Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

Rural telecommunications policy reform

This publication summarises the issues and points to possible changes in rural telecommunications policy. The purpose was not to revisit the usual arguments about the cost of the universal service obligation, or the comparison between metropolitan areas and remote areas. It simply aims to draw together clear thinking about the issues, in the hope of a better outcome for users and providers of telecommunications

Technologies and solutions for location-based services in smart cities: past, present, and future

Location-based services (LBS) in smart cities have drastically altered the way cities operate, giving a new dimension to the life of citizens. LBS rely on location of a device, where proximity estimation remains at its core. The applications of LBS range from social networking and marketing to vehicle-toeverything communications. In many of these applications, there is an increasing need and trend to learn the physical distance between nearby devices. This paper elaborates upon the current needs of proximity estimation in LBS and compares them against the available Localization and Proximity (LP) finding technologies (LP technologies in short). These technologies are compared for their accuracies and performance based on various different parameters, including latency, energy consumption, security, complexity, and throughput. Hereafter, a classification of these technologies, based on various different smart city applications, is presented. Finally, we discuss some emerging LP technologies that enable proximity estimation in LBS and present some future research areas

Security and Privacy Issues in Cloud Computing

Cloud computing transforming the way of information technology (IT) for consuming and managing, promising improving cost efficiencies, accelerate innovations, faster time-to-market and the ability to scale applications on demand (Leighton, 2009). According to Gartner, while the hype grew ex-ponentially during 2008 and continued since, it is clear that there is a major shift towards the cloud computing model and that the benefits may be substantial (Gartner Hype-Cycle, 2012). However, as the shape of the cloud computing is emerging and developing rapidly both conceptually and in reality, the legal/contractual, economic, service quality, interoperability, security and privacy issues still pose significant challenges. In this chapter, we describe various service and deployment models of cloud computing and identify major challenges. In particular, we discuss three critical challenges: regulatory, security and privacy issues in cloud computing. Some solutions to mitigate these challenges are also proposed along with a brief presentation on the future trends in cloud computing deployment

Provisioning Quality of Service of Wireless Telemedicine for E-Health Services: A Review

In general, on-line medical consultation reduces time required for medical consultation and induces improvement in the quality and efficiency of healthcare services. The scope of study includes several key features of present day e-health applications such as X-ray, ECG, video, diagnosis images and other common applications. Moreover, the provision of Quality of Service (QoS) in terms of specific medical care services in e-health, the priority set for e-health services and the support of QoS in wireless networks and techniques or methods aimed at IEEE 802.11 to secure the provision of QoS has been assessed as well. In e-health, medical services in remote places which include rustic healthcare centres, ships, ambulances and home healthcare services can be supported through the applications of e-health services such as medical databases, electronic health data and the transferring of text, video, sound and images. Given this, a proposal has been made for a multiple service wireless networking with multiple sets of priorities. In relation to the terms of an acceptable QoS level by the customers of e-health services, prioritization is an important criterion in a multi-traffic network. The requirement for QoS in medical networking of wireless broadband has paved the way for bandwidth prerequisites and the live transmission or real-time medical applications. The proposed wireless network is capable of handling medical applications for both normal and life-threatening conditions as characterized by the level of emergencies. In addition, the allocation of bandwidth and the system that controls admittance designed based on IEEE 802.16 especially for e-health services or wireless telemedicine will be discussed in this study. It has been concluded that under busy traffic conditions, the proposed architecture can used as a feasible and reliable infrastructure network for telemedicine

Anomaly Identification Model for Telecom Users Based on Machine Learning Model Fusion

With the development of economic globalization and modern information and communication technology, the situation of communication fraud is becoming more and more serious. How to identify fraudulent calls accurately and effectively has become an urgent task in current telecommunications operations. Affected by the sample set and the current state of the art, the current machine learning methods used to identify the imbalanced distribution dataset of positive and negative samples have low recognition accuracy. Therefore, in this paper, we propose a new hybrid model solution that uses feature construction, feature selection and imbalanced classes handling. A stacking model fusion algorithm composed of a two-layer stacking framework with several state-of-the-art machine learning classifiers is adopted. The results show that the risk user identification model based on mobile network communication behavior established by our stacking model fusion algorithm can accurately predict the category labels of telecom users and improve the risk of telecom users. The generalization performance of the identification is high, which provides a certain reference for the telecommunications industry to identify risk users based on mobile network communication behaviors