (NaFHT), has been found to exhibit interesting phase behavior when suspended in saline solutions. NaFHT presents polydispersity in both particle size and aspect ratio [START_REF] Kaviratna | [END_REF]. In the presence of polydispersity a spontaneous phase segregation occurs in the suspensions (Fossum, 1999;Bates, 1999;van der Kooij, 2001), with several phases co-existing in strata. X-ray Diffraction studies of such systems (DiMasi et al., 2001) have investigated the clay particles' orientations in these NaFHT-NaCl-H 2 O systems, taking advantage of their nano-layered nature. Three distinct gel regions were identified and characterized by differences in orientational order and/or the size of ordered domains. One phase was presented as nematic. Those findings are consistent with visual observations (Fossum et al., 2005), including observations through crossed polarizers: a birefringent region, coinciding with the region exhibiting orientational order (as inferred from the wide-angle X-ray scattering study), was observed. More recently, the existence of an isotropic to nematic transition in these systems has been corroborated by MRI studies of anisotropic of water self-diffusion (de Azevedo et al., 2007).

However, the corresponding phase diagram has not yet been determined with precision, nor has the orientationally-ordered gel phase been fully characterized as nematic. In the present work, synchrotron small-angle X-ray scattering (SAXS) is used to obtain a fine characterization of the phase diagram, over a large NaCl concentration range. The experimental method is presented in section 2 and the data analysis and results in section 3; section 4 is the conclusion.

The samples consist of Na-Fluorohectorite (NaFHT) crystallites suspended in a saline solution. They were prepared in the following way: Li-Fluorohectorite clay was purchased in powder form from Corning Inc. (New York). It was cation-exchanged using NaCl, and then the extra Cl -ions were removed through dialysis. After drying, the obtained clay crystallites have the nominal chemical formula Na 0.6 (Mg 2.4 Li 0.6 )Si 4 O 10 F 2 .

Several suspensions of such crystallites were subsequently prepared, with a 3% concentration of clay (w/w), and NaCl concentrations ranging from 0.1 to 25 mM (Table 1).

After addition of the clay powder to the saline solution, the suspensions were left shaking overnight; after twelve hours, they were poured into 2 mm diameter capillaries made of quartz glass (Hilgenberg Mark tubes with 0.01 mm wall thickness). They were then allowed to settle for thirty days. After this time, one could observe up to four superimposed phases, as shown in Fig. 1: the phase at the very bottom is opaque; that on top of it is a translucent gel; the third phase observed from the bottom up is a transparent gel; the top phase is a transparent sol.

Scattering setup

SAXS experiments were performed on the Dutch-Belgian Beamline (DUBBLE) at the European Synchrotron Radiation Facility (ESRF), in Grenoble (France). This beamline provides a focused, monochromatic radiation with an energy tunable in the range 5-30 keV, corresponding to wavelengths between 0.41 and 2.48 Å. A wavelength of 1.55 Å was chosen for this experiment.

The experimental hutch contains the SAXS camera with a maximal and minimal sampleto-detector distance of 8 and 1.4 m, respectively. The maximum camera length D = 8 m was chosen for the whole length of the measurements, so as to investigate length scales as large as possible. Two-dimensional SAXS images were recorded using a two-dimensional multiwire gas-filled detector (Gabriel & Dauvergne, 1982). This detector has an image size of 133x133 mm 2 with a spatial resolution of 250±5 µm. The beam size that we used had a diameter of c. 0.2-0.3 mm and the beam stop was approximately a 5x5 mm 2 square. Consequently, for the chosen wavelength of 1.55 Å, the q-range accessible in the experiment was 0.013-0.33 nm -1 , corresponding to probed length scales between 20 and 480 nm. The measurement setup also contains a linear wide-angle X-ray scattering (WAXS) detector based on a curved microstrip glass strip counter. This allowed to simultaneously record SAXS and WAXS data with a time resolution down to 1 ms/timeframe. The WAXS data will not be discussed in this paper.

In order to avoid repeatedly entering the experimental hutch to change samples, a sample holder containing ten capillaries placed side by side and regularly spaced was employed. The samples were placed in the beam in turn by translating the holder using a remotely-controlled horizontal translation stage. Another translation stage allowed controlling the vertical position of the sample with respect to the beam.

Experimental protocol

For each sample: (i) a vertical transmission scan was carried out and (ii) SAXS patterns at different heights were collected. Table 1 lists the details of vertical positions at which SAXS data was recorded for each sample. The liquid phase at the top of the sample tube was not investigated. All SAXS images were recorded with an exposure time of 60 s. They were subsequently corrected for the detector's transfer function, and normalized with respect to the sample transmission. Scattering from the empty tubes proved to be negligible compared to the data, and therefore no subtraction of the empty tube data was necessary. Iso-intensity lines of the SAXS images are well described by ellipses. Hence, a custommade MATLAB program was used to fit ellipses to such iso-intensity lines. Practically, the fitting procedure is accomplished in the following way. First, a narrow intensity range is selected (Fig. 3a), and then the pixels with an intensity that falls in that range are extracted from the two-dimensional SAXS image. Subsequently an ellipse is fitted to the cloud of points defined by the horizontal and vertical coordinates of the selected pixels (Fig. 3b). This procedure provides the center of the ellipse, the length of its major axis, a, that of its semiminor axis, b, and its angle of tilt with respect to the horizontal. From a and b one can calculate the eccentricity, e The obtained fit parameters can be related to the scattering process as follows: (i) the center of the ellipse is a fine estimate for the position of the direct beam; (ii) the principal axes of the ellipse are related to the orientational ordering of the scattering clay particles; (iii) the eccentricity of the ellipse is a measure of the image's anisotropy: an image with a perfect axial symmetry would yield a value e = 0, while a value closer to 1 denotes a very anisotropic image; and (iv) the angle of tilt of the ellipse is related to the preferential orientation of the scatterers with respect to the laboratory frame.

Data analysis

Method

Finally, one-dimensional intensity profiles of scattering intensity versus q along the principal axes of the ellipses were computed. Those profiles were generated by integrating the images over azimuthal angles in 5 o wide sectors around each of the principal directions. The resolution of those profiles along the radial direction was set to 250 radial bins.

Results

Phase diagram

The computed eccentricities were plotted as a function of the vertical position for each sample. From these plots (not shown here) it is readily noticeable that: (i) a region at the bottom part of the sample corresponds to eccentricities spread over a wide range of values, (ii) a region which only contains high eccentricities values is found on top of the latter one, and (iii) the third region from the bottom up contains only low eccentricities values. Note that the fourth (and top) phase observed visually in the highest part of the sample tube was not studied by SAXS, and will not be discussed in what follows. The three regions found from the SAXS data correspond to the three bottom phases observed visually. Since the anisotropy of the scattering images is characteristic of particle orientational ordering, the phases were identified as the sediment, a gel phase with preferential particle ordering, and an isotropic gel, respectively.

From these plots for individual samples, a surface plot taking all samples into account was constructed. Since the concentrations used here form a non-regular and non-monotonic grid, MATLAB was used to interpolate the data on a regular grid. Fig. 4(a) shows a grayscale view of that surface plot, with salt concentration along the horizontal axis and vertical position along the vertical axis; grayscale intensities denote the eccentricity value at a given point of the parameter space. In this representation, sudden changes in the gray level denote possible phase boundaries. A dark gray zone at the top of the image obviously denotes the isotropic gel phase, since the scattering from that phase is isotropic. On the other hand, the images collected in the gel phase with a preferential orientation of the particles must correspond to high eccentricities, since the characteristic orientational ordering causes a very anisotropic scattering. Therefore, the white zone on the left part of the image, under the region corresponding to the isotropic gel, corresponds to that anisotropic gel.

In order to complete our understanding of the phase boundaries as inferred from the SAXS data, a grayscale image of the transmission data was also made (Fig. 4b). Owing to the relatively sharp change in transmission from the sediment to the gel phases, it is easy to identify the sediment. Note that the images of Figs. 4(a) and 4(b) complement each other; their joint interpretation allows clear definition of the phase boundaries for the sediment, anisotropic gel and isotropic gel. We are left with an unidentified region in the right part of the image, between the regions corresponding to the sediment and to the isotropic gel. That region exhibits moderate attenuation, and moderate eccentricity values that vary on a small scale in the parameter space. It also exhibits all possible angles of tilt for the fitted ellipses (tilt angle data are not shown here). Fig. 5 summarizes this phase diagram for the suspensions. Note that the use of the relative vertical position as a vertical axis in Figure 5 is somewhat un-physical. It can however be related to a more physical parameter such as the particle volume fraction. Indeed, the vertical phase segregation is thought to be related to a vertical gradient in volume fraction, as a consequence of polydispersity. In this sense, the phase diagram in Fig. 5 can be related to better known phase diagrams of clay colloids in saline solution (that of laponite, for example), as a function of particle volume fraction and ionic strength of the solution. We do not know yet how the relative vertical position in the tube translates into local volume fraction, hence we cannot convert the vertical axis into a volume fraction axis. When Fig. 5 is compared to the two previous estimates of the diagrams, one from visual observation, the other one from WAXS data (see DiMasi et al. (2001) and Fossum et al. (2005)), it is evident that the main features are consistent. The anisotropic gel found here is the nematic gel phase as identified from WAXS data. Fig. 2(b) is a typical SAXS image recorded from this phase; the orientation of the elliptic iso-intensity lines is consistent with the previous WAXS analyses, according to which the platelet-shaped clay particles are standing on average with their short dimension along the horizontal (DiMasi et. al., 2001). The rightmost region in the diagram (Fig. 4a) corresponds to what DiMasi et al. (2001) denote as a small nematic domain phase (SD). We believe that this region contains in fact many small nematic regions. At the scale of the scattering volume, this results in SAXS data with a moderate anisotropy, the magnitude and preferential orientation of which are not fixed for the whole region.

Two discrepancies between the current phase diagram and the previous estimates can be spotted. One of them is that the phase boundaries are not exactly at the same vertical position. This is expected since the samples in the different experiments were allowed to settle for unequal times, and the phase boundaries are known to change position for several months before they stabilize. The other evident new observation compared to our previous studies concerns the boundary of the two gel phases at low salt concentrations. Its first two points in the previous estimates are much higher than what is observed here (around two times higher), with respect to the rest of that boundary. The behavior observed in the present experiment is systematic and is observed for five different concentrations here, whereas it was observed for only two concentrations in the other works. Currently, one may suggest several alternative explanations for this difference, and this will be subject for future work.

Spectra along the principal axes

For a given SAXS image, the scattering intensity as a function of the modulus q of the scattering vector was also plotted along the two principal directions of the image, as determined by the fitting of ellipses to iso-intensity lines. Fig. 6 presents such q-plots for a SAXS image in the isotropic phase and another one in the nematic phase of the sample with saline concentration of 1 mM.

The q-plots in Fig. 6 appear as consisting of several power law regimes. This is expected in SAXS data from systems of aggregated particles (Schmidt, 1991). On all plots, a smooth crossover is noticed. It corresponds to a characteristic length scale of approx. 20 nm. This could be related to the average thickness of the stacks of clay platelets, which is the only characteristic length of the particles that can be probed in the q-range investigated with SAXS. Another interpretation for this crossover scale would be that small nematic domains exist locally in the two gel phases, with a typical particle-to-particle distance of around 20 nm. The crossover is smooth due to polydispersity in the particle thicknesses. Note that the characteristic length scale does not correspond to a regular periodicity in the meso-structure, since no peak is visible in the data at the corresponding q-value. Hence, none of the phases exhibits positional order at the length scales probed by the SAXS experiment. In particular, the lower gel phase is ordered with respect to particle orientations but not to positions.

The values for the exponents of the power laws, as estimated from slopes in the log-log plots in Fig. 6 are presented in Table 2. We notice that at higher q-values, the slopes seem to approach -4, possibly indicating crossover into the Porod regime as the probed length scales become smaller than the crossover length scale. We also notice that at lower q-values, the slopes approach -2. This is expected for mono-disperse platelets with no correlations between particle-positions and orientations, either (i) nematically-oriented, provided that q is pointing along the normal to the platelets, or (ii) randomly-oriented (Ramsay, 1990). For nematicallyoriented mono-disperse platelets with no correlations between positions and orientations, a slope of -3 is expected when q points perpendicular to the short plate direction (Ramsay, 1990). Note that our observations in terms of power-law exponents may be influenced by the fact that our platelets are not mono-disperse, and that positions and orientations of particles may be correlated.

Conclusion

SAXS experiments have allowed a precise characterization of the phase diagram of suspensions of Na-fluorohectorite platelet-shaped particles in saline solutions. The characterization was done based on transmission data, and on two-dimensional SAXS images.

Ellipses were fitted to iso-intensity lines of the SAXS images. The phase boundaries were obtained through joint analysis of the transmission data and of results for the eccentricities and tilt angles of the ellipses. Among the different phases observed, one is a gel phase exhibiting a high degree of orientational order, while the other one is an isotropic gel. This phase diagram is consistent with our previous estimates using other approaches. Moreover, plots of the integrated intensities versus the modulus of the scattering vector along the principal axes of the ellipses for both gel phases exhibit power law behaviors with a smooth crossover at a characteristic length scale that may correspond to the typical particle thickness, and exponents that approach those of well-known configurations at the lower and higher qvalues. These q-plots confirm that no positional order exists in any of the phases. X-ray Scattering techniques have proved to be a technique appropriate for discriminating between different phases in these samples. A prospect of the study concerns further understanding of the differences between the different phases, in terms of the geometry of the porous space between the particles (Knudsen et al., 2004), focusing on the power law behavior of q-plots. The ultimate goal is to understand the underlying mechanisms responsible for the formation of the different phases. Figure 6 Integrated intensities plots as a function of the modulus of the scattering vector, q , along the principal axes of the ellipse, for both a point in the isotropic phase and also for a point in the nematic phase. The smooth crossover is positioned at a q value corresponding to a length scale of about 20 nm. The solid lines denote reference slopes.

Table 1 Vertical positions at which SAXS data was recorded, for each sample.

Table 2 Power law exponents determined from Fig. 6.

Fig. 2

 2 Fig. 2 displays examples of SAXS images recorded from the lower and upper gel phases, for a salt concentration of 1 mM. The data in Fig. 2(a) is isotropic, while the one displayed in Fig. 2(b) is clearly anisotropic, indicating a preferential orientation of the clay crystallites.

  tested at different intensity levels, and the fit results were shown to depend only weakly on the intensity range used to obtain them.

Figure 1

 1 Figure1Na-Fluorohectorite sample with a particle concentration of 3 % (w/w) and a salt (NaCl) concentration of 4.5 mM. The 4 four phases are easily identifiable.

Figure 2

 2 Figure 2 SAXS images recorded in the upper (a) and lower (b) gel phases. The anisotropic image in (b) indicates a preferential orientation of the clay crystallites in the lower phase.

Figure 3

 3 Figure 3 (a) A three-dimensional view of a scattering image. The arrow indicates a range that could be used to generate the cloud of points. (b) The blue circles represent the cloud of points inside the range of the scattering profile. The green ellipse is the initial guess for the fitting procedure. The red ellipse is the evaluated best fit to the cloud of points.

Figure 4

 4 Figure 4 (a) Greyscale map for the eccentricity values computed from the SAXS data, as a function of the salt concentration and vertical position in the sample tubes. (b) Idem, but computed from the transmission data.

Figure 5

 5 Figure 5Phase diagram created from the greyscale maps for eccentricity and transmission. The displayed regions are sediment (S), nematic gel (NG), isotropic gel (IG), and region containing small domains (SD). The line thickness corresponds to the uncertainty on the boundary position.

  Figure 1.

  Figure 2.

  Figure 4.

Figure

  Figure 6.

Acknowledgements

The authors acknowledge the European Synchrotron Radiation Facility for provision of synchrotron radiation facilities and we would like to thank Dr. Igor Dolbnya for assistance in using beamline BM26B. The two anonymous referees are also acknowledged for helping improve the manuscript. This work has received partial financial support from the Research Council of Norway (RCN) through the NANOMAT Program: RCN project numbers 152426/431, 154059/420 and 148865/432, as well as through 138368/V30 and SUP154059/420. Van der Kooij, F. M., van der Beek, D. & Lekkerkerker, H. N. W. (2001). J. Phys. Chem. B 105, 1696-1700.

Nematic along semi-minor axis -2.3 ± 0.1 -2.9 ± 0.1 Isotropic along semi-major axis -2.2 ± 0.1 -2.4 ± 0.1 Isotropic along semi-major axis -2.5 ± 0.1 -2.4 ± 0.2 Table 2.


Tomoki Kajinami
email: kajinami@mis.ous.ac.jp

Kazuya Hasegawa

Watching Support System by Annotation Displaying According to Fighting Game Situations

Keywords: e-Sports, Fighting Game, Watcher Support

This study proposes a watching support system for a beginner watcher of fighting games. The fighting games is a type of e-Sports genre similar to Karate and boxing. Two game characters (e.g., a grappler) fight each other in the game. As with actual fighting sports, positioning on the game field of the game character in this game is important in winning the match. A concept of displaying annotation according to situations based on the characters' positioning for a beginner watcher of the fighting games is proposed from a previous study. The present paper defines three typical situations and proposes keyword and graphic annotations to encourage understanding of the match and emphasize amusement for the beginner watcher of fighting games. This study also develops a prototype system, and their annotations are superimposed on the match video. As a result, the proposed system can support beginner watchers through subjective experiments.

Introduction

This study proposes a watching support system for a beginner watcher of fighting games, a type of e-Sports genre similar to Karate and boxing. Two game characters (e.g., a grappler) fight each other in the game. A vast amount of e-Sports competitions have recently been held worldwide [START_REF] Adamus | Playing Computer Games as Electronic Sport: In Search of a Theoretical Framework for New Research Field[END_REF]. Accordingly, the analysis of the competitive game players' community has been studied [START_REF] Taylor | Raising the Stakes: E-sports and the Professionalization of Computer Games[END_REF]. As with actual fighting sports, the players must consider the positioning of the game characters on the game field to win a fighting game match. A concept of displaying annotation according to situations based on the characters' positioning for a beginner watcher of the fighting games is proposed herein from a previous study [START_REF] Kajinami | Supporting Method for Watching e-Sports Considering Relationship between Player's Conception and Game Field[END_REF]. The present paper defines three typical situations, namely long-distance, short-distance, and corner situations, and proposes keyword and graphic annotations to encourage understanding of the point of the match and emphasize amusement for a beginner watcher of the fighting games. The game characters' positions are extracted from the match video by template matching. Furthermore, this study develops a prototype system, and their annotations are superimposed on the match video. This study shows that the proposed system can support beginner watchers through subjective experiments.

Displaying Annotation According to Three Typical Situations

Long-distance, short-distance, and corner situations are defined herein. The game screen width is assumed to be 1280 pixels. The x coordinate of the game character on the left is xl, while that on the right is xr. In this study, keyword and graphic annotations are proposed depending on the three typical situations. Table 1 summarizes the correspondence relationship between their situations and displayed annotations. The keyword annotations vividly show the contents of situations. The graphic annotations indicate the places, where a high possibility of a battle occurrence on the screen exists. The game players in the long-distance situation tend to wait and see the play of the opponent, and too much intense battle is not done. "Wait and see" is displayed, and a large blue rectangle is displayed between the characters. Meanwhile, the game players in the short-distance situation tend to actively attack opponents. Intense battle is done, and the victory or defeat tends to be decided at a stretch. "! Explosive !" is displayed, and a small rectangle is displayed around the characters. In the corner situation, the other character is advantageous, while the other chasing a corner is not. The character on the advantage side tends to move to close off the escape path of the disadvantage-side character. An important battle in the game tends to be done in the sky space rather than in front of both characters. "Chance" and "!" are displayed according to the advantage or disadvantage side. A rectangle is displayed in the sky between the two characters. Section 3 presents the displaying examples of the annotations.

Prototype System

The character positions herein are extracted from a game movie by template matching using OpenCV. The template image is an image of a part of the character image of 40 × 40 pixels. The prototype system is developed for a specific game title "Street Fighter V." Figure 2 shows an execution example of the proposed system. Figure 2(a) presents an example, in which an annotation is displayed in the long-distance situation. "Wait and see" is displayed, and a blue rectangle is shown to cover a large area between the two characters. Figure 2(b) depicts an example, in which the annotation is presented in the short-distance situation. "Explosive" and a green rectangle are displayed around both characters. Figure 2(c) shows an example, in which the annotation is presented in the corner situation. "Chance" is displayed around the advantage-side character, while "!" is displayed around the disadvantage side character. A red rectangle is displayed on the sky between the two characters.

Experiment

The experiment aimed to evaluate whether the point of the match becomes easy to understand and emphasize amusement by the proposed system. We prepared the match videos with annotations using the proposed system and without annotations. The subjects were beginner watchers, who were not competitive players. Each subject watched the match videos with proposed annotations and without annotations. The order of video watching was different for each subject. A total of 10 subjects (A-J) participated in the experiment.

Table 2. Evaluation scores by the subjects.

A B C D E F G H I J Average Video with annotations 7 3 5 5 4 7 3 7 7 6 5.4 Video without annotations 3 5 2 4 3 3 3 3 6 4 3.6 Table 2 summarizes the experimental result on the amusement by easiness of point of the match (7: Good, 1: Bad). We asked the subjects to evaluate whether the point of the match became easy to understand with the proposed annotation. Table 2 shows that the average evaluation value was higher in the proposed system. Eight out of 10 subjects highly evaluated the proposed annotations. In other words, there is a tendency that the proposed annotations can emphasize amusement by the easiness of the match highlight. We then focused on the comments obtained by the subjects, and performed a qualitative evaluation of the proposed system.

The typical positive comments obtained by the subjects were as follows. "I could get prediction of the battle (I could understand the point of the battle). (A and I);" "It is interesting by displayed annotations. (E, F, and G);" "Even in an unknown game, I could know where to focus on. (H);" and "It become easy to follow changing in battle. (J)." These comments, especially those from subject H, implied that the point of the match became easy to understand with the proposed system. The proposed system can support a beginner watcher with poor prior knowledge of the game title.

The typical negative comments obtained by the subjects were as follows. "The screen was complicated, and the screen was sometimes difficult to see. (D, E, G, and J)" and "When the keyword and graphic annotations are viewed at the same time, the game characters are difficult to see. (F and G)." These comments expressed the need for improvements in visibility as the future works. Moreover, subject B said "I can note point of battle when without annotations," and obtained a low score for the proposed system. He was a beginner of the fighting game, but had experience of a similar action game. Therefore, his watching level can be considered higher than that of the other beginner watchers. His comment imposed a consideration of the annotation displaying methods according to the watchers' watching levels as a future work.

Conclusion

This study proposed a watching support system for a fighting game's beginner watchers. Three typical situations were defined herein based on the game characters' positions in the game field. The proposed system displayed keyword and graphic annotations depending on the situations to support understanding of the watching point of the match. The effectiveness of the proposed system was examined through subjective experiments. The result showed that the proposed system can support understanding of the point of battle and emphasize amusement as regards watching the fighting game matches. The future work will focus on improving visibility and examining the annotation presentation methods according to the watchers' watching levels.

Figure 1 (

 1 a) shows the long-distance situation defined by xrxl ≧ 300 pixels. Figure 1(b) presents the short-distance situation defined by xrxl < 300 pixels. Meanwhile, Figure 1(c) illustrates the corner situation defined by (xl < 200 ∧ 200 ≦ xr ≦ 1080) ∨ (200 ≦ xl ≦ 1080 ∧ 1080 < xr).

Fig. 1 .

 1 Fig. 1. Three typical situations in fighting games.

Fig. 2 .

 2 Fig. 2. Execution example of the prototype system.

Table 1 .

 1 Displaying annotations according to the three situations.

	Situations	Keyword annotation	Graphic annotation
	Long-distance Wait and see	Large blue rectangle
	Short-distance ! Explosive !	Small green rectangle
	Corner	Chance (Advantage side)	Red rectangle
		! (Disadvantage side)


Syoichiro Ota

Hayaki Kawata
email: kawata.hayaki@entcomp.esys.tsukuba.ac.jp

Masahumi Muta
email: masafumi.muta@rakuten.com

Soh Masuko
email: so.masuko@rakuten.com

Jun ' Ichi Hoshino

AniReco : Japanese Anime Recommendation System

Keywords: Recommendation system, Interface design, Anime

Along with development of animation works and their market, it has become more difficult for users to find out works corresponding to their own preference from among huge number of animation works as well as to recognize the whole picture of contents related to them. Therefore, "AniReco" is proposed in this paper which is an animation work recommendation system capable of recommending animation works and their related contents in a crosssectional fashion while reflecting users' potential preference. As a result of evaluation experiment performed aiming at verifying the system usability and contents of recommendation; it has been proved that the recommendation system is capable of recommending animation works which reflect users' preference.

Introduction

With more than 200 pieces of animation works broadcast annually in Japan in recent years, animation market scale in a broad sense including contents such as related goods has reached approximately 1.8 trillion yen [START_REF]Anime industry report 2016[END_REF]. In addition, places where animation work and manga titled as "Pilgrimage" was set and locations related to it have been frequently taken up as a topic these days because of many people visiting there, having impacts on regional industries including local governments which develops goods and services in collaboration with animation works. Moreover, about 30% of the animation industry market as mentioned above is shared by overseas sales and animation makes up the largest share in export value of Japanese broadcast contents [START_REF]Analysis on overseas deployment of breadcast contents 2014[END_REF]. In consideration of the situations above, animation is believed to be one of important industrial markets.

Animation is content with various elements including genre, scenario, drawing, music and voice actor, however, the related contents such as goods and sacred places may expand along with the development of works. Therefore, it has become not easy for audiences to find out works corresponding to their own preference and recognize related contents in a cross-sectional manner from among increasing works.

In order to resolve these problems, it is believed that such system is necessary for users capable of finding out animations corresponding to their preference easily, to recognize what kind of constituent elements of animation they prefer, and to enhance their interest in related contents. In this paper, "AniReco" is proposed which is an animation work recommendation system capable of recommending animation works and their related contents in a cross sectional fashion while reflecting users' potential preference.

System Overview

AniReco is a recommendation system via visualization using a network diagram based on calculation of user's preference from history of watching works and evaluation for them by using information regarding constituent elements of animation works. General outline of the system is shown in Fig. 1. (A) is a screen to display recommended works. User is represented by the center of the network spread in a radial fashion, and the closer to the center is a work located the higher is the rank of recommendation of the work. (B) is a screen to display information of works and related contents as well as to enter evaluation. User profile is updated and contents of recommendation vary when users watch animation works and evaluate them.

With a recommendation approach by content-based filtering adopted, the system has defined similarity and association between animations using a vector space model expressing metadata of each animation by n-hot vector in reference to [START_REF] Fleischman | Recommenda-tions without user preferences: a natural language pro-cessing approach[END_REF]. Users are able to recognize recommendation rank of each work visually and intuitively by suggestion of recommendation using a network diagram as described above. In addition, low diversity of content-based filtering recommendation has been resolved because even works with low recommendation rank are available as selection candidates. An evaluation experiment was performed to examine usability and recommendation accuracy of AniReco. The experiment was performed for 13 subjects aged from 22 to 28 (male: 11, female: 2) for two weeks (14days). Contents of the questionnaire and the results are shown in Table .1 and Fig. 2, respectively. Evaluation method of the questionnaire was five-level Likert scale.

From a result that scores in all questions (Q1~Q4) regarding system usability were more than middle score 3, it has been proved that the system tends to be easier to search works with better usability. In consideration of such an opinion that "it is easyto-grasp because it focuses only on proximity in addition to high visual exploratory performance ", recommendation suggesting method using a network diagram may be said to be suitable for recognition of difference in recommendation rank and exploration of works. In addition to descriptions suggesting resolution of selection from large number of animation works which is a background of the study such as "it's useful because it was difficult to determine which animation was interesting due to large number of animations", an effect to enhance animation watching were also suggested by opinions such as "recommendation provides an opportunity to watch animations," and "it is possible to encounter unknown works." Q5 ~ Q8 are questions regarding content of recommendation. From a result of Q5 and Q7, it is understood that no recommendation of works has been made which is greatly departed from user's preference. such a trend is recognized from Q7 and Q8 that recommendation with novelty and serendipity has been made reflecting potential preference of users. In addition, it is understood from Fig. 3 that some of works with high evaluation obtained from many subjects include animations in genres which have not been recognized by them to be preferable in advance. From those mentioned above, it has been suggested that the system is capable of recommending both preferences which users have and have not recognized in both subjective and objective evaluations.

Result of Q9 with a score greatly lower than middle score 3 indicates that the system has less effect to enhance interest in related contents of works such as goods and sacred places. The reason why is believed that presentation of related contents information just with animation works information had less effect to draw attention to related contents.

Conclusion

With a problem presentation that it has become difficult to find out animation works corresponding to individual preference from among tremendously increased works as well as to recognize expanding related contents in a cross-sectional manner in recent years, an animation work recommendation system "AniReco"has been proposed which reflects users' potential preference. Consequently, recommendation presenting method using a network diagram has obtained a high evaluation in system usability clarifying that the system has an effect to reduce burden for animation works exploration and leads to new discovery of works as well. In addition, it has been proved that the system is possibly capable of making recommendation of animation works reflecting not only users' known preference but also potential one by preference extraction using frequency of watching of works and evaluation for the works.

Fig. 1 .

 1 Fig. 1. System view and system configuration

Fig. 2 .

 2 Fig. 2. Analysis of high-rated works and favorite genres. No. is subjects' number.

Table . 1. Questionnaire

 .

					a
		Questionnaire	mean	sd		Questionnaire	mean	sd
	About the system usabitity			Q6	Among the recommended	4.46	0.52
	Q1	Was AniReco easy to use?	3.54	0.66		works, did you have works
	Q2	Was the network diagram	3.54	0.88		you did not know?
		easier to find the work?			Q7	Among the recommended	3.77	0.60
	Q3	Compared to searching on the	4.15	0.90		works, did you have favorite
		internet, is it easy to find				works you did not know?
		favorite works?			Q8	Among	the	constituent	3.39	1.56
	Q4	Do you want to continue	4.23	0.83		elements of works you never
		using this system in the				thought of it as favorites, did
		future?				you have anything favorite
	About the content of recommendation			newly?
	Q5 Among the recommended	3.77	0.83	Q9	Were you interested in the	1.85	1.14
		works, did you have favorite				suggested	goods	and
		works you have watched?				pilgrimages?


Teguh Budianto

Hyunwoo Oh

Yi Ding

Zi Long

Takehito Utsuro
email: utsuro@iit.tsukuba.ac.jp

Identifying Rush Strategies Employed in StarCraft II Using Support Vector Machines

Keywords: Real-Time Strategy Game, StarCraft II, Rush Strategy

This paper studies the strategies used in StarCraft II, a realtime strategy game (RTS) wherein two sides fight against each other in a battlefield context. We propose an approach which automatically classifies StarCraft II game-log collections into rush and non-rush strategies using a support vector machine (SVM). To achieve this, three types of features are evaluated: (i) the upper bound of variance in time series for the numbers of workers, (ii) the upper bound of the numbers of workers at a specific time, and (iii) the lower bound of the start time for building the second base. Thus, by evaluating these features, we obtain the optimal parameters combinations.

Introduction

Real-time strategy (RTS) games make up a popular on line computer game genre wherein two sides fight against each other in a battlefield context. The players are required to gather specific resources to develop their combat strengths in the form of advanced buildings, technologies, and armies. Unlike other strategy games such as Go and Chess wherein complete information on the state of play is provided to both players, information in RTS games is limited and rapidly changes as the player's resources respond to various factors. Moreover, RTS game environments are formed from complex and dynamic sets of information depending on the actions taken by the players. These characteristics contribute to the game's difficulty level and prevent the improvement of RTSbased AI technologies. In this paper, the strategies employed in StarCraft II, a well-known RTS game, are analyzed. These strategies form the most important aspect of competing with opponent's playing styles in order to ultimately win the game. Liu et al. [START_REF] Liu | Player identification from RTS game replays[END_REF] investigated the player's styles to predict their future actions. This type of analysis can aid human players to judge opponent's strategies and accordingly decide a defense strategy. An incorrect strategy judgment about an opponent's game plan and the resultant poor choice of action in Star-Craft II leads to the selection of an inappropriate defense strategy which harms the player's strength. Thus, strategy identification in RTS games has become a prominent research area, including strategy prediction and strategy modeling. Studies focusing on strategy prediction also employ data mining techniques [START_REF] Weber | A data mining approach to strategy prediction[END_REF] and machine-learning approaches [START_REF] Park | Prediction of early stage opponents strategy for StarCraft AI using scouting and machine learning[END_REF]. Improvements in strategy identification contribute to the advancement of RTS-game-based AI in order to discover the most effective strategies that human players can employ depending on their opponent's plan of action.

Considering these factors, this paper examines the strategies used in Star-Craft II by classifying them into two main categories: rush and non-rush strategies. A rush strategy involves players that perform sudden attacks on an opponent's base as early as possible in the game. This strategy aims to interfere with the opponent's movements at the early stages of the game. Conversely, in a non-rush strategy, the players mainly focus on development (i.e., producing more workers and upgrading technologies) rather than attacking the opponent base. Therefore, to examine the strategies of the players, we designed a support vector machine (SVM)-based model that automatically classifies StarCraft II game logs into rush and non-rush strategies.

Game-Log Features and the Evaluation Procedure

We collected 5,150 one-vs.-one game replays of StarCraft II from http://www. spawningtool.com. All replay files were extracted into human-readable logs using a Python library: sc2reader1 . Our study only focuses on the games between high-level players. This produced 753 game logs wherein each sample comprises a single player's game log, as summarized in Table 1.

We propose several types of features that are closely related to the number of workers each player has in a rush game. In particular, a major difference tends to exist between the number of workers on both sides. Generally, a player not employing rush strategy continues producing a much higher number of workers since the beginning of the game, while a player adopting a rush strategy produces only a moderate number of workers and stops production at a particular time. Thus, by considering these phenomena, we designed features based on the variance between the time-series number of workers and the number of workers at a specific time. We use the information about the number of workers a player has produced up until a certain time. The reason for this is because players cannot have a complete control over the number of workers each player possess at a certain time. In addition, we examine time required for constructing the second base (a building for collecting resources) in order to further design our features. We observe the differences in the timing of construction of the second bases of both players. Players employing a rush strategy do not necessarily build their second base as early as possible; however, it is expected that these players build their second base before a certain time. Based on the above observation, we propose three types of features: f vw , f nw , and f b (Table 2).

In our proposed feature-based design, the parameter combinations of the three feature functions were examined to determine the optimal parameter combinations. For f vw , the parameter combinations were examined by changing v 0 from 0 to 2, d 0 from 60 to 300, and e 0 from 240 to 360. For f nw , the parameter combinations were examined by changing t 0 from 300 to 600 and n 0 from 25 to 40. Finally, for f b , the parameter combination was examined by changing t 0 from 60 to 360. We first divided our data set into 10 subsets of equal size to perform 10-fold cross validation. From the training data of each fold, the optimal parameters combinations of each three feature functions f vw , f nw , and f b were identified from the combinations possessing maximum recall, precision, and f-measure. Based on this procedure, each feature function generated three optimal parameter combinations in total resulting in nine optimal parameter combinations for each fold. Next, we created and implemented a feature vector constructed from these nine features. Each features represents a parameter of a set of optimal parameter combinations. Our design eventually resulted in 10 different sets of optimal parameter combinations, which we used to train the SVM classifier.

Evaluation of Results

We used the confidence in SVM to calculate the performance of each fold of our approach using recall and precision. Further, we generated the average performance curve of our approach, as shown in Figure 1. The curves use 11 points plotted from 0 to 100 in order to display the average performance. We generalized the recall value of each fold to the closest position among these 11 points. Each of the three baseline curves was produced by removing each set of optimal parameter combinations of the three feature functions from the evaluation.

Fig. 1. Recall and precision curve of the overall design

Removing f nw from the evaluation degraded its baseline performance. Probably, this occurred because the differences between the number of workers at a specific time has a significant impact on a rush game. Considering the overall performance, the F-score of the proposed design shows the highest value among all three baselines. Thus, considering the above, we found that there is a significant correlation between the optimal parameter combinations of the three features functions. This indicates that the proposed design incorporating all the combinations worked better than the design considering each combination separately. Therefore, the proposed design could possibly be effective in identifying the use of rush strategies in RTS game-logs-collections.

Table 1 .

 1 Data set for evaluation

	Logs	Number of game logs
	Rush strategy	137
	Non-rush strategy	616
	Total logs	753

Table 2 .

 2 Features of a game log x

	Features		Variables of x
	Upper bound of the variance of time-series num-	x.f v vw Variance of x
	ber of workers	x.f d vw Time for calculating
	fvw(x; u0, d0, e0) =		variance [s]
	(x.f v vw ≤ u0) ∧ (x.f d vw = d0) ∧ (x.f e vw = e0)	x.f e vw End time of calculating
			variance [s]
	Upper bound of number of workers at a specific time fnw(x; t0, n0) = (x.f t nw = t0)∧(x.f n nw ≤ n0)	x.f t nw Specific time [s] x.f n nw Number of workers
	Lower bound of the start time of second base construction f b (x; t0) = (x.f t b ≥ t0)	x.f t b	Start time of second base construction [s]

https://github.com/GraylinKim/sc2reader

Conclusions

This study proposed a method to identify the rush and non-rush strategies employed by players from RTS game logs. We examined nine optimal parameter combinations of the three feature functions f vw , f nw , and f b . These combinations along with an SVM were used as the basis for constructing the features that could accurately identify a player's use of a rush strategy.


Minkyu Choi
email: choi.minkyu@entcomp.esys.tsukuba.ac.jp

Junichi Hoshino
email: jhoshino@esys.tsukuba.ac.jp

Karaoke Entertainment Character Based on User Behavior Recognition

Keywords:

In recent years, research on CG technology has advanced. However, the current CG character can only perform deterministic behavior; there is a problem that interaction cannot be real. Therefore, it is necessary to change the facial expression and gaze in real time to the user by the CG character to select a specific user in the space where there are multiple users, and to do real interaction with the user by using the episode control system and user recognition. In this paper, Kinect V2 recognizes the behavior of a specific user from multiple users, generates a complex gesture of CG characters, gaze representation etc., and proposes a system that CG character supports the provision of services. In this paper, we verify behavior recognition when there is one user and verify behavior recognition by priority when there are multiple users. Because there were many misrecognition of the skeleton, there were many times when the behavior was not recognized. In the evaluation experiments, we will realize even CG character's behavior generation in relation to episode control technology.

Introduction

Karaoke is an entertainment that only the musical accompaniment of each song is recorded, and users sing along with the accompaniment when it's played. In Japan, 'karaoke boxes' that provide karaoke became popular in 1980's, and ever since, they have been widely used for friends' gatherings, social occasions, and 'after-drink parties' as well as stress release purposes. In 2015, there are over 150,000 karaoke places and the market size of the karaoke boxes is said to be about 400 million yen. Karaoke is also widely popular in Asia, America, and in Europe, and there is the World Grand Prix of karaoke held as well. It is also impacting the music industry as popularities of songs in Karaoke influences the sales of CDs and downloads as well. A typical karaoke room in Japan normally has a large monitor that displays promotion videos or image videos of songs and devices to select songs. As users input songs they would like to sing, it will play them in turn. Sometimes, it has scoring system to judge how good they sang their songs, or video recording system that records them singing and post it on SNS. However, there is a room for improvement, in terms of some gismos to entertain the user, or pick up his/her preferences and make recommendations of songs and services.

This article proposes an entertainment character that, when multiple users are using at a karaoke room, recognizes the behaviors of the users to entertain them accordingly, and promote songs and food & drink services to them.

Entertainment Character for Karaoke Room

Fig. 1 shows a scene in a karaoke room. A CG character as a companion is displayed on the large monitor. Also, on the table is a small monitor for selecting songs. The character talks with voice to the users, and the users are to select answers displayed on the monitor. During the conversations, the character picks up your preferences, promotes songs and also recommends some foods and drinks as well as other services.

Fig. 1. Scene in a karaoke room and system architecture

In this system, the character recognizes users' behaviors such as singing, dancing and selecting songs, and it would sing along together, help you select songs and such. In this way, the character can avoid doing improper things such as talking to users when they are singing, and it can talk to you in appropriate timing. The judging of the character is done according to the priority degree shown in Table 1, using the results of state recognition on users, by selecting action module, in which some behavior or contents of talks are recorded. When someone is looking sideways, and is not paying attention to the singer, the character talks to motivate him/her to participate. Or, when users are enjoying karaoke, the character would also join them and take behaviors to entertain them such as singing, or clapping its hands. When no one is singing and they are selecting songs, it would recommend some songs, talk about itself, chat about random things based on the news of the day or it would recommend other services.

Table 1. User Behavior and priority

As a method to recognize users's behaviors, as there are many irregular lights such varying lighting and light from monitors, it uses RGB-D camera that can obtain images of certain distances to record users, and obtain their framework information such as bodies and limbs (Fig. 2). For extraction of framework information, the kinect library was used. By matching with preliminarily recorded postures and behavior patterns of users, it recognizes users' behaviors. Fig. 2 shows an example of extracting framework information. As shown here, it is capable of detecting basic postures of users in karaoke scenes.

Fig. 2. RGB-D image

Preliminary Evaluation

In this chapter, how the system recognizes users' behaviors and how the judgment of the character is made that were mentioned in chapter 2 were verified by an experiment.

1) Recognition of single user's behavior and the behavior generation by the character It was verified, when a behavior of a user is recognized, whether the character was able to generate an anticipated behavior. Table 2 shows the rate of correct recognition when one behavior was showed 10 times. It was able to recognize behaviors from (A) to (D) mostly. However, the recognition rate was down for (E) choosing a song, as the monitor for selecting songs blocked the user's lower body, making it difficult to judge whether the user was sitting or standing.

2) Recognition of two users' behaviors and behavior generation by the character It was verified whether the character could choose appropriate behavior according to the priority degree of the behavior when there are two users. For instance, each of the two users took behaviors of (A) and (B), (A) is to be selected as its priority is higher. Table 3 shows, when one pattern of behavior was showed 10 times, the anticipated behaviors of the character and actual behaviors it generated. In many cases, anticipated behavior was generated, but when two users overwrapped each other and part of their bodies were blocked, recognition errors tended to occur. For instance, when a user was not paying attention to the singer as in (A), if part of her body was not visible, it was recognized that the user was merely stand-by state.

Table 2. Accuracy of user recognition

Table 3. Recognition result of behavior by priority

As explained, the recognition capability of RGB-D camera was mostly stable, but recognition errors tended to occur when part of users' bodies were blocked by an object or other users. In such cases, the character would generate unexpected behaviors, and this should be examined in actual karaoke scenes, how disturbing they would be.

Conclusion

This article proposed an entertainment character that, in a karaoke room where one or multiple users are singing, recognizes users' behaviors and entertains them in karaoke. For the future projects, the recognition ability and contents of its conversations of the character should be improved by creating a mock karaoke room where users are actually engaged in karaoke to observe whether the reactions of the character are appropriate, and whether it can entertain the users.


Haiku Generator

Vinicius Carvalho Pereira
email: viniciuscarpe@gmail.com

Cristiano Maciel

A Literary Analysis of Poems Automatically Produced by

Keywords: literature and new technologies, text generators, computer-based poetry, Peter's Haiku Generator

The development of computer technologies gives rise to a revolution in all socio-cultural practices, including arts and literature. In terms of poetry, for example, readers have now access to new lyrical experiences either through emerging poetic genres or through so-far unimagined approaches to traditional ones. Lots of research has been done in the field of Computer Science on technical issues of computer-generated poetry, but little on the aesthetic impacts of having poems produced by machines. Therefore, we herein propose a multidisciplinary literary analysis of poems produced by the tool Peter's Haiku Generator, in order to discuss how software design decisions can affect literary aspects and the aesthetic effects of those poems.

Introduction

The development of computer technologies gives rise to a revolution in socio-cultural practices, including arts and literature. Along with a subversion of the literary system, in which the roles of authors and readers become blurry, in a prosumer paradigm (Kim et al [START_REF] Kim | On social Web sites[END_REF] , the materiality of poetic works is also altered, since the digital and the printed media develop increasingly distinct aesthetic resources. Analyzing the research area of entertainment computing in industry and academy, Nakatsu and Rauterberg [START_REF] Nakatsu | Entertainment computing: inaugural editorial[END_REF] highlight "art and entertainment" as one of the seven active working groups in TC14 (Entertainment Computing) by IFIP, where an interdisciplinary approach is highly desired. The printing press revolutionized the literary art of the Modern Age, providing it with agile circulation and effective reproducibility. The emergence of the novel as a longer literary genre, due to the invention press, is one of the most noticeable effects of how technology influences much more than the contents of a literary text. McLuhan [START_REF] Mcluhan | Os meios de comunicação como extensões do homem[END_REF] agrees with that in his most famous quoting: "the medium is the message".

Likewise, the new information and communication technologies radically affected the symbolic practices of our increasingly digital society, which is immersed in what Lévi [12] calls cyberculture. Like any other field, such paradigm affects also literature, which causes the emergence of new genres, some of which compose an exclusively virtual poetics. That is the case of computer-generated poetry (grouped under the wider term "Generative Literature"), which consists of poems produced by automatic recombination of elements of different granularity, following algorithms that consider natural language processing. To Zhang and Lapata [START_REF] Zhang | Chinese Poetry Generation with Recurrent Neural Networks[END_REF], automated poetry generation has been a popular research topic over past decades, but we herein discuss how software design decisions can affect literary aspects and the aesthetic effects of those poems. To do so, we chose the tool Peter's Haiku Generator, among others available online, because the genres of poem it produces (haiku and tanka), in comparison to most poetic forms in the West, are very short and and rely on sometimes fragmented visual images, which are features easier to meet in passable quality by computer-generated poems. Besides, different from most other online haiku generators, this tool produces haiku in English, instead of Japanese, which makes it easier for a broader audience to follow the discussions herein presented.

This paper is structured as follows: after the introduction, we present in section 2 a brief theoretical discussion about generative literature and a review of related works about haiku generators. Section 3 presents an overview of Peter's Haiku Generator and a close reading of two of its poems. Section 4 contains the final remarks of the paper and is followed by the references section.

2

Algorithmic Literature: Computer-Generated Haiku

In the area of Literature Studies, research on computer-generated literature is still scarce, since the idea of machines producing poems deconstructs some of the most traditional understandings of poetry as an emotional expression that comes from inspiration. Therefore, before we move to a literary analysis of the poems generated by Peter's Haiku Generator, it is necessary to specify what notions of language and literature are at stake when discussing computer-generated poems. An analysis of literary texts generated by computers must be grounded in the assumption that language itself is an algorithmic phenomenon, as proposed in Structural Linguistics [START_REF] Saussure | Cours de linguistique générale[END_REF], Generative Grammar [START_REF] Chomsky | Language and Mind[END_REF] and Computational Linguistics [START_REF] Mitkov | The Oxford handbook of computational linguistics[END_REF]. According to those approaches, every language is formed by a grammar, that is, a set of associative and restrictive principles that command the selection and ordering of lexical items, similarly to the data a computer processes following combination rules [START_REF] Lutz | Stochastische text[END_REF]. Furthermore, as in the digital information cryptography into binary systems, every natural language also operates by means of opposite relations, according Saussure [START_REF] Saussure | Cours de linguistique générale[END_REF].

As to the definitions of literature herein adopted, Barthes [START_REF] Barthes | [END_REF] considered that literature is a cheating within language rules, thus deconstructing traditional forms of perception and representation. To do so, literature brings linguistic systems to limit situations, forcing new word associations that are possible according to language rules, but not commonly used in daily communication. Such understanding of literature supports the idea that a machine, equipped with the structures and the lexicon of a language, can form verses by combinatory rules, since it will operate within the limits imposed by language itself and coded by the software programmer. And, if the verses formed seem sometimes unfit, or even nonsensical, this does not make their aesthetic value null, since these awkward formations can be read as the cheatings within language argued for by Barthes. Considering that estrangement is a formalist category associated with literariness [START_REF] Jakobson | Linguística e comunicação[END_REF], an awkward verse produced by the machine could be read not only as an accidental malformation, but as a token of what makes a text literary: the capacity to make people think about language, denaturalizing the relationship between things and words. Besides, as computer-generated poems frequently lead to somewhat disjointed verses, it is important to highlight that Eco [START_REF] Eco | The open Work[END_REF] stated that semiosis comes not only from respecting, but also from disrespecting established codes, so there is meaning even in noise. This is why Manurung et al. stated that "poetry generation is different from traditional informative generation due to poetry's unity, which essentially means the satisfying of interdependent constraints on semantics, syntax and lexis." [START_REF] Mcluhan | Os meios de comunicação como extensões do homem[END_REF].

Accepting the hypothesis that texts randomly produced by machines can be poetic, Generative Literature must be read and analyzed considering the characteristics of this emerging genre, imposed by its enunciation format: instead of a poetic product whose full message is a logical product, coherent in its parts, as in more traditional literary texts, fragmentation is inherent to this virtual poetic.

Another problem that this genre poses to the traditional literary system has to do with authorship. Far beyond the death of the author professed by Barthes [START_REF] Barthes | A morte do autor[END_REF], who defended people should read texts ignoring authorial intention, Generative Literature goes further: it dissolves notions of authorship as understood in the area of Literature Studies. In summation, who is the author of a software-generated poem? The reader that unchains the poem's random composition by simply clicking a button? The software engineer who also wrote a text -the system code -, which allows the functioning and artistic operation of the machine? Or the author of the original verses recombined by the software, in the case of machines that work with this feedstock? Among other software programs of this kind, the group ALAMO (Atélier de Littérature Assistée par les Mathématiques et les Ordinateurs) developed the software Alexandrins au greffoir [START_REF] Pereira | The user's and the designer's role and the aesthetic experience of generative literature[END_REF], which forms sonnets from the random recombination of halves of alexandrine verses by famous French poets, such as Nerval, Valéry and Baudelaire.

The problem is that none of these agents knows the final poetic product before the automatic recombination happens. If authorship is decentralized among agents who do not know the final product of their work, it is because software-generated poems make language itself speak, minimizing the effects of authorial intention. Thus, what is poetic is the process through which the poems are generated, rather than each generated text itself, since each of them is nothing but one among countless combinations the machine could generate. Furthermore, they vanish forever by means of a single click if they are not saved in a separate file, in case some reader wants to perpetuate a poetic moment.

Whereas the romantic tradition and the 19th century criticism valued the image of the author as that of a person touched by inspiration, away from the common people and master of the meanings of his text, Generative Literature deconstructs all these parameters, leading us to re-think the act of writing itself. Compared to a text engineer, the poet is no longer someone who works guided by the muses' whispers, but an individual that operates linguistic (and computer-based) algorithms, aiming at an aesthetic effect. Surprised with a machine's random combinations, the system developer who created the algorithms becomes a common reader of the poems. And other readers who click the refresh button generate new poems, so they play a physical part in the poetic production, thus contributing as co-authors. But who is the writer and who is the reader then? Maybe, such aesthetic claims for a new paradigm: that of the wreader [START_REF] Hayles | Electronic Literature: What is it? V.1.0. Januay[END_REF].

Among different poetic genres that can be produced by automated text generators, haikus tend to have more effective aesthetic results in comparison to most poetic forms in the West, since haikus are very short and and rely on visual images, which are features easier to meet in passable quality by computer-generated poems. According to Obara, Tosa and Minoh [START_REF] Obara | Hitch haiku: an interactive generation system of haiku[END_REF], haiku is a "Japanese classical poem style with minimal length of 5-7-5 characters" and "it is a story that generates context -the shortest story in the world". In English, as in any other Indo-European languages, haikus are composed of three verses, with 5-7-5 syllables respectively.

Tools to produce software-generated poems are not new. The first of them, created by Theo Lutz in 1959 [START_REF] Lutz | Stochastische text[END_REF], did not allow any input from users. More recent tools, on the other hand, allow users to interact with the system, such as Hitch Haiku (2007 -25) and its developments [START_REF] Tosa | Hitch haiku: An interactive supporting system for composing haiku poem[END_REF] [START_REF] Wu | New hitch haiku: An interactive renku poem composition supporting tool applied for sightseeing navigation system[END_REF]; others use Word Associations Norms, such as Gaiku [START_REF] Netzer | Gaiku: Generating haiku with word associations norms[END_REF]. There are also systems that combine traditional poetry culture and mobile messaging technology, such as Poetry Mix-up [START_REF] Fernando | Poetry mix-up: a poetry generating system for cultural communication[END_REF] and others which use word occurrences in the WWW and grammar templates, as proposed by [START_REF] Rafal | Haiku generator that reads blogs and illustrates them with sounds and images[END_REF].

Recently, Hreskova and Machová [START_REF] Hruskova | Použitie transformačnej regresnej techniky pre dolovanie v údajoch[END_REF] carried out research comparing two different approaches to the automated generation of haiku poetry. Their first approach consists of evolutionary algorithms and human as a fitness function in the evolution. The second approach consists in generating poems based on haiku models that were extracted from haiku database. The goal is to create poems, considered by humans as understandable and with aesthetic value. In this research, when comparing poems generated by both systems, generating haiku poetry with poem models created better poems both in terms of form and content. According to the authors, one of the reasons is that it is easier to combine words than whole verses.

3

Peter's Haiku Generator and Two of its Poems

Peter's Haiku Generator is a system programmed in Flash that generates haikus and tankas automatically whenever a user clicks the refresh button. The system does so through a series of algorithms that rule the combination of words registered in its database. These words are categorized according to their parts of speech. The initial step taken by the software, after the user's click, is the random selection of a syntactic structure for each verse (there are 3 in a haiku, or 5 in a tanka). Although the software initially works with a predefined set of basic sentence patterns, those can also be enriched by the user, as long as he or she has some knowledge of Linguistics and Flash.

In linguistic terms, Howard opted for a generative model, where a structure called "simple sentence" can be divided into two substructures, called noun phrase and verb phrase, also breakable into even smaller substructures, and so on, until minimal non-breakable structures. Table 1 shows the basic syntactic structures and the respective substructures that can be employed by Peter's Haiku Generator. Brackets indicate that a certain substructure is optional, depending on the number of syllables of the selected words, so as to meet the requirements of 5-7-5 syllables per verse, respectively: After the random selection of the underlying syntactic structure, the system randomly selects words in its database to fill the previously defined syntactic substructures, which obey the standard English grammar. Furthermore, to warrant isotopies [START_REF] Greimas | Sémiotique; dictionnaire raisonné de la théorie du langage[END_REF], i.e., coherence produced by words with meanings from similar areas, the words in the database are tagged according to the semantic field to which they belong. Before clicking the refresh button, the user can choose the semantic field of the poem to be generated; he or she can also add new words to the database, in case he or she has some knowledge about programming in Flash. Finally, an algorithm related to the metrics of the verses is triggered: only verses with seven and five syllables are formed according to the traditional versification of haikus and tankas.

Such idiosyncrasies of the machine's "writing" process, if compared to the way how poems are traditionally produced also demand particular methods for literary analysis. For example, it is not possible to exhaustively read the whole poetic production generated by the software, as it is frequently done in researches on human poets and their writings. The only methodological option, so to speak, is to randomly generate some poems and make a close reading of them, which means disregarding elements like authorial intention, literary period, social context and other features frequently considered in literary analyses.

For the sake of the literary analysis herein proposed, we chose the semantic field noir in the interface and clicked the refresh button twelve times before we reached the haiku below transcribed: Yellow winds waste streets. Fear turns however heat turns. Tepid heaven burns. [START_REF] Howard | Peter's Haiku Generator[END_REF] The choice for that specific semantic field justifies the presence of words associated to the notions of destruction and suffering, such as waste, fear and burns. The same meaning is conveyed in the phonetic layer of the verses by the assonance (vowel repetition) of the central vowel followed by the voiced alveolar trill, in fear, turns, however and burns. In those words, the sound resonates in the mouth cavity with little movement of the lips and tongue; they are inert as the desolate landscape described in the haiku. Also regarding stylistic phonetics, the alliteration of the semivowel /w/ (produced by the gliding movement of the lips) suggests the waves of warm wind that ravage the images described in the poem.

A poem coldly written by a machine, and not by an inspired author, paradoxically describes a warm scene, both in the phonological and in the lexical layers, as seen in the phrase "tepid heaven burns". That paradox is analogue to the one that connects programming and random in the construction of a haiku by a machine. Another paradox is produced by the synesthesia in the phrase "yellow winds", which describes winds that sweep the images of the poem just like the electric currents that erase each new haiku when the user clicks the refresh button.

But how can one make a literary interpretation of software generated by a machine? If each haiku is only the fortuitous product of chance, is it pertinent to search for different layers of meaning in their reading? Eco [START_REF] Eco | Interpretação e superinterpretação[END_REF] defends a literary analysis based on the work's intention, rather than the author's intention or the reader's intention. According to that paradigm, every literary text is provided with an immanent intention and significance, which the analysis herein carried out tries to retrace.

Final Remarks

If Remington type-writers once revolutionized the way people write, today poetry generators revolutionize the way to understand writing itself: in generative literature, who writes? Who reads? What is the work of art: the software or the poem? In this sequence of questions, the definitions of literature and poetry are at stake, especially because the concepts of reader and writer do not really apply to generative literature.

Poems automatically produced by a machine require specific analytical procedures, which must understand poetry as a product of systems (both linguistic and computational ones) rather than inspiration. Therefore, we have opted for a close reading approach in this paper.

A new aesthetics paradigm is brought forth by generative literature, which requires new understandings of literature. In that context, some of the haikus produced by Peter's Haiku Generator can be read as metapoems, whose noise from awkward images is not a communication break. Rather than that, it is meaning formed by random word association, which should be read as the work's intention, and not as the author's.

Table 1 .

 1 parsing rules processed by Peter's Haiku Generator[START_REF] Howard | Peter's Haiku Generator[END_REF]

	Structures	Substructures
	<sentence>	<clause> [<linking word> <clause>]
	<clause>	[<gerund utterance>] <clause>
	<clause>	1. <noun phrase> [<adverb phrase>] <intransitive verb> [<preposition>
		<noun phrase>
		2. <noun phrase> <intransitive verb> [<preposition> <noun phrase>] [<ad-
		verb phrase>]
		3. [<adverb phrase>] <noun phrase> <intransitive verb> [<preposition>
		<noun phrase>]
		4. <noun phrase> <transitive verb phrase> <noun phrase>
	<noun phrase>	1. <definite article> [<adjective phrase>] <common noun>
		2. [<adjective phrase>] <noun>
		3. <indefinite article> [<adjective phrase>] <common singular noun>
	<gerund utterance>	1. [[<adverb phrase>] <gerund verb>
	<adverb phrase>	1. [<adverb>] <adverb>
	<transitive verb phrase>	1. [<adverb phrase>] <transitive verb>
	<adjective phrase>	1. <adjective> [" , "<adjective>]
	<adjective>	1. <adjective> [<adjective>]
		2. [<adverb>] <adjective>


Motoi Okuzono

Masahumi Muta
email: masafumi.muta@rakuten.com

Soh Masuko
email: so.masuko@rakuten.com

Hayaki Kawata
email: kawata.hayaki@entcomp.esys.tsukuba.ac.jp

Junichi Hoshino
email: jhoshino@esys.tsukuba.ac.jp

Partner Character Attracting Consumers to a Real Store

Keywords: Pertner character, O2O, Gamification

The diversification of personal tastes and the rapid increase in choices makes it difficult to select things that suits them. For service providers it is fixedly segmented like a conventional mass media It is becoming more difficult to provide advertisements and services to individuals. Because of these circumstances, it is requested that we can accurately acquire personal preferences and analyze them. On the other hand, attention is focused on O2O, which connects online actions to offline online shopping in real stores.We also use gaming which makes various elements of everyday life into a game, Measures have also been taken to immerse and positively tackle purchasing behavior. In the marketing field, it is said that narrative is important for inducing user's behavior. Therefore, in this research, we construct a partner character system based on scenario game and verify whether we can increase purchasing behavior in a real shop by making users engage in the system using scenarios and characters that can be friends with users.

Introduction

Interests in O2O are increasing. So far, they are used for promoting visits and purchasing activities at physical retail stores with email marketing and online campaigns; there are also initiatives to lead online members and internet visitors to stores and actual off-line purchasing behaviors. There are also measures being carried out to utilize gamification which turns various factors in everyday life into a form of game to draw in users and get them to proactively undertake purchasing behaviors. Moreover, in the field of marketing, having narrativity is considered important for inducing user actions [START_REF] Shankar | Understanding consumption: Contributions from a narrative perspective[END_REF]. Therefore in this study, a partner character system is constructed using a scenario based game, to verify whether purchasing behaviors at physical retail stores can be increased by heightening engagement of users with the system, utilizing a scenario and a character that can befriend users. In this system, preferences of users are checked using conversation based on scenarios, and scenarios are changed depending on actions or location information of users. For this study, bakery was chosen as target purchasing category.

System Overview

This system uses a character for its interface. l This character uses expressions of emotional feelings (delight, anger, sorrow and pleasure) as shown on Fig. 1 l Backgrounds change depending on the scenario scene l Texts are displayed at lower part of the screen, to make it feel as if the character is talking to users l Users have pseudo-conversations with the character by selecting choices that are presented

The responsibilities of this front end character are; l Controlling the story l Estimation of user model from interactions with users By using this front end character, the system renders a story and carries out dialogues with users. Three levels are set for the front end character depending on how engrossed a user becomes, and new stories develop as levels go up. Moreover, a character that resides on smartphones of users is used to accumulate knowledge about users, by continuously having dialogues with users. Users would convey their preferences through dialogues with the partner, as well as evaluating proposals from the character.

Fig. 1. Example of character expression

This system tries to lead to purchases at physical retail stores, by proposing buns that users would like. To that end, a questionnaire allowing multiple answers is carried out to 32 men and women, where favorite buns are selected out of 73 types of buns quoted from a corporate website [START_REF]Book of kind of breads | COOKTWON[END_REF] of a company that holds cooking classes on baking buns; and the results from this questionnaire are used to enable recommendation with a collaboration filter. When using this system for the first time, questions in Table 1 are asked by the front end character. The results from this and right or wrong of answers on quiz regarding buns that the front end character posed to users are utilized to specify buns that users would like, and based on data obtained from the aforementioned preliminary survey, collaboration filtering is carried out. As an engagement parameter of users to the system, a degree of closeness is implemented in this system. There are four levels in the degree of closeness including the initial stage, with several criteria for going up in the level. Criteria are; l Visit a bakery l Listen to trivia on buns l Provide correct answer on quiz relating to buns l Experience bakeries or buns that the system recommended l Give a high evaluation to the bakery or buns that the user experienced By going up in the level, events would proceed and the character will become friendlier in its manner of speaking to users, showing more expressions.

Evaluation Testing

Test subjects are 16 male students between the ages of 20 to 25 who are studying at University of Tsukuba. They are asked to spend a week using the system. Furthermore, while there are no rules set forth to enforce use of the system, allowing the system to use location information and to use push notification at 12:00 every day were mandatory. Test subjects were classified based on their degree of closeness with the character, and their average number of visits to physical retail stores was summarized in Table 2. The results showed that higher the degree of closeness, the more they tended to visit stores. Therefore this showed that the more users become closer with a character in a system with narrativity, the more they visit physical retail stores, which means leading to purchasing behaviors.

Conclusion

While it showed that higher degree of closeness resulted in attracting more customers to physical retail stores, a third of test subjects were at the initial state of closeness; therefore more contrivance is needed to heighten engagement with the system. Moreover, since the scope was limited to buns as subjects in this study, algorithm for the system to recommend buns to users had remained a simple collaborative filtering as well. In future, it would be good to collaborate with commercial facilities and such to create partner characters that span across several fields such as apparels, books and films. And as volume of contents being handled increases, creation of contents and store database that are currently being prepared manually will likely need to be automated, by collaborating with EC (electronic commerce) websites.

Fig. 2 .

 2 Fig. 2. Familiarity distribution and number of actual store visits for each subject