14 research outputs found
Aircraft Noise
Noise generated by aircraft continues to be a pressing issue for society, as an increasing number of people residing in close proximity to airports make noise complaints on a regular basis. The reduction in aircraft noise is therefore a very important engineering task that would require the careful identification of different acoustic sources around the airplane, the understanding of noise source behavior and ranking along flight trajectories, sophisticated measurement techniques, and robust and accurate numerical tools aimed at predicting the generation of noise, the propagation through the atmosphere, and the resulting noise impact along approach and departure flights. For an overall assessment of the situation, it has to be assessed along entire flight trajectories rather than assessing limited operating conditions only. Furthermore, it is highly recommended to apply multiple acoustic metrics and account for different and widespread observer locations along the flight. Only then can the overall situation be adequately captured. Obviously, this is a highly multidisciplinary effort and no single discipline can address this problem. This reprint includes selected research studies with that multidisciplinary context that deal with numerical or experimental investigations that range from the investigation of specific noise sources to the assessment of noise generated by the overall aircraft in operation. Both basic and applied research studies involving the modelling and simulation of aircraft noise are included
Optimization Methods Applied to Power Systems â…¡
Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems
Planning and Scheduling Optimization
Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development
Aircraft Noise
This reprint is about aircraft noise. Multidisciplinary topics are covered. One focus is supersonic transport aircraft and their noise generation during approach and take-off. The articles within this study present recent and ongoing research activities from research entities and universities from around the world. This book is beneficial for engineers and researchers that are working the field of aircraft noise
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Proceedings 31st Annual ARCOM Conference, Lincoln, 7-9 September 2015: vol. 1
Particle Swarm Optimization
Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field
Service level agreement specification for IoT application workflow activity deployment, configuration and monitoring
PhD ThesisCurrently, we see the use of the Internet of Things (IoT) within various domains
such as healthcare, smart homes, smart cars, smart-x applications, and smart
cities. The number of applications based on IoT and cloud computing is projected
to increase rapidly over the next few years. IoT-based services must meet
the guaranteed levels of quality of service (QoS) to match users’ expectations.
Ensuring QoS through specifying the QoS constraints using service level agreements
(SLAs) is crucial. Also because of the potentially highly complex nature
of multi-layered IoT applications, lifecycle management (deployment, dynamic
reconfiguration, and monitoring) needs to be automated. To achieve this it is
essential to be able to specify SLAs in a machine-readable format.
currently available SLA specification languages are unable to accommodate
the unique characteristics (interdependency of its multi-layers) of the IoT domain.
Therefore, in this research, we propose a grammar for a syntactical structure
of an SLA specification for IoT. The grammar is based on a proposed conceptual
model that considers the main concepts that can be used to express the requirements
for most common hardware and software components of an IoT application
on an end-to-end basis. We follow the Goal Question Metric (GQM) approach to
evaluate the generality and expressiveness of the proposed grammar by reviewing
its concepts and their predefined lists of vocabularies against two use-cases
with a number of participants whose research interests are mainly related to IoT.
The results of the analysis show that the proposed grammar achieved 91.70% of
its generality goal and 93.43% of its expressiveness goal.
To enhance the process of specifying SLA terms, We then developed a toolkit
for creating SLA specifications for IoT applications. The toolkit is used to simplify
the process of capturing the requirements of IoT applications. We demonstrate
the effectiveness of the toolkit using a remote health monitoring service (RHMS)
use-case as well as applying a user experience measure to evaluate the tool by
applying a questionnaire-oriented approach. We discussed the applicability of our
tool by including it as a core component of two different applications: 1) a contextaware
recommender system for IoT configuration across layers; and 2) a tool for
automatically translating an SLA from JSON to a smart contract, deploying it
on different peer nodes that represent the contractual parties. The smart contract
is able to monitor the created SLA using Blockchain technology. These two
applications are utilized within our proposed SLA management framework for IoT.
Furthermore, we propose a greedy heuristic algorithm to decentralize workflow
activities of an IoT application across Edge and Cloud resources to enhance
response time, cost, energy consumption and network usage. We evaluated the
efficiency of our proposed approach using iFogSim simulator. The performance
analysis shows that the proposed algorithm minimized cost, execution time, networking,
and Cloud energy consumption compared to Cloud-only and edge-ward
placement approaches
Personality Identification from Social Media Using Deep Learning: A Review
Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed