Supporting Collaborative Privacy-Observant Information Sharing Using RFID-Tagged Objects

RFID technology provides an economically feasible means to embed computing and communication capabilities in numerous physical objects around us, thereby allowing anyone to effortlessly announce and expose varieties of information anywhere at any time. As the technology is increasingly used in everyday environments, there is a heightening tension in the design and shaping of social boundaries in the digitally enhanced real world. Our experiments of RFID-triggered information sharing have identified usability, deployment, and privacy issues of physically based information systems. We discuss awareness issues and cognitive costs in regulating RFID-triggered information flows and propose a framework for privacy-observant RFID applications. The proposed framework supports users' in situ privacy boundary control by allowing users to (1) see how their information is socially disclosed and viewed by others, (2) dynamically negotiate their privacy boundaries, and (3) automate certain information disclosure processes

Survey of smart parking systems

The large number of vehicles constantly seeking access to congested areas in cities means that finding a public parking place is often difficult and causes problems for drivers and citizens alike. In this context, strategies that guide vehicles from one point to another, looking for the most optimal path, are needed. Most contributions in the literature are routing strategies that take into account different criteria to select the optimal route required to find a parking space. This paper aims to identify the types of smart parking systems (SPS) that are available today, as well as investigate the kinds of vehicle detection techniques (VDT) they have and the algorithms or other methods they employ, in order to analyze where the development of these systems is at today. To do this, a survey of 274 publications from January 2012 to December 2019 was conducted. The survey considered four principal features: SPS types reported in the literature, the kinds of VDT used in these SPS, the algorithms or methods they implement, and the stage of development at which they are. Based on a search and extraction of results methodology, this work was able to effectively obtain the current state of the research area. In addition, the exhaustive study of the studies analyzed allowed for a discussion to be established concerning the main difficulties, as well as the gaps and open problems detected for the SPS. The results shown in this study may provide a base for future research on the subject.Fil: Diaz Ogás, Mathias Gabriel. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Fabregat Gesa, Ramon. Universidad de Girona; EspañaFil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

An Occupancy Based Cyber-Physical System Design for Intelligent Building Automation

Cyber-physical system (CPS) includes the class of Intelligent Building Automation System (IBAS) which increasingly utilizes advanced technologies for long term stability, economy, longevity, and user comfort. However, there are diverse issues associated with wireless interconnection of the sensors, controllers, and power consuming physical end devices. In this paper, a novel architecture of CPS for wireless networked IBAS with priority-based access mechanism is proposed for zones in a large building with dynamically varying occupancy. Priority status of zones based on occupancy is determined using fuzzy inference engine. Nondominated Sorting Genetic Algorithm-II (NSGA-II) is used to solve the optimization problem involving conflicting demands of minimizing total energy consumption and maximizing occupant comfort levels in building. An algorithm is proposed for power scheduling in sensor nodes to reduce their energy consumption. Wi-Fi with Elimination-Yield Nonpreemptive Multiple Access (EY-NPMA) scheme is used for assigning priority among nodes for wireless channel access. Controller design techniques are also proposed for ensuring the stability of the closed loop control of IBAS in the presence of packet dropouts due to unreliable network links

Advances in Grid Computing

This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems

Development of computer vision algorithms using J2ME for mobile phone applications.

This thesis describes research on the use of Java to develop cross-platform computer vision applications for mobile phones with integrated cameras. The particular area of research that we are interested in is Mobile Augmented Reality (AR). Currently there is no computer vision library which can be used for mobile Augmented Reality using the J2ME platform. This thesis introduces the structure of our J2ME computer vision library and describes the implementation of algorithms in our library. We also present several sample applications on J2ME enabled mobile phones and report on experiments conducted to evaluate the compatibility, portability and efficiency of the implemented algorithms

Biosignal controlled recommendation in entertainment systems

With the explosive growth of the entertainment contents and the ubiquitous access of them via fixed or mobile computing devices, recommendation systems become essential tools to help the user to find the right entertainment at the right time and location. I envision that by integrating the bio signal input into the recommendation process, it will help the users not only to find interesting contents, but also to increase one’s comfort level by taking into account the biosginal feedback from the users. The goal of this project was to develop a biosignal controlled entertainment recommendation system that increases the user’s comfort level by reducing the level of stress. As the starting point, this project aims to contribute to the field of recommendation systems with two points. The first is the mechanism of embedding the biosignal non-intrusively into the recommendation process. The second is the strategy of the biosignal controlled recommendation to reduce stress. Heart rate controlled in-flight music recommendation is chosen as its application domain. The hypothesis of this application is that, the passenger's heart rate deviates from the normal due to unusual long haul flight cabin environment. By properly designing a music recommendation system to recommend heart rate controlled personalized music playlists to the passenger, the passengers' heart rate can be uplifted, down-lifted back to normal or kept within normal, thus their stress can be reduced. Four research questions have been formulated based on this hypothesis. After the literature study, the project went mainly through three phases: framework design, system implementation and user evaluation to answer these research questions. During the framework design phase, the heart rate was firstly modeled as the states of bradycardia, normal and tachycardia. The objective of the framework is that, if the user's heart rate is higher or lower than the normal heart rate, the system recommends a personalized music playlist accordingly to transfer the user’s heart rate back to normal, otherwise to keep it at normal. The adaptive framework integrates the concepts of context adaptive systems, user profiling, and the methods of using music to adjust the heart rate in a feedback control system. In the feedback loop, the playlists were composed using a Markov decision process. Yet, the framework allows the user to reject the recommendations and to manually select the favorite music items. During this process, the system logs the interactions between the user and the system for later learning the user’s latest music preferences. The designed framework was then implemented with platform independent software architecture. The architecture has five abstraction levels. The lowest resource level contains the music source, the heart rate sensors and the user profile information. The second layer is for resource management. In this layer are the manager components to manage the resources from the first layer and to modulate the access from upper layers to these resources. The third layer is the database, acting as a data repository. The fourth layer is for the adaptive control, which includes the user feedback log, the inference engine and the preference learning component. The top layer is the user interface. In this architecture, the layers and the components in the layers are loosely coupled, which ensures the flexibility. The implemented system was used in the user experiments to validate the hypothesis. The experiments simulated the long haul flights from Amsterdam to Shanghai with the same time schedule as the KLM flights. Twelve subjects were invited to participate in the experiments. Six were allocated to the controlled group and others were allocated to the treatment group. In addition to a normal entertainment system for the control group, the treatment group was also provided with the heart rate controlled music recommendation system. The experiments results validated the hypothesis and answered the research questions. The passenger's heart rate deviates from normal. In our user experiments, the passenger's heart rate was in the bradycardia state 24.6% of time and was in the tachycardia state 7.3% of time. The recommended uplifting music reduces the average bradycardia state duration from 14.78 seconds in the control group to 6.86 seconds in the treatment group. The recommended keeping music increases the average normal state duration from 24.66 seconds in the control group to 29.79 seconds in the treatment group. The recommended down-lifting music reduces the average tachycardia state duration from 13.89 seconds in the control group to 6.53 seconds in the treatment group. Compared to the control group, the stress of the treatment group has been reduced significantly

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

The reliability of rock mass classification systems as underground excavation support design tools

This thesis examines the reliability of rock mass classification systems available for underground excavation support design. These methods are sometimes preferred to rational methods of support design particularly if detailed information required for the latter mentioned methods is lacking. The classification approach requires no analysis of any specific failure mechanisms or the forces required to stabilise unstable rocks, yet, the support measures thus designed are considered to deal with all possible failure mechanisms in a rock mass.Amongst the several rock mass classification methods developed for application in underground excavation engineering, two have stood out. These are known as rock mass rating (RMR) and tunnelling quality index (Q), introduced by Bieniawski (1973) and Barton et al. (1974), respectively. Over the years, the two methods have been revised and updated so as to improve their reliability as support design tools, yet the two methods are know to have limitations and their reliability has long been a subject of considerable debate. Nevertheless, attempts to assess their reliability in a systematic manner have been limited. Further, some practitioners in the field of rock engineering continue to use these methods as the sole methods of support design for underground rock excavations. The objective of thesis, therefore, is to contribute to a better understanding of the reliability of the two classification methods.This study considered that the reliability of the RMR and Q methods can be assessed by comparing their support predictions with those derived by other applicable methods and also with the actual support installed. Such an assessment can best be carried out during excavation of an underground opening because representative data can be collected by direct observation of the as-excavated ground conditions and monitoring the performance of the support installed. In this context, the geotechnical data obtained during the construction of several case tunnels were reviewed and the two classification methods were applied. The effectiveness of their support predictions was then evaluated against the potential failures that can be predicted by some of the applicable rational methods. Since the rock masses intersected in the case tunnels are jointed, mostly the structurally controlled failure modes were analysed. The support measures predicted by the two methods were compared with each other and with the actual support installed in the case tunnels. Further, the RMR and Q vales assigned to the case tunnels were correlated to observe any relationship between the two.The study showed that the RMR and Q predicted support measures are not always compatible. In some circumstances, the two methods can either overestimate or under estimate support requirements