Ambient intelligence : European conference, AmI 2008, Nuremberg, Germany, November 19-22, 2008 : proceedings

No abstract

Ambient intelligence : European conference, AmI 2008, Nuremberg, Germany, November 19-22, 2008 : proceedings

No abstract

The survey on Near Field Communication

PubMed ID: 26057043Near Field Communication (NFC) is an emerging short-range wireless communication technology that offers great and varied promise in services such as payment, ticketing, gaming, crowd sourcing, voting, navigation, and many others. NFC technology enables the integration of services from a wide range of applications into one single smartphone. NFC technology has emerged recently, and consequently not much academic data are available yet, although the number of academic research studies carried out in the past two years has already surpassed the total number of the prior works combined. This paper presents the concept of NFC technology in a holistic approach from different perspectives, including hardware improvement and optimization, communication essentials and standards, applications, secure elements, privacy and security, usability analysis, and ecosystem and business issues. Further research opportunities in terms of the academic and business points of view are also explored and discussed at the end of each section. This comprehensive survey will be a valuable guide for researchers and academicians, as well as for business in the NFC technology and ecosystem.Publisher's Versio

Shaping technologies for older adults with and without dementia: Reflections on ethics and preferences

As a result of several years of European funding, progressive introduction of assistive technologies in our society has provided many researchers and companies with opportunities to develop new information and communication technologies aimed at overcoming the digital divide of those at a greater risk of being left behind, as can be the case with healthy older people and those developing cognitive decline and dementia. Moreover, in recent years, when considering how information and communication technologies have been integrated into older people’s lives, and how technology has influenced these individuals, doubts remain regarding whether technologies really fulfil older users’ needs and wishes and whether technologies developed specifically for older users necessarily protect and consider main ethical values. In this article, we address the relevance of privacy, vulnerability and preservation of autonomy as key factors when involving older individuals as target users for information and communication technology research and development. We provide explanatory examples on ethical issues involved in the particular case of developing different types of information and communication technology for older people (from robotics to serious games), what previously performed research tells us about older adults’ preferences and wishes for information and communication technology and what steps should be taken into consideration in the near future

Advanced Methods of Power Load Forecasting

This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used. On the other hand, multiple seasonal Holt-Winters models with discrete seasonality and the application of the Prophet method to demand forecasting are presented. These models are applied in different circumstances and show highly positive results. This reprint is intended for both researchers related to energy management and those related to forecasting, especially power load

Improving Electricity Distribution System State Estimation with AMR-Based Load Profiles

The ongoing battle against global warming is rapidly increasing the amount of renewable power generation, and smart solutions are needed to integrate these new generation units into the existing distribution systems. Smart grids answer this call by introducing intelligent ways of controlling the network and active resources connected to it. However, before the network can be controlled, the automation system must know what the node voltages and line currents defining the network state are.Distribution system state estimation (DSSE) is needed to find the most likely state of the network when the number and accuracy of measurements are limited. Typically, two types of measurements are used in DSSE: real-time measurements and pseudomeasurements. In recent years, finding cost-efficient ways to improve the DSSE accuracy has been a popular subject in the literature. While others have focused on optimizing the type, amount and location of real-time measurements, the main hypothesis of this thesis is that it is possible to enhance the DSSE accuracy by using interval measurements collected with automatic meter reading (AMR) to improve the load profiles used as pseudo-measurements.The work done in this thesis can be divided into three stages. In the first stage, methods for creating new AMR-based load profiles are studied. AMR measurements from thousands of customers are used to test and compare the different options for improving the load profiling accuracy. Different clustering algorithms are tested and a novel twostage clustering method for load profiling is developed. In the second stage, a DSSE algorithm suited for smart grid environment is developed. Simulations and real-life demonstrations are conducted to verify the accuracy and applicability of the developed state estimator. In the third and final stage, the AMR-based load profiling and DSSE are combined. Matlab simulations with real AMR data and a real distribution network model are made and the developed load profiles are compared with other commonly used pseudo-measurements.The results indicate that clustering is an efficient way to improve the load profiling accuracy. With the help of clustering, both the customer classification and customer class load profiles can be updated simultaneously. Several of the tested clustering algorithms were suited for clustering electricity customers, but the best results were achieved with a modified k-means algorithm. Results from the third stage simulations supported the main hypothesis that the new AMR-based load profiles improve the DSSE accuracy.The results presented in this thesis should motivate distribution system operators and other actors in the field of electricity distribution to utilize AMR data and clustering algorithms in load profiling. It improves not only the DSSE accuracy but also many other functions that rely on load flow calculation and need accurate load estimates or forecasts

Psychosocial support in emergency situations

In recent decades we have witnessed a growing number of major accidents and emergencies caused by natural hazards (floods, earthquakes, cyclones) and human factors (chemical and nuclear accidents, conflicts, terrorism). In such situations, people’s lives are fundamentally changed and accompanied by various social consequences: loss of loved ones, loss of control over one’s own life, loss of the sense of security, hope and initiative, social infrastructure, access to services and assets. Reactions may be various; shock, tears, anger, rage, a sense of hopelessness and an anxiety are just part of the whole range of unpleasant experiences. However, the intensity of the stress responses differs among individuals, but also communities, and thus the needs for interventions are different. The role of organizations dealing with the protection and rescue is to provide immediate assistance and protection, and also psychosocial assistance and support. The psychosocial support is the process of facilitating the recovery of individuals, family and communities from the effects of hazards and it plays a key role in the interventions at major accidents involving large number of victims. Psychosocial support means that in the approach to a person two dimensions are involved influencing each other mutually: psychological (inner, emotional and meditative processes, feelings and reactions of individual) and social (relationships with other people, family networks, social values and culture of the community). The third dimension involves the first responders. Stress can initiate the development of depression, depressive disorders, anxiety, professional burn-out, depersonalization, distress, emotional exhaustion and related mental health problems, as well as other indicators of psychological distress among members of rescue teams. Bearing in mind the importance of psychosocial programs of the nineties, their implementation is supported in many projects and it is proposed that the psychosocial care becomes an integral part of the emergency response of the public health care system

The appraisal of Facebook online community: An exposition of mobile commerce in social media reviews

Peer reviewe