Facilitating Internet of Things on the Edge

The evolution of electronics and wireless technologies has entered a new era, the Internet of Things (IoT). Presently, IoT technologies influence the global market, bringing benefits in many areas, including healthcare, manufacturing, transportation, and entertainment. Modern IoT devices serve as a thin client with data processing performed in a remote computing node, such as a cloud server or a mobile edge compute unit. These computing units own significant resources that allow prompt data processing. The user experience for such an approach relies drastically on the availability and quality of the internet connection. In this case, if the internet connection is unavailable, the resulting operations of IoT applications can be completely disrupted. It is worth noting that emerging IoT applications are even more throughput demanding and latency-sensitive which makes communication networks a practical bottleneck for the service provisioning. This thesis aims to eliminate the limitations of wireless access, via the improvement of connectivity and throughput between the devices on the edge, as well as their network identification, which is fundamentally important for IoT service management. The introduction begins with a discussion on the emerging IoT applications and their demands. Subsequent chapters introduce scenarios of interest, describe the proposed solutions and provide selected performance evaluation results. Specifically, we start with research on the use of degraded memory chips for network identification of IoT devices as an alternative to conventional methods, such as IMEI; these methods are not vulnerable to tampering and cloning. Further, we introduce our contributions for improving connectivity and throughput among IoT devices on the edge in a case where the mobile network infrastructure is limited or totally unavailable. Finally, we conclude the introduction with a summary of the results achieved

Nano-Communication for Biomedical Applications: A Review on the State-of-the-Art From Physical Layers to Novel Networking Concepts

We review EM modeling of the human body, which is essential for in vivo wireless communication channel characterization; discuss EM wave propagation through human tissues; present the choice of operational frequencies based on current standards and examine their effects on communication system performance; discuss the challenges of in vivo antenna design, as the antenna is generally considered to be an integral part of the in vivo channel; review the propagation models for the in vivo wireless communication channel and discuss the main differences relative to the ex vivo channel; and address several open research problems and future research directions

Uav-assisted data collection in wireless sensor networks: A comprehensive survey

Wireless sensor networks (WSNs) are usually deployed to different areas of interest to sense phenomena, process sensed data, and take actions accordingly. The networks are integrated with many advanced technologies to be able to fulfill their tasks that is becoming more and more complicated. These networks tend to connect to multimedia networks and to process huge data over long distances. Due to the limited resources of static sensor nodes, WSNs need to cooperate with mobile robots such as unmanned ground vehicles (UGVs), or unmanned aerial vehicles (UAVs) in their developments. The mobile devices show their maneuverability, computational and energystorage abilities to support WSNs in multimedia networks. This paper addresses a comprehensive survey of almost scenarios utilizing UAVs and UGVs with strogly emphasising on UAVs for data collection in WSNs. Either UGVs or UAVs can collect data from static sensor nodes in the monitoring fields. UAVs can either work alone to collect data or can cooperate with other UAVs to increase their coverage in their working fields. Different techniques to support the UAVs are addressed in this survey. Communication links, control algorithms, network structures and different mechanisms are provided and compared. Energy consumption or transportation cost for such scenarios are considered. Opening issues and challenges are provided and suggested for the future developments

Characterisation of the In-vivo Terahertz Communication Channel within the Human Body Tissues for Future Nano-Communication Networks.

PhDBody centric communication has been extensively studied in the past for a range of frequencies, however the need to reduce the size of the devices makes nano-scale technologies attractive for future applications. This opens up opportunities of applying nano-devices made of the novel materials, like carbon nano tubes (CNT), graphene and etc., which operate at THz frequencies and probably inside human bodies. With a brief introduction of nano-communications and review of the state of the art, three main contributions have been demonstrated in this thesis to characterise nano-scale body-centric communication at THz band: • A novel channel model has been studied. The path loss values obtained from the simulation have been compared with an analytical model in order to verify the feasibility of the numerical analysis. On the basis of the path loss model and noise model, the channel capacity is also investigated. • A 3-D stratified skin model is built to investigate the wave propagation from the under-skin to skin surface and the influence of the rough interface between different skin layers is investigated by introducing two detailed skin models with different interfaces (i.e.,3-D sine function and 3-D sinc function). In addition, the effects of the inclusion of the sweat duct is also analysed and the results show great potential of the THz waves on sensing and communicating. • Since the data of dielectric properties for biological materials at THz band are quite scarce, in collaboration with the Blizard Institute, London, UK, different human tissues such as skin, blood, muscle and etc. are planned to be measured with the THz Time Domain Spectroscopy (THz-TDS) system at Queen Mary University of London to enrich the database of electromagnetic parameters at the band of interest. In this chapter, collagen, the main constitution of skin was i mainly studied. Meanwhile, the measured results are compared with the simulated ones with a good agreement. Finally, a plan for further research activities is presented, aiming at widening and deepening the present understanding of the THz body-centric nano-communication channel, thus providing a complete characterisation useful for the design of reliable and efficient body centric nano-networks. iiChina Scholarship Council Queen Mary University of Londo

Формирование профессиональных компетенций юриста

В статье рассматривается проблема формирования профессиональных компетенций юриста в рамках дисциплины «Профессиональные навыки юриста» в условиях игрового состязательного судебного процесса, различные формы организации учебной деятельности студентов, которые способствуют приобретению студентами новых знаний, закреплению коммуникативных умений и навыков публичных выступлений

Оценка точности восстановления координат при моделировании трехмерных объектов с использованием стереоизображений

Необходимость реконструкции трехмерных координат возникает в задачах распознавания, в которых требуется восстановить форму изображенного объекта. Один из способов решения задачи базируется на использовании модели системы технического зрения, описывающей формирование стереопары изображений. Параметры такой модели задаются матрицами преобразования однородных координат сцены. Для калибровки модели могут быть использованы тестовые стереоизображения, сделанные в разных ракурсах, для шести точек которых известны координаты соответствующих им точек сцены. Точность восстановления координат точек поверхности изображенного объекта (при условии удачного распознавания соответствующих им точек стереопары изображений) обуславливается, главным образом, точностью калибровки модели технического зрения. Оценка погрешностей позволяет построить тетраэдр, во внутренней области которого лежит точка поверхности трехмерного тела, соответствующая распознанной точке стереоизображения

Randomized Machine Learning: Statement, solution, applications

In this paper we propose a new machine learning concept called randomized machine learning, in which model parameters are assumed random and data are assumed to contain random errors. Distinction of this approach from “classical” machine learning is that optimal estimation deals with the probability density functions of random parameters and the “worst” probability density of random data errors. As the optimality criterion of estimation, randomized machine learning employs the generalized information entropy maximized on a set described by the system of empirical balances. We apply this approach to text classification and dynamic regression problems. The results illustrate capabilities of the approach