Impact of initialization of a modified particle swarm optimization on cooperative source searching

Swarm robotic is well known for its flexibility, scalability and robustness that make it suitable for solving many real-world problems. Source searching which is characterized by complex operation due to the spatial characteristic of the source intensity distribution, uncertain searching environments and rigid searching constraints is an example of application where swarm robotics can be applied. Particle swarm optimization (PSO) is one of the famous algorithms have been used for source searching where its effectiveness depends on several factors. Improper parameter selection may lead to a premature convergence and thus robots will fail (i.e., low success rate) to locate the source within the given searching constraints. Additionally, target overshooting and improper initialization strategies may lead to a nonoptimal (i.e., take longer time to converge) target searching. In this study, a modified PSO and three different initializations strategies (i.e., random, equidistant and centralized) were proposed. The findings shown that the proposed PSO model successfully reduce the target overshooting by choosing optimal PSO parameters and has better convergence rate and success rate compared to the benchmark algorithms. Additionally, the findings also indicate that the random initialization give better searching success compared to equidistant and centralize initialization

Drones and the Creative Industry

This open access, interdisciplinary book presents innovative strategies in the use of civil drones in the cultural and creative industry. Specially aimed at small and medium-sized enterprises (SMEs), the book offers valuable insights from the fields of marketing, engineering, arts and management. With contributions from experts representing varied interests throughout the creative industry, including academic researchers, software developers and engineers, it analyzes the needs of the creative industry when using civil drones both outdoors and indoors. The book also provides timely recommendations to the industry, as well as guidance for academics and policymakers

Towards Proactive Context-aware Computing and Systems

A primary goal of context-aware systems is delivering the right information at the right place and right time to users in order to enable them to make effective decisions and improve their quality of life. There are three key requirements for achieving this goal: determining what information is relevant, personalizing it based on the users’ context (location, preferences, behavioral history etc.), and delivering it to them in a timely manner without an explicit request from them. These requirements create a paradigm that we term as “Proactive Context-aware Computing”. Most of the existing context-aware systems fulfill only a subset of these requirements. Many of these systems focus only on personalization of the requested information based on users’ current context. Moreover, they are often designed for specific domains. In addition, most of the existing systems are reactive - the users request for some information and the system delivers it to them. These systems are not proactive i.e. they cannot anticipate users’ intent and behavior and act proactively without an explicit request from them. In order to overcome these limitations, we need to conduct a deeper analysis and enhance our understanding of context-aware systems that are generic, universal, proactive and applicable to a wide variety of domains. To support this dissertation, we explore several directions. Clearly the most significant sources of information about users today are smartphones. A large amount of users’ context can be acquired through them and they can be used as an effective means to deliver information to users. In addition, social media such as Facebook, Flickr and Foursquare provide a rich and powerful platform to mine users’ interests, preferences and behavioral history. We employ the ubiquity of smartphones and the wealth of information available from social media to address the challenge of building proactive context-aware systems. We have implemented and evaluated a few approaches, including some as part of the Rover framework, to achieve the paradigm of Proactive Context-aware Computing. Rover is a context-aware research platform which has been evolving for the last 6 years. Since location is one of the most important context for users, we have developed ‘Locus’, an indoor localization, tracking and navigation system for multi-story buildings. Other important dimensions of users’ context include the activities that they are engaged in. To this end, we have developed ‘SenseMe’, a system that leverages the smartphone and its multiple sensors in order to perform multidimensional context and activity recognition for users. As part of the ‘SenseMe’ project, we also conducted an exploratory study of privacy, trust, risks and other concerns of users with smart phone based personal sensing systems and applications. To determine what information would be relevant to users’ situations, we have developed ‘TellMe’ - a system that employs a new, flexible and scalable approach based on Natural Language Processing techniques to perform bootstrapped discovery and ranking of relevant information in context-aware systems. In order to personalize the relevant information, we have also developed an algorithm and system for mining a broad range of users’ preferences from their social network profiles and activities. For recommending new information to the users based on their past behavior and context history (such as visited locations, activities and time), we have developed a recommender system and approach for performing multi-dimensional collaborative recommendations using tensor factorization. For timely delivery of personalized and relevant information, it is essential to anticipate and predict users’ behavior. To this end, we have developed a unified infrastructure, within the Rover framework, and implemented several novel approaches and algorithms that employ various contextual features and state of the art machine learning techniques for building diverse behavioral models of users. Examples of generated models include classifying users’ semantic places and mobility states, predicting their availability for accepting calls on smartphones and inferring their device charging behavior. Finally, to enable proactivity in context-aware systems, we have also developed a planning framework based on HTN planning. Together, these works provide a major push in the direction of proactive context-aware computing

Three transducers for one photodetector: essays for optical communications

Dissertation presented to obtain the PhD degree in Electrical and Computer Engineering - ElectronicsOptical processing devices based on a- SiC:H multilayer architectures are expected to become reconfigurable to perform WDM optoelectronic logic functions and provide as well complex photonic functions such as signal amplification and switching. This thesis, entitled ”Three Transducers for One Photodetector: essays for optical communications”, reports the main work areas to design, control, validate and evaluate the research of a voltage-controllable wavelength selective optical switching based on shifting between positive and negative electrically bias and a photodetector, which enables the filtering function with the detector itself and has the potential to be rapidly optically biasing tuned: System Architecture – In this work area it is defined the basic requirements of the device: light-to-dark sensitivity, colour recognition, selective optical and electrical output response, amplification and opto-electronic conversion to transmit, receive, and/or process intelligence(data).The output multiplexed signals should have a strong nonlinear dependence on the light absorption profile, i.e., on the incident light wavelength, bit rate and intensity under unbalanced light generation of carriers. Experimental Design – This test activities work area allows the evaluation of the results. Multiple monochromatic pulsed communication channels were transmitted together, each one with a specific bit sequence. The combined optical signal was analyzed by reading out, under different applied voltages and optical bias, the generated photocurrent across the device. Depending on the wavelength of the external background and irradiation side, it acts either as a short- or a long- pass band filter or as a band-stop filter Optoelectronic Algorithm Interface – To help improve our understanding of the output multiplexed signal, computer models of monolithic photodetectors are developed. Following control theoretic methods we derive state-space representation and an equivalent circuit optoelectronic simulator. We validate each model and calibrate the spectral gain model by background–probe experiments and truth tables lookup that perform 8-to-1 multiplexer (MUX) and 1-to-8 demultiplexer (DEMUX) functions. Applications – The purpose of this work area is to present a new optical logic architecture that offers considerable improvements in reconfigurability. Tunable WDM converters based on amorphous SiC multilayer photonic active filters are used to build blocks to perform standard digital system operations. The transducers combine the simultaneous demultiplexing operation with the photodetection and self amplification. They are optimized for provide the high-sensitivity needed for low-light applications, such as medicine, lighting, sensing and measurement, and manufacturing. The migration to next generation packet based networks can be much easier and smoother than previously thought, using the emerging a-Si solutions and its integration with plastic optical fiber. It will push the limits of functionality, cost/performance and integration level

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate