A Multidimensional Reputation Evaluation Model for Mobile Crowd Sensing

The participant's reputation is vital to improve the quality of service for Mobile Crowd Sensing (MCS). A multidimensional reputation evaluation model was proposed in this paper to evaluate the participant's reputation more objectively. Different from the existing strategies, the service delay and the count of the successful as well as the failed transactions were additionally utilized to evaluate the participant's reputation. An algorithm based on Analytic Hierarchical Process (AHP) was presented to establish the reputation evaluation weight matrix. Besides, a fuzzy logic based mechanism was proposed to normalize the value of the four criteria and a dual-threshold mechanism was designed to achieve admission control more properly. Finally, extensive simulations were conducted and the simulation results confirmed the effectiveness of the reputation evaluation model

Intersystem soft handover for converged DVB-H and UMTS networks

Digital video broadcasting for handhelds (DVB-H) is the standard for broadcasting Internet Protocol (IP) data services to mobile portable devices. To provide interactive services for DVB-H, the Universal Mobile Telecommunications System (UMTS) can be used as a terrestrial interaction channel for the unidirectional DVB-H network. The converged DVB-H and UMTS network can be used to address the congestion problems due to the limited multimedia channel accesses of the UMTS network. In the converged network, intersystem soft handover between DVB-H and UMTS is needed for an optimum radio resource allocation, which reduces network operation cost while providing the required quality of service. This paper deals with the intersystem soft handover between DVB-H and UMTS in such a converged network. The converged network structure is presented. A novel soft handover scheme is proposed and evaluated. After considering the network operation cost, the performance tradeoff between the network quality of service and the network operation cost for the intersystem soft handover in the converged network is modeled using a stochastic tree and analyzed using a numerical simulation. The results show that the proposed algorithm is feasible and has the potential to be used for implementation in the real environment

Development and validation of an instrument to measure user perceived service quality of mHealth

The role of service quality in fostering the growth of mHealth services has gained much attention in the academic and practitioner communities. However, empirical research in this area has been beset by inadequate conceptualization and the lack of a validated scale. This study addresses these limitations by theoretically conceptualizing and empirically validating a multidimensional service quality scale in the mHealth context. The findings show that mHealth service quality is a hierarchical, multidimensional, and reflective construct, which consists of three primary dimensions and eight subdimensions. The results also confirm that the mHealth service quality scale is more effective at predicting satisfaction and continuance in a nomological network

Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence

IEEE Access Volume 3, 2015, Article number 7217798, Pages 1512-1530 Open Access Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article) Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc a Department of Information Engineering, University of Padua, Padua, Italy b Department of General Psychology, University of Padua, Padua, Italy c IRCCS San Camillo Foundation, Venice-Lido, Italy View additional affiliations View references (107) Abstract In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network

EXPERIENTIAL VALUE: A HIERARCHICAL MODEL, THE IMPACT ON E-LOYALTY AND A CUSTOMER TYPOLOGY

The main objective of this study is to empirically test a fourth-order hierarchical model of experiential value in an online book and CD setting. In addition, we provide empirical evidence for the role of hedonic and utilitarian value components in creating attitudinal and behavioral loyalty. Finally, we develop an online customer typology, based on the underlying value sources. Based on a sample of 190 visitors of online book and CD retailers, we used PLS to test a third and fourth order hierarchical model of experiential value, emphasizing a hedonic (intrinsic) and utilitarian (extrinsic) value component and the existence of the holistic concept of experiential value. Our results demonstrate that experiential value consists of the third order components hedonic (intrinsic) and utilitarian (extrinsic) value. Both value aspects impact attitudinal loyalty ultimately leading to behavioral loyalty which is also directly affected by utilitarian value. Finally, a nonhierarchical (k-means) cluster analysis identified four segments of online visitors: hedonists, utilitarians, active negativists, and reactive positivists.marketing ;

Eliciting Customer Preferences for Shopping Companion Apps: A Service Quality Approach

Shopping companion apps, which assist customers in product search and buying decisions, are an emerging phenomenon in the context of omnichannel retail. These retailer-provided apps link the digital with the physical servicescape of the store, allowing for new forms of online and at the same time physical service. So far, there is no dominant design for this type of information system. Both academia and practice lack empirical information about what customers expect from this kind of mobile app. Drawing from service quality literature as theoretical foundation, we conducted a qualitative content analysis of 1,448 customer reviews of three major shopping companion apps. The analysis yielded 23 aspects that customers expect from shopping companion apps, and that, in turn, can support establishing high mobile service quality. Our results contribute to the knowledge of m-service in retail and quality-driven app design

Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices (wearables, home-medical sensors, etc) facilitates data collection and provide cloud storage with a central administration. More recently, blockchain and other distributed ledgers became available as alternative storage options based on decentralised organisation systems. We bring attention to the human data bleeding problem and argue that neither centralised nor decentralised system organisations are a magic bullet for data-driven innovation if individual, community and societal values are ignored. The motivation for this position paper is to elaborate on strategies to protect privacy as well as to encourage data sharing and support open data without requiring a complex access protocol for researchers. Our main contribution is to outline the design of a self-regulated Open Health Archive (OHA) system with focus on quality of life (QoL) data.Comment: DSS 2018: Data-Driven Self-Regulating System