Cognitive radio-based TV White Space (TVWS) is a promising idea which seeks to increase spectrum utilization by opportunistically accessing spectrum initially licensed to TV transmitters or incumbents. Orthogonal frequency multiple access (OFDM) is thought to be a promising technology for TVWS systems. In this paper, we consider an OFDM based cognitive High-Altitude Platform (HAP) exploiting the TVWS spectrum. We employ dynamic resource allocation for providing wireless access from a HAP at an altitude of 20km, while utilizing the TVWS spectrum. This paper focuses on the resource allocation algorithms, which are designed to increase the system transmission rate of secondary users while keeping the disturbance applied to the incumbent band below a threshold level and the overall power within a range using the Artificial Immune System Algorithm. As per the simulation demonstrated so far, the proposed algorithm outperforms the water-filling algorithm, implying that the system transmission rate is greatly optimized. Moreover, the proposed resource allocation algorithm allocates resources to users in a fair manner, without favoring any particular user, and has good convergence performance.

Successful maritime search and rescue (SAR) missions and real-time information exchange among first responder organizations (FRs) and command/coordination centers, fully rely on straightforward information flow and accurate communication channels, supported by novel data sharing technologies, advanced network connections, and interoperable platforms. Therefore, SAR actions at sea, as an integral part of the national maritime safety system, are supported with mission-critical communication (MCC) networks and devices. The paper presents the analysis of SAR operational and communication specifics, use cases and technical efficiency increasing in the maritime safety framework, with a focus on specific operational capabilities of MCC, connection networks, devices, and procedures for maritime distress communication. Further to MCC, the paper provides insight into the 5G network applied in maritime SAR and communications. The case study consists of an elaboration of the Mission Critical Communication platform components and X/BELLO tool, a secure 5G application that allows real-time information exchange, deployed under the RESPOND-A project approach. These systems represent the technical part of the SAR pilot of the EU RESPOND-A project showcasing the opportunities to strengthen the operational framework of maritime FRs and improve their joint mission performance.

The Internet of Things (IoT) will facilitate communications among multiple entities or Things to enable interaction among them in a more extensive manner with endless possibilities for collaboration. These Things will support operations in critical infrastructures, such as in health care. In this work we investigate the scenario of IoT deployment in hospitals to monitor and assist in-hospital patient care. We introduce the notion of trust grading of Things at both the individual and group level, to assess the trustworthiness of entities for patients' progress. Weights are assigned to different sensing nodes as a means of properly aggregating criteria for trust and mitigating associated risks for the patients. Based on the proposed methodology, a GUI is implemented that allows for the visualization of malicious or irregular IoT behavior, and the dynamic calculation of trustworthiness. This work aims to support existing work for Io T deployment in hospitals.

Several studies have focused on the different types of laboratories arising with the evolution of technology and their influence within all educational levels concerning Science, Technology, Engineering and Mathematics (STEM) Education. Augmented Reality (AR) is receiving increased attention and interest in recent years, within not only the commercial and the entertainment sectors, but also the educational field. In this paper, some current trends are identified after a brief overview of the state-of-the-art concerning Laboratory-based education. Moreover, challenges are discussed and potential future areas of research are identified. Finally, an outline of a methodology is suggested aiming to identify how the use of different types of labs may affect students' enrollment in STEM-related studies.

Many rural and low-income areas around the globe have poor quality (or no) internet service with limited telephone coverage due to a lack of infrastructure, insufficient power supply, and a limited core telecommunications network. Because of limited mobile device propagation capabilities, sparse population density and poor purchasing power, it is not economically feasible for mobile operators to deploy traditional communication networks in these regions. Researchers recently discovered that a portion of the underutilized TV spectrum known as TV white space (TVWS) could be suitable for those areas in terms of bandwidth, improved reception features, good penetration of buildings, and broad reach. This paper presents a comprehensive evaluation of available TVWS channels in Ethiopia using a Geolocation Database front-end (GLSD) aided by the CSIR Calculation Engine hosted by the CSIR Meraka Institute. GLSD and the CSIR calculation engine together are able to quantify the amount of TVWSs through dynamically allocating the TVWS network radio services according to the geographic position of WSDs. The GLSD was developed using the ITU-R P.1546-5 propagation model. Using the GLSD and the CSIR calculation engine, the quantification of TVWS free channels are calculated. The results show that among the 58 VHF and UHF TV channels, 52 of the channels are free (underutilized) in Ethiopia. These free channels can be employed to provide wireless broadband solutions for connecting the rural areas as well as offloading the urban traffic.

This paper describes the findings from our study on the parallel usage of Logisim software tool and remote experiment based on Nexys 2 FPGA hardware platform for learning digital circuits design and computer architecture by students of the first and the second-year of Electrical, Computer and Mechatronics Engineering undergraduate study programs at the Faculty of Technical Science Čačak, University of Kragujevac. For the purpose of comparison of the effectiveness of these two learning tools, a survey was conducted between students who used these tools in learning digital circuits design within the course Foundations in Computer Technics 2 during the winter semester of the academic year 2016-2107. Based on analysis of given results some conclusions were drawn regarding to parallel usage of Logisim software tool and remote experiments based on FPGA hardware platform in learning digital circuits design.

The issue of spectrum allocation in cognitive high altitude platform wireless networks using TV White Space (TVWS) spectrum is presented in this paper. The mathematical model of spectrum allocation is given, and this model is converted into a constrained optimization problem with the goal of maximizing network benefits. Then, a spectrum allocation optimization approach is proposed that is based on improved immune clonal selection algorithm. According to the characteristics of the problem, the design, coding, cloning, mutation, hypermutation and selection operators suitable for the algorithm's solution are presented. Finally, a simulation experiment was carried out on this algorithm. The proposed algorithm was validated and proved that it converges better than Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Moreover, experiments demonstrate that the suggested approach maximizes network benefits or rewards more effectively when compared with GA and PSO algorithms and results proved the effectiveness of the algorithm.

Employing technological advances in communications along with the available aerial and space platforms can enable us, to setup a safety monitoring and management system for delivering proactive and reactive surveillance of our forests. This work stresses the importance of protecting our forests considering the socioeconomic impact they have on our world. It also outlines the available platform technologies and proposes a tool for setting up a monitoring system that employs current technologies. This tool simulates forest fires and uses wireless sensors to monitor the fire. Results show that the number and the location of the sensors in a forest are critical in increasing the chances of sensing the fire on time. Since positioning sensors in an organized manner within a forest is tedious if not impossible to implement, it is recommended that areas with higher flammability are equipped with greater number of sensors.

Employing technological advances in communications along with the available aerial and space platforms can enable us, to setup a safety monitoring and management system for delivering proactive and reactive surveillance of our forests. This work stresses the importance of protecting our forests considering the socioeconomic impact they have on our world. It also outlines the available platform technologies and proposes a tool for setting up a monitoring system that employs current technologies. This tool simulates forest fires and uses wireless sensors to monitor the fire. Results show that the number and the location of the sensors in a forest are critical in increasing the chances of sensing the fire on time. Since positioning sensors in an organized manner within a forest is tedious if not impossible to implement, it is recommended that areas with higher flammability are equipped with greater number of sensors.

The use of Social Network Centrality alongside Content Centric Networking is used towards improving user's access to content, as well as maximizing the efficient exploitation of network resources. This work demonstrates how online Social Network Centrality can be used with content centric solutions for efficient content distribution in AAL environments. The benefits of this approach are highlighted, by conducting simulations and providing results on the performance of the proposed research approach. In particular, this work shows how the proposed resource allocation method improves the regular IP-based content delivery allocation in the distribution of content. Facebook data is used as a super-set of AAL data, in order to map users to a network graph and using their social proximity to determine where content can be effectively cached. The efficiency of the proposed scheme is validated for its performance through simulations, indicating the level of the offered efficiency in contrast to content distribution.

The Digital Agenda for Europe (2015) states that there will be 825,000 unfilled vacancies for Information and Communications Technology by 2020. This lack of IT professionals stems from the small number of students graduating in computer science. To retain more students in the field, teachers can use various educational technologies to explain difficult concepts. One of these educational technologies is remote robotic experimentation. The correlational study described in this paper utilizes the unified theory of acceptance and use of technology acceptance model to examine if performance expectancy, effort expectancy, social influence, and facilitating conditions can predict the intention of high school computer science teachers in Cyprus to use remote robotic experiments in their classes. Surveys, based on the UTAUT survey instrument, were collected from 90 high school computer science teachers in Cyprus, and a multiple regression analysis was applied to measure the correlations between the constructs and finally the model fit of the analysis. The results of the study show that if certain conditions are provided to the teachers then there is a higher probability that they will use remote robotic experimentation in their classes.

The uptake of urban city monitoring systems has been synonymous with the rise of Internet of Things (IoT) technologies since their conception. These systems are increasingly incorporated in a wide range of domains, such as disaster awareness, management, and prevention by contextualizing events. In this study, we have developed a platform capable of capturing and associating data from both social media and sensing devices, towards early discovery of disaster-related events by authorities and citizens alike. Establishing these points of association, which we dub as the 'Feedback Loop', forms the basis of our research endeavors. In this paper, we present the architectural components put in place to realize this, at the hardware and software level, as well as the challenges we had to overcome in deploying these at scale within the Engomi Business Region of Nicosia, Cyprus. Pivotal to its final form involved the utilization of Big Data processing technologies to allow for flexibility of sensor deployment and high availability throughout its lifetime. Coupled with state-of-the-art Natural Language Processing (NLP) and anomaly detection algorithms, geared towards spatiotemporal sensor data and natural language processing, our eco-system features a holistic solution towards enhanced decision support.

Recent advances in wireless communications such as Low Power Wider Area Networks (LPWAN) have actively encouraged the development of cutting-edge Internet of Things (IoT) applications. The healthcare sector has been considered one of the main areas that IoT can be used to inspire novel applications. One such application is the electrocardiogram (ECG) which integrating it with an IoT capability can become an instrument for monitoring patients and predicting possible conditions of the patients thanks to crowdsensing and machine learning techniques. This paper presents a conceptual design of a system for 3-lead ECG monitoring that is being customized to communicate its findings through LoRaWAN. The medical sensor's conceptual design is based on the specification of the communication protocol in order to cope with its operating characteristics as well as to improve its power consumption.