Main Track T. Baste, TU Eindhoven, NL O. Boncalo, U Pol Timisoara, RO G.-M. Callico, ULPGC, ES P. Carballo, ULPGC, ES R. Cavicchioli, U of Modena and Reggio Emilia, IT T. Chen, Colorado St., US A. Cilardo, U Naples, IT G. Danese, U Pavia, IT J. Dondo, UCLM, ES R. Drechsler, U Bremen, DE E. Ebeid, Aarhus U, DK A. Eltawil, U of California, Irvine, US J. Ferreira, U Porto, PT M. Figueroa, U Concepcion, CL W. Fornaciari, Politecnico of Milan, IT R. Giorgi, U of Siena, IT V. Goulart, U Kyushu, JP J. Haid, Infineon, AT A. Hemani, KTH, SE D. Houzet, U Grenoble IT, FR M. Hubner, RUB, DE G. Jacquemod, U Nice-Sophia, FR R. Jordans, TU Eindhoven, NL L. Jozwiak, TU Eindhoven, NL B. Juurlink, TU Berlin, DE K. Kent, U New Brunswick, CA P. Kitsos, U of Peloponnese, GR N. Konofaos, Aristotle U of Thessaloniki, GR Z. Kotasek, BUT in Brno, CZ H. Kubatova, CTU in Prague, CZ K. Kuchcinski, U Lund, SE S. Kumar, U Jonkoping, SE A. Lastovetsky, U Coll Dublin, IE J. Lee, U Chosun, KR F. Leporati, U Pavia, IT E. Martins, U Aveiro, PT J. Matos, U Porto, PT A. McEwan, U Leicester, UK S. Mosin, Vladimir State U, RU V. Muthukumar, U Nevada, US N. Nedjah, U Rio de Janeiro, BR H. Neto, UT Lisboa, PT S. Niar, U Valenciennes, FR D. Noguet, CEA, FR M. Novotny, CTU in Prague, CZ A. Nunez, ULPGC, ES
The ageing population of Europe is a concern for political decision makers and visions on how to deal with the issues are being debated. The issues raised concern elderly people, the age group 75-90 years, but not much thought is given the young elderly- the age groups 60-75 years-as the serious age-related problems are not visible among them. Nevertheless, pro-active preventive action programs among the young elderly could significantly reduce the problems society faces when people become elderly. We will address the issues with the ageing population from the perspective of digital wellness services that are designed, produced and offered over omnivore platforms on smart mobile phones and backed up by analytics tools over cloud services. The aim is to keep the young elderly healthy, active and independent when they reach the 75+ age group. In this research the digital wellness services are proposed as effective interventions to build wellness routines. The design of wellness services need to be done through co-creation with the young elderly, not for them.
In platform-driven markets, competitive advantage is derived from superior platform design and configurations. For this reason, platform owners strive to create unique and inimitable platform configurals to maintain and extend their competitiveness within network economies. To disentangle firm competition within platform-driven markets, we opted for the UK mobile payment market as our empirical setting. By embracing the theoretical lens of strategic groups and digital platforms, this study supplements prior research by deriving a taxonomy of platform-driven strategic groups that is grounded on competitive attributes of platform- driven markets; namely interfirm modularity and strategic linkages.
As mobile phones and tablets are in widespread use, the emergence of mobile channel is changing the way customers interact with financial institutions. In this research, we empirically examine how the use of mobile devices can improve customer informedness and affect customer behavior in financial transactions. We use a large-scale customer transaction data obtained from one of the largest commercial banks in the United States. Specifically, we investigate: (1) whether the use of mobile phones and tablets is associated with a higher level of customer informedness and demand for services; and (2) compared to customers that only transact through a PC, whether mobile phone and tablet users are less likely to incur overdraft and credit card penalty fees. This paper contributes new knowledge in omni-channel banking services by examining post-adoption customer behavioral changes using transaction-level observations. We also discuss insights for banks’ managers related to the design of new mobile channel, and strategic management of existing digital and physical channels.
Stored data is a critical component of any application. The stored data component of mobile applications (apps) presents special considerations. This paper examines the management of stored data for mobile apps. It identifies three types of mobile apps and describes the stored data characteristics of each type. It presents decision factors for selecting a data storage approach for a mobile app and the impact of the factors on the usability of the app. The paper surveys over 70 apps in a specific domain (that of walking the Camino de Santiago in Spain) to examine their data storage characteristics. Finally the paper presents a case study of the development of one app in this domain (eCamino). The paper concludes that in the domain examined the data storage approach selected for a mobile app depends on the characteristics of the situation in which the app will be used.
This study presents a model for studying the innovative capabilities of digital payment platforms in regards to open innovation integration and commercialization. We perceive digital platforms as layered modular IT artifacts, where platform governance and the configuration of platform layers impact the support for open innovation. The proposed model has been employed in a comparative case study between two digital payment platforms: Apple Pay and Google Wallet. The findings suggest that digital payment platforms make use of boundary resources to be highly integrative or integratable, which supports the intended conjoint commercialization efforts. Furthermore, the architectural design of digital platforms impacts the access to commercialization, resulting to an exclusion or inclusion strategy in accessing value opportunities. Our findings contribute to the open innovation and digital platform literature, by providing a deeper understanding how these digital platforms can be designed and configured to support open innovation.
Authentication and identification for mobile payment transactions is typically provided by the secure element. While the SIM-card has long been the only option for locating the secure element, recently alternatives emerged like embedding the secure element into the device or offering it through the cloud. This paper elicits factors that influence stakeholder preferences for these three technical options. Exploratory interviews suggest a wide range of decision-making factors. Our results show that besides the basic security and performance traits of the technical options, other factors can only be understood when framing based on concepts of multisided platforms. The case of secure elements for mobile payments represents a highly complex illustration of platform competition that takes place on three different levels of the technical architecture.
The omnipresent mobile networks, such as Wi-Fi, WLAN, and network provided by mobile operators, facilitate the whole world connected. Mobile technology users can access to the world with the networks, making them feel constant connection to others which predicts the perception of invasion. This study aims to explore the boundary condition of this relationship from two perspectives—individuals’ psychological needs and social norms. This study theorizes that psychological needs strengthen the effect of accessibility of omnipresent networks, while social norms weaken that effect. Data was collected from 223 employees with mobile technology usage in their work. The results support our justifications, and discussion and implications are also presented.
This paper examines the role of IT in developing collaborative consumption. We present a study of the multi-sided platform goCatch, which is widely recognized as a mobile application and digital disruptor in the Australian transport industry. From our investigation, we find that goCatch uses IT to create situational-based and object-based opportunities to enable collaborative consumption and in turn digital disruption to the incumbent industry. We also highlight the factors to consider in developing a mobile application to connect with customers, and serve as a viable competitive option for responding to competition. Such research is necessary in order to better understand how service providers extract business value from digital technologies to formulate new breakthrough strategies, design compelling new products and services, and transform management processes. Ongoing work will reveal how m-commerce service providers can extract business value from a collaborative consumption model.
Smartphones have penetrated our everyday lives. Novel technologies facilitate self-management of chronic diseases such as diabetes. However, not all the patients are motivated to use technologies to manage their chronic conditions. Patients depend on certain human values to self-manage their conditions and these values are not implicated in the technologies they use. In this research in progress study we draw on value sensitive design methodological and theoretical approach to investigate human responses to self-management technology. We collect app reviews for a diabetes app and schematically code the review. Our findings contribute to designing technologies and systems that account for the human values of the patients-users.
Numerous digital payment solutions, which rely on new disruptive technologies, have been launched on the payment market in the recent years. But despite the growing number of mobile payment apps, very few solutions turn to be successful as the majority of them fail to gain a critical mass of users. In this paper we investigate two successful digital payment solutions in order to outline some of the factors which contribute to the widespread adoption of a digital payment platform. In order to conduct our analysis we propose the Reach and Range Framework for Multi-Sided Platforms. Our study indicates that the success of digital payment platforms lies with the ability of the platform to balance the reach (number of participants) and the range (features and functionalities) of the platform.
Understanding adoption patterns of smartphones is of vital importance to telecommunication managers in today’s highly dynamic mobile markets. In this paper, we leverage the network structure and specific position of each individual in the social network to account for and measure the potential heterogeneous role of peer influence in the adoption of the iPhone 3G. We introduce the idea of coreperiphery as a meso-level organizational principle to study the social network, which complements the use of centrality measures derived from either global network properties (macro-level) or from each individual's local social neighbourhood (micro-level). Using millions of call detailed records from a mobile network operator in one country for a period of eleven months, we identify overlapping social communities as well as core and periphery individuals in the network. Our empirical analysis shows that core users exert more influence on periphery users than vice versa. Our findings provide important insights to help identify influential members in the social network, which is potentially useful to design optimal targeting strategies to improve current network-based marketing practices.
Tongue diagnosis is an important method in TCM. Teeth marks are objective indexes of the diagnosis of qi deficiency. One method on teeth marks recognition is based on detecting the size of concave regions. The concave regions are caused by the bending of the tip and margin of the tongue, and the lip shades are easy to be misjudged into teeth marks. The pose and asymmetry of the tongue body also affect the judgment. Another method to identify teeth marks is to calculate concavity and convexity of the margin of the tongue. The narrow and long concave regions whose concavity is not deep are easy to be misjudged into teeth marks. Accordingly, this paper proposed a new method to extract teeth marks by calculating the slope of the margin of the tongue and the length and degree of the concave regions. Experimental results demonstrate the effectiveness of the method.
Rectus femoris (RF) has long been known to be susceptible to injuries, especially in population occupationally required to stretch quadriceps forcefully. Among various RF injuries, those involve strains about the central tendon (CT) of RF are found to cost longer recovery interval than other sites. To look into the contraction pattern of RF quantitatively, we start with sonography study of CT during isometric knee extensions. Nine healthy male adults participated the experiments. The tilt angle of CT (TACT) was calculated manually. Inter-frame velocity field were computed using a Primal-Dual method. Captured at 25 Hz, totally 1920 sonograms were included in the experiments. TACT and the averaged velocity (AV) demonstrated interesting patterns in ramp increasing/ decreasing phases, compared to piece-wise quasi-linear torque signal. TACT appears sensitive to knee extension during the starting and ending phases only, which imply that during the starting and ending of torque output, CT experiences more dramatic changes of force from it two sides. The preliminary results of TACT and AV could be helpful for understanding of RF injuries during fast quadriceps stretch.
The color images produced by digital cameras are usually not in conformity with their inherent colors. This will seriously impact computer-aided facial image analysis because it is on the basis of accurate rendering of color information. To solve that, we propose a novel color correction framework. Firstly, we utilize 122 undistorted facial images to demarcate complexion gamut. Secondly, several training sets based on complexion gamut are compared experimentally for the selection of optimal training samples. Thirdly, we select an adaptive target device-independent color space for our facial images color correction task. Finally, we evaluate the performance of three most popular color correction algorithms in color science area, and select the most suitable one to build our final regression model. Compared with the previous work, our color correction framework is characterized by mission dependence and statistical reliability. Besides, its trained model has low complexity and high accuracy. All of these features make it effective for facial images color correction.
This paper proposes a novel framework for iris image processing based on conformal geometric algebra (CGA) and Markov random field (MRF). Texture complexity and individual differences are two unique features of iris image, which bring many difficulties to automatic analysis and diagnosis. We propose a circle detection algorithm based on CGA for iris image segmentation. The algorithm is simple and has a wide scope of application. What's more, it can detect the inside and outside boundaries of iris simultaneously without any denoising. Then we propose a novel scheme for texture representation of iris image based on MRF. By learning the statistical texture differences of different pathological features, such as holes, cracks, a MRF based texture representation method shows different pathological regions in iris. Experimental results demonstrated that the proposed framework is very practical, provides a great help for subsequent diagnosis as well.
Pulse signal contains important information about health status and pulse diagnosis has been extensively applied in oriental medicine. In recent years more and more research interests have been given on computerized pulse diagnosis. Pulse feature extraction plays an important role in computerized pulse diagnosis. The most popular pulse feature extraction methods can be grouped into two categories, i.e. time domain feature extraction method and frequency domain feature extraction method. The pulse signal is a pseudo periodic signal while the common feature extraction methods usually assume it is a periodic signal and only a typical period or an averaged period was used in the feature extraction, while the difference between periods was less emphasized. In this paper we use complex network to transform the pulse signal from time domain to network domain and use the statistics parameters which describe the organization of the complex network as the features to characterize the difference between pulse periods. The experiment shows that the complex network features are useful in characterizing the relationship between different pulse periods the diagnosis performance on diabetes are similar with the multi scale sample entropy. By combining complex network features with sample entropy features, higher diagnosis performance can be further obtained.
In this paper we propose a method to distinguish Healthy and Disease individuals through tongue image analysis, specifically via tongue geometry features with Sparse Representation Classifier (SRC). After a tongue is captured using our non-invasive device, it is first segmented to remove its background pixels. Thirteen geometry features based on areas, measurements, distances, and their ratios are then extracted from the tongue foreground pixels. These features then form two sub-dictionaries in the SRC process, a Healthy geometry feature sub-dictionary, and Disease geometry feature sub-dictionary. Experimental results are conducted on a dataset consisting of 130 Healthy and 130 Disease samples. Using all thirteen geometry features SRC achieved a sensitivity of 86.15%, a specificity of 72.31%, and an average accuracy of 79.23% at Healthy vs. Disease classification.
In recent years, palm print identification technology has been widely carried out and used in fields such as identity recognition. At the same time, some features of palm vividly reveal information about diseases and health condition of the human body. We can research the application of palm diagnosis in traditional Chinese medicine with the help of digital image processing technology. In the palm diagnosis, palm print features and color features of visceral reflex regions are very important pathological features. Specific palm prints and color change of different reflex regions indicate different diseases. We want to take advantage of digital image processing technology to process palm images, in order to locate and segment the visceral reflex regions and extract certain palm print and color information, helping herbalist doctors diagnose diseases with palm diagnosis theory. This dissertation mainly focuses on approaches and methods of palm image pre-processing, prepared for further research and achieved certain results. The main work we have done is summarized as follows: Research on image acquisition conditions, median filtering, image binaryzation, binary image optimization, palm extraction, palm edge extraction and corner detection.
