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Über dieses Buch

This volume contains the proceedings of UIC 2009, the 6th International C- ference on Ubiquitous Intelligence and Computing: Building Smart Worlds in Real and Cyber Spaces. The UIC 2009 conference was technically co-sponsored by the IEEE and the IEEE Computer Society Technical Committee on Scalable Computing. The conference was also sponsored by the Australian Centre of - cellence in Information and Communication Technologies (NICTA). UIC 2009 was accompanied by six workshops on a variety of research challenges within the area of ubiquitous intelligence and computing. The conference was held in Brisbane, Australia, July 7–9, 2009. The event was the sixth meeting of this conference series. USW 2005 (First International Workshop on Ubiquitous Smart World), held in March 2005 in Taiwan, was the ?rst event in the series. This event was followed by UISW 2005 (Second International Symposium on Ubiquitous Intelligence and Smart Worlds) held in December 2005 in Japan. Since 2006, the conference has been held annually under the name UIC (International Conference on Ubiquitous Intelligence and Computing). UIC 2006 was held in September 2006 in Wuhan andThreeGorges,China,followedbyUIC2007heldinJuly2007inHongKong, and UIC 2008 held in June 2008 in Oslo, Norway. Ubiquitous sensors,computers, networksand informationare paving the way towardasmartworldinwhichcomputationalintelligenceisdistributedthrou- out the physical environment to provide reliable and relevant services to people.



Keynote Speeches

Distributed Computing in Opportunistic Environments

Opportunistic networks have evolved from mobile ad hoc networking and the delayed tolerant networking paradigms and have quickly gained popularity in research and industry. In opportunistic networking, when pairs of devices come within each others communication range, opportunistically, short-lived links (or opportunistic links) are created. Opportunistic computing exploits the opportunistic links created by pair-wise contacts, to share information content, resources and services, leading to a wide variety of applications. In this talk we discuss the research challenges and issues in exploiting opportunistic contacts to create a delay tolerant distributed computing environment. Further more, the impact of social computing and networking paradigms for such problems as synchronization and trust will be investigated. Results of ongoing research work on information dissemination, collaboration and trust will be presented. The research work is supported through an NSF grant.
Mohan Kumar

Web of Things as a Framework for Ubiquitous Intelligence and Computing

In the last few years the web has evolved from just being a source of information to a platform for business applications. In parallel to this, wireless sensor network technologies have evolved to a stage where they are capable of connecting to the web. This amalgamation of technologies referred to as “Web of Things”, has created new opportunities for intelligent application development. However, the "Web of Things" has brought interesting challenges like - efficiently utilizing online sensors, sensor composition for just in time application development and others that require urgent attention. In this paper, we propose a conceptual framework and reference architecture for embedding the notions of Ubiquitous Intelligence and Computing within the “Web of Things” and empowering their use in a broader context.
Tharam S. Dillon, Alex Talevski, Vidyasagar Potdar, Elizabeth Chang

Context Awareness

Inferring Human Interactions in Meetings: A Multimodal Approach

Social dynamics, such as human interaction is important for understanding how a conclusion was reached in a meeting and determining whether the meeting was well organized. In this paper, a multimodal approach is proposed to infer human semantic interactions in meeting discussions. The human interaction, such as proposing an idea, giving comments, expressing a positive opinion, etc., implies user role, attitude, or intention toward a topic. Our approach infers human interactions based on a variety of audiovisual and high-level features, e.g., gestures, attention, speech tone, speaking time, interaction occasion, and information about the previous interaction. Four different inference models including Support Vector Machine (SVM), Bayesian Net, Naïve Bayes, and Decision Tree are selected and compared in human interaction recognition. Our experimental results show that SVM outperforms other inference models, we can successfully infer human interactions with a recognition rate around 80%, and our multimodal approach achieves robust and reliable results by leveraging on the characteristics of each single modality.
Zhiwen Yu, Zhiyong Yu, Yusa Ko, Xingshe Zhou, Yuichi Nakamura

Gesture Recognition with a 3-D Accelerometer

Gesture-based interaction, as a natural way for human-computer interaction, has a wide range of applications in ubiquitous computing environment. This paper presents an acceleration-based gesture recognition approach, called FDSVM (Frame-based Descriptor and multi-class SVM), which needs only a wearable 3-dimensional accelerometer. With FDSVM, firstly, the acceleration data of a gesture is collected and represented by a frame-based descriptor, to extract the discriminative information. Then a SVM-based multi-class gesture classifier is built for recognition in the nonlinear gesture feature space. Extensive experimental results on a data set with 3360 gesture samples of 12 gestures over weeks demonstrate that the proposed FDSVM approach significantly outperforms other four methods: DTW, Naïve Bayes, C4.5 and HMM. In the user-dependent case, FDSVM achieves the recognition rate of 99.38% for the 4 direction gestures and 95.21% for all the 12 gestures. In the user-independent case, it obtains the recognition rate of 98.93% for 4 gestures and 89.29% for 12 gestures. Compared to other accelerometer-based gesture recognition approaches reported in literature FDSVM gives the best resulrs for both user-dependent and user-independent cases.
Jiahui Wu, Gang Pan, Daqing Zhang, Guande Qi, Shijian Li

Context-Aware Activity Recognition through a Combination of Ontological and Statistical Reasoning

In the last years, techniques for activity recognition have attracted increasing attention. Among many applications, a special interest is in the pervasive e-Health domain where automatic activity recognition is used in rehabilitation systems, chronic disease management, monitoring of the elderly, as well as in personal well being applications. Research in this field has mainly adopted techniques based on supervised learning algorithms to recognize activities based on contextual conditions (e.g., location, surrounding environment, used objects) and data retrieved from body-worn sensors. Since these systems rely on a sufficiently large amount of training data which is hard to collect, scalability with respect to the number of considered activities and contextual data is a major issue. In this paper, we propose the use of ontologies and ontological reasoning combined with statistical inferencing to address this problem. Our technique relies on the use of semantic relationships that express the feasibility of performing a given activity in a given context. The proposed technique neither increases the obtrusiveness of the statistical activity recognition system, nor introduces significant computational overhead to real-time activity recognition. The results of extensive experiments with data collected from sensors worn by a group of volunteers performing activities both indoor and outdoor show the superiority of the combined technique with respect to a solely statistical approach. To the best of our knowledge, this is the first work that systematically investigates the integration of statistical and ontological reasoning for activity recognition.
Daniele Riboni, Claudio Bettini

Context-Aware Path Planning in Ubiquitous Network

A ubiquitous network aims to provide users intelligent human-centric context-aware services at anytime anywhere. Path planning in a ubiquitous network considers users’ needs and surrounding context to plan the best path which is very different from that of car navigation or mobile robot research currently available. In this paper, we propose a context-aware path planning mechanism based on spatial conceptual map (SCM) and genetic algorithm (GA), referred to as UbiPaPaGo. SCM model is adopted to represent the real map of the surrounding environment. GA is a robust heuristic algorithm that devotes to UbiPaPaGo to plan the optimal path. The goal of UbiPaPaGo is to automatically find the best-fitting path that satisfies multiple requirements of individual user. A prototype of the UbiPaPaGo has been implemented to show its feasibility. Our numerical results also indicate that the proposed UbiPaPaGo is very efficient.
Chiung-Ying Wang, Ren-Hung Hwang

Middleware and Services

An Efficient Approach to Situation-Aware Service Discovery in Pervasive Service Computing Environments

Service discovery, which is an important required function for service-based systems (SBS), affects the performance of SBS, especially in pervasive service computing environments. In this paper, an efficient approach to service discovery in multi-hop pervasive service computing environments is presented. This approach is situation-aware and based on group-based service discovery protocol. In a pervasive computing environment, the situation, including available service resources, users’ preferences and the physical environment, changes more dynamically. Our service discovery approach exploits the network asymmetry and incorporates situational information while keeping low network overhead. Our simulation results show that our approach discovers services efficiently.
Stephen S. Yau, Gautam G. Pohare

Printing in Ubiquitous Computing Environments

Document printing has long been considered an indispensable part of the workspace. While this process is considered trivial and simple for environments where resources are ample (e.g. desktop computers connected to printers within a corporate network), it becomes complicated when applied in a mobile context. Contemporary mobile devices have the computational resources required for document processing and are affordable enough for an increasingly large number of users. Therefore, document printing using mobile devices is now both technically feasible and relevant to users’ needs. In this study, we present an infrastructure for document printing using mobile devices. In order to realize the vision, we utilize an existing set of network protocols, a set of common programming languages, standard concepts of ubiquitous computing, and machine learning, in order to automate the printing process.
Athanasios Karapantelakis, Alisa Devlic, Mohammad Zarify, Saltanat Khamit

The Å Publish/Subscribe Framework

This paper describes the design and implementation of a novel decentralized publish/subscribe framework. The primary goal of the design was for a high level of end-developer and user accessibility and simplicity. Furthermore, it was desired to have strong support for occasionally-connected clients and support for mobile and web-based systems. Content-based event patterns can be defined using scripts, with many common script languages supported. Script-based, stateful event patterns permit rich expressiveness, simplify client development and reduce network usage. The framework also offers event persistence, caching and publisher quenching. We also describe a number of applications already built on the framework, for example publishers to support location and presence awareness and ambient visualizations of financial data.
Clint Heyer

Mining and Visualizing Mobile Social Network Based on Bayesian Probabilistic Model

Social networking has provided powerful new ways to find people, organize groups, and share information. Recently, the potential functionalities of the ubiquitous infrastructure let users form a mobile social network (MSN) which is discriminative against the previous social networks based on the Internet. Since a mobile phone is used in a much wider range of situations and is carried by the user at all times, it easily collects personal information and can be customized to fit the user’s preference. In this paper, we presented MSN mining model which estimates the social contexts like closeness and relationship from uncertain phone logs using a Bayesian network. The mining results were then used for recommending callees or representing the state of social relationships. We have implemented the phonebook application that displays the contexts as network or graph style, and have performed a subjectivity test. As a result, we have confirmed that the visualizing of the MSN is useful as an interface for social networking services.
Jun-Ki Min, Su-Hyung Jang, Sung-Bae Cho

Routing and Sensor Networks

SMSR: A Scalable Multipath Source Routing Protocol for Wireless Sensor Networks

In wireless sensor networks (WSNs), providing resilience (fault tolerance) is a challenging issue. A lot of multipath routing protocols, therefore, have been proposed to achieve the goal; however, they usually suffer from control message overhead or a lack of scalability. Although some protocols utilize partially disjoint paths or longer alternate paths in order to reduce such overhead, they cannot guarantee resilience, because a single failure on a shared node breaks all the paths. In this paper, we therefore propose a scalable multipath source routing (SMSR) protocol. In SMSR, a sink node collects each sensor node’s one-hop upstream neighbor information during an initialization phase which the sink node then uses in order to construct several shortest node-disjoint downstream (sink-to-sensor) paths. When transmitting downstream packets, the source routing technique is exploited. On the other hand, each sensor node forwards upstream (sensor-to-sink) packets to one of its upstream neighbors, through the concept of gradient-based routing. The initialization phase depends on only one-time flooding and n (network size) times unicasting, and each sensor node manages only one-hop upstream neighbor information. In this sense, SMSR is scalable in terms of the overhead and the size of routing tables in sensor nodes. Particularly, since SMSR provides several node-disjoint paths with low overhead, it can guarantee resilience efficiently. Through experiments using both ns-2 simulation and our real world test-bed, we verify that SMSR achieves the goal better than other existing routing protocols.
Sutaek Oh, Dongkyun Kim, Hyunwoo Kang, Hong-Jong Jeong

A Framework to Calibrate a MEMS Sensor Network

The Smart Surface project aims at designing an integrated micro-manipulator based on an array of micromodules connected with a 2D array topology network. Each micromodule comprises a sensor, an actuator and a processing unit. One of the aims of the processing unit is to differentiate the shape of the part that is put on top of the Smart Surface. From a set of shapes this differentiation is done through a distributed algorithm that we call a criterion. The article presents Sensor Network Calibrator (SNC), a calibrator which allows to parametrize the Smart Surface and to determine the necessary number of sensors required by our Smart Surface. The tests will show that SNC is of great importance for choosing the number of sensors, and therefore to determine the size of the sensors grid.
Kahina Boutoustous, Eugen Dedu, Julien Bourgeois

Application Domain Driven Data Visualisation Framework for Wireless Sensor Networks

Wireless sensor networks (WSNs) have an intrinsic interdependency with the environments in which they operate. The part of the world with which an application is concerned is defined as that application’s domain. This paper advocates that an application domain of a WSN application can serve as a supplement to analysis, interpretation, and visualisation methods and tools. We believe it is critical to elevate the capabilities of the visualisation service, the mapping service, proposed in [1] to make use of the special characteristics of an application domain. In this paper, we propose an adaptive Multi-Dimensional Application Domain-driven (M-DAD) visualisation framework that is suitable for visualising an arbitrary number of sense modalities and other parameters of the application domain to improve the visualisation performance. M-DAD starts with an initial user defined model that is maintained and updated throughout the network lifetime. The experimental results demonstrate that M-DAD visualisation framework performs as well or better than visualisation services without its extended capabilities.
Mohammad Hammoudeh, Robert Newman, Christopher Dennett, Sarah Mount

Hybrid Bluetooth Scatternet Routing

A Bluetooth® scatternet is a Wireless Personal Area Network (WPAN) formed by inter-connecting piconets using cross-over nodes called bridges. In order for arbitrary nodes to be able to communicate in a scatternet they must be able to discover each other, sometimes without knowing the peer device’s identity, and establish routes. Traditionally, routing in wireless ad-hoc networks is done using either a proactive, reactive, or a hybrid approach. In this paper, we present a hybrid solution with a dual meaning. We use a hybrid zone routing approach, but also perform route discovery based on either a destination address or a service. The proactive part of the protocol establishes an Extended Scatternet Neighborhood (ESN) with a complete view of adjacent, directly connected, piconets. The reactive part utilizes a route discovery mechanism and establishes inter-piconet modified source routes. The route request dissemination, for both destination and service-based route discovery, is performed using a probabilistic gossiping strategy to reduce routing load.
Karl E. Persson, D. Manivannan

Ubiquitous Networks and Devices

Self-estimation of Neighborhood Density for Mobile Wireless Nodes

In this paper, we propose a method to estimate the density of nodes for pedestrians and/or vehicles with information terminals. The method enables us to provide intelligent services which are environment-aware with highly dynamic movement of nodes such as intellectual navigation that tells the user the best route to detour congested regions. In the proposed method, each node is supposed to know its location roughly (i.e. within some error range) and to maintain a density map covering its surroundings. This map is updated when a node receives a density map from a neighboring node. Also by estimating the change of the density, taking into account the movement characteristics of nodes, the density map is updated in a timely fashion. The simulation experiments have been conducted and the results have shown the accuracy of the estimated density maps.
Junji Hamada, Akira Uchiyama, Hirozumi Yamaguchi, Shinji Kusumoto, Teruo Higashino

MeshVision: An Adaptive Wireless Mesh Network Video Surveillance System

The major surveillance camera manufacturers have begun incorporating wireless networking functionality into their products to enable wireless access. However, the video feeds from such cameras can only be accessed within the transmission range of the cameras. These cameras must be connected to backbone infrastructure in order to access them from more than one hop away. This network infrastructure is both time-consuming and expensive to install, making it impractical in many rapid deployment situations (for example to provide temporary surveillance at a crime scene). To overcome this problem, we propose the MeshVision system that incorporates wireless mesh network functionality directly into the cameras. Video streams can be pulled from any camera within a network of MeshVision cameras, irrespective of how many hops away that camera is. To manage the trade-off between video stream quality and the number of video streams that could be concurrently accessed over the network, MeshVision uses a Bandwidth Adaptation Mechanism. This mechanism monitors the wireless network looking for drops in link quality or signs of congestion and adjusts the quality of existing video streams in order to reduce that congestion. A significant benefit of the approach is that it is low cost, requiring only a software upgrade of the cameras.
Peizhao Hu, Ryan Wishart, Jimmy Ti, Marius Portmann, Jadwiga Indulska

SDEC: A P2P Semantic Distance Embedding Based on Virtual Coordinate System

Large-scale P2P applications can benefit from the ability to predict semantic distances to other peers without having to contact them first. In this paper, we propose a novel semantic distance embedding approach, SDEC, in P2P network, which assigns synthetic coordinates to peers such that the distance between the coordinates of two peers approximately predicts the semantic distance between any two peers. Specifically, the semantic distance between peers is quantitatively characterized through vector space model based on peers’ semantic profiles, and then, based on measured semantic distances from a peer to a handful of other peers and the current coordinates of those peers, we adopt the spring relaxation method, mimicking the physical mass-spring system, to simulate the semantic embedding procedure, which can find minimal energy configuration corresponding to relatively accurate semantic embedding. Simulation results show that a 3-dimensional Euclidean model can embed these peers with relatively high accuracy.
Yufeng Wang, Akihiro Nakao, Jianhua Ma

Dynamic Integration of Zigbee Devices into Residential Gateways for Ubiquitous Home Services

In recent years, Zigbee becomes one of the most promising protocols for ubiquitous networking. So, it would be essential that residential gateways can effectively interoperate with Zigbee-enabled ubiquitous devices such as wireless sensors and digital appliances to provide ubiquitous home services. In this paper, I design and implement an effective architecture for dynamic integration of Zigbee devices into OSGi-based residential gateways, where ad hoc Zigbee devices are represented as device proxy services. And such proxy services can be automatically downloaded, installed and registered to the OSGi service registry by the dynamic device integration manager on the corresponding devices’ joining the Zigbee network. Thus, ubiquitous home service applications can discover proxy services for the required Zigbee devices, and access the devices with the common proxy service interfaces without concerning the specific device access protocols and libraries.
Young-Guk Ha

Location-Based Services

Fine-Grained Evaluation of Local Positioning Systems for Specific Target Applications

Location-aware software has become widespread outdoors. Indoor applications are now on the rise. However, careful selection of the appropriate local positioning system (LPS) and application fine-tuning are required in order to guarantee acceptable user experience. We present a simulation-based approach that includes application characteristics, LPS characteristics, and building characteristics to this complex task and illustrate how the appropriate LPS can be chosen and how applications can be fine-tuned. A sophisticated indoor navigation system is used as sample application. The paper also provides insights into subtle details and caveats of different LPS technologies from an application and building viewpoint.
Erwin Aitenbichler, Fernando Lyardet, Aristotelis Hadjakos, Max Mühlhäuser

Indoor Positioning System Using Beacon Devices for Practical Pedestrian Navigation on Mobile Phone

In this paper, we propose a positioning system for indoor pedestrian navigation services using mobile phones. Position information services with a Global Positioning System (GPS) are widely used for car navigation and portable navigation. Their navigation systems facilitate development of industry and increase the convenience of civil life. However, such systems and services are available only for locations in which satellite signals can be received because users’ self-positions are computed using GPS. Therefore, we developed a system for indoor environments, operating with a user’s mobile terminal and battery-driven beacon devices in a server-less environment. Moreover, to provide convenient services using position information indoors, we developed an indoor navigation system that is useful in commercial facilities and office buildings. The system consists of smart phone and license-free radio beacon devices that can be driven with little electric power. In our proposed method, probabilistic estimation algorithms are applied to estimate self-positions in indoor locations, such as those where it is impossible to receive GPS signals. Feature of the system is that 2.5-dimensional indoor positioning is possible to calculate with low computational power device such as mobile phone. The system works autonomously, i.e., the user’s device receives wireless beacon signals from the surrounding environment and can thereby detect a user’s position independently from the mobile terminal, thereby obviating server-side computation.
Yutaka Inoue, Akio Sashima, Koichi Kurumatani

NavTag: An Inter-Working Framework Based on Tags for Symbolic Location Coordinates for Smart Spaces

Location information and sensor networks are key ingredients in realizing smart spaces by customizing the behavior of the application according to users’ locations and by being able to sense and act upon the physical space. This paper presents a flexible interworking model for complex smart space environments, in which points of interest are represented as tags, while spatial representations are achieved by representing the physical space as a tag space encoding a quadtree. The mechanism is beneficial for reducing the modeling and maintenance costs of location in smart spaces, as well as providing a low entry barrier for integration with other information systems.
Vlad Stirbu

Mobile Web 2.0-Oriented Five Senses Multimedia Technology with LBS-Based Intelligent Agent

Ubiquitous-oriented realistic next generation mobile multimedia technology requires new approaches that sufficiently reflect human’s sensory information and mobile Web 2.0-oriented collective intelligence and social networking concepts. Hence, we suggest and implement enhanced user location-based five senses multimedia technology that realizes a collective intelligence and mobile social networking between multi-mobile users. This includes 1) mobile station-based mixed-web map module via mobile mash-up, 2) authoring module of location-based five senses multimedia contents using ubiquitous-oriented sensor network and WiBro(Mobile Wi-Max), and 3) LBS-oriented intelligent agent module that includes ontology-based five senses multimedia retrieval module, social network-based user detection interface and user-centric automatic five senses multimedia recommender interface.
Jung-Hyun Kim, Hyeong-Joon Kwon, Hyo-Haeng Lee, Kwang-Seok Hong

Security and Privacy

Conflicting-Set-Based Wormhole Attack Resistant Localization in Wireless Sensor Networks

The wormhole attack sniffs packets in one point in the network, tunnels them through a wired or wireless link to another point to cause severe influence on the localization process or routing process in the network. In this paper, we analyze the impact of the wormhole attack on the localization in wireless sensor networks and we propose a wormhole attack resistant secure localization scheme. The main idea of our proposed scheme is to build a so-called conflicting set for each locator based on the abnormalities of message exchanges among neighboring locators, and then to identify all dubious locators which are filtered out during localization. Our proposed scheme can identify the dubious locators with a very high probability to achieve secure localization. The simulation results show that it outperforms the existed schemes under different network parameters.
Honglong Chen, Wei Lou, Zhi Wang

Novel and Efficient Identity-Based Authenticated Key Agreement Protocols from Weil Pairings

It is often a challenging task to make a system satisfy desirable security properties and maintain a low computational overhead. In this paper, we attempt to minimize the gap for two identity-based key agreement protocols, in the sense that we allow our key agreement protocols to satisfy all general desirable security properties including master-key forward security and in the meanwhile achieve a good computational efficiency. Our protocols are novel, since we are able to make use of several nice algebraic properties of the Weil Pairing to outperform other state-of-the-art key agreement protocols. To our knowledge, our second protocol is the first identity-based protocol that provides master key forward security and satisfies all basic desirable security properties based on the key extraction algorithm due to Sakai and Kasahara.
Hua Guo, Yi Mu, Xiyong Zhang, Zhoujun Li

Implicit User Re-authentication for Mobile Devices

Portable computers are used to store and access sensitive information. They are frequently used in insecure locations with little or no physical protection, and are therefore susceptible to theft and unauthorized access. We propose an implicit user re-authentication system for portable computers that requires no application changes or hardware modifications. The proposed technique observes user-specific patterns in filesystem activity and network access to build models of normal behavior. These are used to distinguish between normal use and anomalous use. We describe these automated model generation and user detection techniques, and explain how to efficiently implement them in a wireless distributed system composed of servers and battery-powered portable devices. The proposed system is able to distinguish between normal use and attack with an accuracy of approximately 90% every 5 minutes and consumes less than 12% of a typical laptop battery in 24 hours.
Sausan Yazji, Xi Chen, Robert P. Dick, Peter Scheuermann

Lattice Based Privacy Negotiation Rule Generation for Context-Aware Service

Online privacy has consistently been a major concern for customers, growing commensurately with the growth of online commerce. Individuals often have serious concerns that their online activities are being monitored, which can prevent them from using online services. With this concern in view, service providers have started making their privacy policies more clear to customers. However, legacy systems often lack flexibility and the inability to adapt to user’s interests, which are often the main reasons for inappropriate agreement. Negotiation between the service provider and user can be a possible solution to reach an agreement which seems appealing and profitable to both parties. In this paper we have developed a negotiation mechanism using the concept lattice approach. Using concept lattices in a privacy policy makes it flexible and allows both the parties to sacrifice a few interests for mutual benefits and appropriate agreement.
Yonnim Lee, Debashis Sarangi, Ohbyung Kwon, Min-Yong Kim

Ubiquitous Intelligence

Using RFID to Overcome Inventory Control Challenges: A Proof of Concept

Using a Proof of Concept approach, this paper examines RFID’s impact on inventory control of a small-to-medium retailer. Results indicate that RFID technology can function effectively in a small-to-medium hardware environment. Also, the majority of the simulations recorded reasonable read rates even though the simulations were set up over a short period of time without a great deal of fine-tuning. Moreover, RFID could have a positive impact on the inventory-related processes of the organisation by either streamlining or formalizing them and facilitate the electronic storage of information captured in real-time, relating to the movement of stock and the amount of stock held, providing visibility to members of the organisation. Despite these encouraging findings in relation to using RFID for inventory control purposes within the small-to-medium retailer, it is recommended that other alternatives aimed at improving the inventory control practices of the organisation be investigated before committing to the implementation of RFID.
Dane Hamilton, Katina Michael, Samuel Fosso Wamba

Anticipative Wrap-Around Inquiry Method towards Efficient RFID Tag Identification

One of the challenges in designing modern RFID systems is that when more than one tag exists in an RFID environment, it may occurs collisions so that the whole system becomes inefficient and increases the time for identifying RFID Tags. To simultaneously recognize multiple tags within a reader interrogation zone, an anti-collision algorithm should be applied. In this paper, we present an Anticipative Wrap-Around Inquiry (AWAI) method, which is an enhanced technique based on the query tree protocol. The main idea of the Anticipative Inquiry is to limit number of collisions at different level of a query tree. When number of collisions reaches a predefined ratio, it reveals that density in RF field is too high. To avoid sending unnecessary inquiries, the prefix matching will be moved to next level, alleviating the collision problems. Since the prefix matching is performed in level-ordered scheme, it may cause an imbalanced query tree on which the right sub-tree was not examined due to threshold jumping. By scanning the query tree from right sub-tree to left sub-tree in alternative levels, i.e., wrap-around, this flaw could be significantly ameliorated. The experimental results show that the method of setting frequency bound and wrap-around scan indeed improve the identification efficiency in high density and randomly deployed RFID systems.
Ching-Hsien Hsu, Wei-Jau Chen, Yeh-Ching Chung

A Probabilistic Semantic Based Mixture Collaborative Filtering

Personalized recommendation techniques play more and more important roles for the explosively increasing of information nowadays. As a most popular recommendation approach, collaborative filtering (CF) obtains great success in practice. To overcome the inherent problems of CF, such as sparsity and scalability, we proposed a semantic based mixture CF in this paper. Our approach decomposes the original vector into semantic component and residual component, and then combines them together to implement recommendation. The semantic component can be extracted by topic model analysis and the residual component can be approximated by top values selected from the original vector respectively. Compared to the traditional CF, the proposed mixture approach has introduced semantic information and reduced dimensions without serious information missing owe to the complement of residual error. Experimental evaluation demonstrates that our approach can indeed provide better recommendations in both accuracy and efficiency.
Linkai Weng, Yaoxue Zhang, Yuezhi Zhou, Laurance T. Yang, Pengwei Tian, Ming Zhong


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