Accuracy improvement of connectivity-based sensor network localization

The early results from connectivity-based sensor network localization suffer from disappointing accuracy. The reason is partly due to the limited information of the problem, and also the deficiencies of the algorithms. This paper proposes a two-level range/indication of connectivity between each pair of nodes, which would indicate three levels of connectivity: strong, weak or nil. Theoretically, the two-level connectivity localization problem can be modeled as a non-convex optimization problem in mathematics, which contains the convex constraints and non-convex constraints. Besides using two-level range to enrich the given information, a two-objective evolutionary algorithm is also used for searching a solution. The simulation is carried out using five different topology networks all containing 100 nodes. Simulation results have shown that better solution can be obtained by using two-level range connectivity when compared with the usual one-level range connectivity-based localization.published_or_final_versionThe 25th IEEE Canadian Conference on Electrical & Computer Engineering (CCECE 2012), Montreal, QC., 29 April-2 May 2012. In IEEE Canadian Conference on Electrical and Computer Engineering Proceedings, 2012, p. 1-

Design of the usability measurement tool for multimodal mobile applications

Nowadays, mobile phones provide not just voice call and messaging services, but plethora of other services.Those computational capabilities allow mobile phones to serve people in various areas including education, banking, commerce, travelling, and other daily life aspects. Meanwhile, the number of mobile phone users has increased dramatically in the last decade.On the other hand, the usability of an application can usually be verified through the user interface. Therefore, this paper aims to design a measurement tool to evaluate the usability of mobile applications based on the usability attributes and dimensions that must be considered in the interface.To obtain the appropriate attributes, a Systematic Literature Review (SLR) has been conducted and the Goal Question Metric (GQM) has been used to design the tool. From 261 related works only 18 most relevant ones were selected, through four SLR. 25 dimensions were found through the SLR, but some of these dimensions are synonymous or a part of other dimensions. Consequently, three dimensions must be included in any usability evaluation instrument, which is broken down into ten sub dimensions

A mobile app to support clinical diagnosis of upper respiratory problems (eHealthResp): co-design approach

Background: The misuse of antibiotics is a global public health issue that fosters bacterial resistance and jeopardizes generational health. The development of validated tools such as web-based courses and mobile apps to enhance clinical decisions in upper respiratory infections is of great importance in reducing the incorrect use of antibiotics in these situations. Objective: The aim of this study was to design and prevalidate the interface of a mobile app to assist and provide clinical support in the diagnosis of upper respiratory problems. We aimed to assess the adequacy and usability of the interface of the tool in the belief that it could be beneficial to health care delivery in the clinical decision setting. Methods: Using a co-design approach that brought together professionals in interface design and experts in pharmacology and pharmacoepidemiology, the mobile app interface was evaluated through peer review sessions held by interface design professionals on a heuristic survey. The reviewers accessed a high-fidelity interactive mock-up of the interface and filled in a questionnaire to assess the dimensions of layout and visual design and navigation and tasks. The resulting feedback of this evaluation supported the redesign of the primary interface, which was assessed for the second time by 2 of the previously mentioned reviewers. Results: With 4 as the highest score, the interface scored a mean of 3.16 (SD 0.45; median of the means 3.2) for layout and visual design and a mean of 3.43 (SD 0.33; median of the means 3.51) for navigation and tasks, reflecting an overall positive evaluation. The open-ended commentaries allowed us to better understand specific recommendations of the reviewers. Throughout this section, approximately 0.98 comments per parameter were registered, reflecting a high level of effectiveness of the chosen parameters in identifying potential problems. The resultant beta version of the interface, addressing the majority of the detected problems, was further assessed by 2 of the previous reviewers, validating the new design. Future tests with physicians and pharmacists will help assess credibility and user experience dimensions. Conclusions: Our study revealed that the designed interface is easy to interpret and use. Peer reviewers raised important issues that could be easily fixed and positively reassessed. As a result, the study enabled us to produce a new tool for interface usability assessment and a set of recommendations for developing mobile interfaces for clinical decision support systems in the scope of upper respiratory problems.publishe

Optimal Sizing of Battery Storage Systems for Industrial Applications when Uncertainties Exist

in fact, we think that the sizing procedure must properly take into account the unavoidable uncertainties introduced by the cost of electricity and the load demands of industrial facilities. Three approaches provided by Decision Theory were applied, and they were based on: (1) the minimization of expected cos

Spectral and Energy Efficient Communication Systems and Networks

In this thesis, design and analysis of energy- and spectral-efficient communication and cellular systems in micro wave and millimeter wave bands are considered using the following system performance metrics: i) Energy efficiency; ii) Spectral efficiency; iii) Spatial spectral efficiency; iv) Spatial energy efficiency, and v) Bit error rate. Statistical channel distributions, Nakagami-m and Generalized-K, and path loss models, Line of Sight (LOS) and Non-Line of Sight (NLOS), are used to represent the propagation environment in these systems. Adaptive M-QAM and M-CPFSK communication systems are proposed to enhance their efficiency metrics as a function of Signal-to-Noise Ratio (SNR) over the channel. It is observed that in the adaptive M-QAM system energy efficiency can be improved by 0.214 bits/J whereas its spectral efficiency can be enhanced by 40%, for wide range of SNR compared to that of conventional M-QAM system. In case of adaptive M-CPFSK system, spectral and energy efficiencies can be increased by 33% and 76%, respectively. A framework for design and analysis of a cellular system, with omni and sectorized antenna systems at Base Station (BS), using its efficiency metrics and coverage probability is presented assuming wireless channel is Nakagami-m fading coupled with path loss and co-channel interference. It is noted that sectorized antenna system at BS enhances energy and spectral efficiencies by nearly 109% and 1.5 bits/s/Hz, respectively, compared to conventional omni antenna system. A Multi-User MIMO cellular system is then investigated and closed-form expressions for its uplink efficiency metrics are derived for fading and shadowing wireless channel environment. It is observed that increasing number of antennas in MIMO system at BS can significantly improve efficiency metrics of cellular system. Finally, a framework for design and analysis of dense mmWave cellular system, in 28 and 73 GHz bands, is presented for efficient utilization of spectrum and power of the system. The efficiency metrics of the system are evaluated for LOS and NLOS links. It is observed that while 28 GHz band is expedient for indoor cellular systems, the 73 GHz band is appropriate for outdoor systems

A single-phase bidirectional AC/DC converter for V2G applications

This paper presents a single-phase bidirectional current-source AC/DC converter for vehicle to grid (V2G) applications. The presented converter consists of a line frequency commutated unfolding bridge and an interleaved buck-boost stage. The low semiconductor losses of the line frequency commutated unfolding bridge contribute to the comparatively good efficiency of this converter. The buck and boost operating modes of the interleaved buck-boost stage provide operation over a wide battery voltage range. The interleaved structure of the interleaved buck-boost stage results in lower battery current ripple. In addition, sinusoidal input current, bidirectional power flow and reactive power compensation capability are also guaranteed. This paper presents the topology and operating principles of the presented converter. The feasibility of the converter is validated using MATLAB simulations, as well as experimental results

Deep Learning Based Methods for Outdoor Robot Localization and Navigation

The number of elderly people is increasing around the globe. In order to support the growing of ageing society, mobile robot is one of viable choices for assisting the elders in their daily activities. These activities happen in any places, either indoor or outdoor. Although outdoor activities benefit the elders in many ways, outdoor environments contain difficulties from their unpredictable natures. Mobile robots for supporting humans in outdoor environments must automatically traverse through various difficulties in the environments using suitable navigation systems.Core components of mobile robots always include the navigation segments. Navigation system helps guiding the robot to its destination where it can perform its designated tasks. There are various tools to be chosen for navigation systems. Outdoor environments are mostly open for conventional navigation tools such as Global Positioning System (GPS) devices. In this thesis three systems for localization and navigation of mobile robots based on visual data and deep learning algorithms are proposed. The first localization system is based on landmark detection. The Faster Regional-Convolutional Neural Network (Faster R-CNN) detects landmarks and signs in the captured image. A Feed-Forward Neural Network (FFNN) is trained to determine robot location coordinates and compass orientation from detected landmarks. The dataset consists of images, geolocation data and labeled bounding boxes to train and test two proposed localization methods. Results are illustrated with absolute errors from the comparisons between localization results and reference geolocation data in the dataset. The second system is the navigation system based on visual data and a deep reinforcement learning algorithm called Deep Q Network (DQN). The employed DQN automatically guides the mobile robot with visual data in the form of images, which received from the only Universal Serial Bus (USB) camera that attached to the robot. DQN consists of a deep neural network called convolutional neural network (CNN), and a reinforcement learning algorithm named Q-Learning. It can make decisions with visual data as input, using experiences from consequences of trial-and-error attempts. Our DQN agents are trained in the simulation environments provided by a platform based on a First-Person Shooter (FPS) game named ViZDoom. Simulation is implemented for training to avoid any possible damage on the real robot during trial-and-error process. Perspective from the simulation is the same as if a camera is attached to the front of the mobile robot. There are many differences between the simulation and the real world. We applied a markerbased Augmented Reality (AR) algorithm to reduce differences between the simulation and the world by altering visual data from the camera with resources from the simulation.The second system is assigned the task of simple navigation to the robot, in which the starting location is fixed but the goal location is random in the designated zone. The robot must be able to detect and track the goal object using a USB camera as its only sensor. Once started, the robot must move from its starting location to the designated goal object. Our DQN navigation method is tested in the simulation and on the real robot. Performances of our DQN are measured quantitatively via average total scores and the number of success navigation attempts. The results show that our DQN can effectively guide a mobile robot to the goal object of the simple navigation tasks, for both the simulation and the real world.The third system employs a Transfer Learning (TL) strategy to reduce training time and resources required for the training of newly added tasks of DQN agents. The new task is the task of reaching the goal while also avoiding obstacles at the same time. Additionally, the starting and the goal locations are all random within the specified areas. The employed transfer learning strategy uses the whole network of the DQN agent trained for the first simple navigation task as the base for training the DQN agent for the second task. The training in our TL strategy decrease the exploration factor, which cause the agent to rely on the existing knowledge from the base network more than randomly selecting actions during the training. It results in the decreased training time, in which optimal solutions can be found faster than training from scratch.We evaluate performances of our TL strategy by comparing the DQN agents trained with our TL at different exploration factor values and the DQN agent trained from scratch. Additionally, agents trained from our TL are trained with the decreased number of episodes to extensively display performances of our TL agents. All DQN agents for the second navigation task are tested in the simulation to avoid any possible and uncontrollable damages from the obstacles. Performances are measured through success attempts and average total scores, same as in the first navigation task. Results show that DQN agents trained via the TL strategy can greatly outperform the agent trained from scratch, despite the lower number of training episodes.博士(工学)法政大学 (Hosei University

Advancements in Hydropower Design and Operation for Present and Future Electrical Demand

With current infrastructure, meeting the ever-growing demand for electrical energy across the globe is becoming increasingly difficult. The widespread adoption of both commercial and residential non-dispatchable renewable energy facilities, such as solar and wind, further taxes the stability of the electrical grid, often causing traditional fossil fuel power plants to operate at lower efficiency, and with increased carbon emissions. Hydropower, as a proven renewable energy technology, has a significant part to play in the future global electrical power market, especially as increasing demand for electric vehicles will further amplify the need for dispatchable energy sources during peak charging times. Even with more than a century of proven experience, significant opportunities still exist to expand the worldwide hydropower resources and more efficiently utilize existing hydropower installations. Given this context, this Special Issue of Energies intended to present recent developments and advancements in hydropower design and operation. This Special Issue includes five articles, authored by international research teams from Japan, Pakistan, Sweden, Norway, the United States, and China. The authors bring the collective expertise of government research laboratories, university professors, industry research engineers, computer scientists, and economists. The articles explore advancements in hydroturbine and pump-turbine design, power plant operation, auxiliary equipment design to mitigate environmental damage, and an exploration of community-owned small hydropower facilities

Current state of digital signal processing in myoelectric interfaces and related applications

This review discusses the critical issues and recommended practices from the perspective of myoelectric interfaces. The major benefits and challenges of myoelectric interfaces are evaluated. The article aims to fill gaps left by previous reviews and identify avenues for future research. Recommendations are given, for example, for electrode placement, sampling rate, segmentation, and classifiers. Four groups of applications where myoelectric interfaces have been adopted are identified: assistive technology, rehabilitation technology, input devices, and silent speech interfaces. The state-of-the-art applications in each of these groups are presented.Peer reviewe