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Articles 4501 - 4530 of 5232

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Instance-Specific Selection Of Aos Methods For Solving Combinatorial Optimisation Problems Via Neural Networks, Teck Hou (Deng Dehao) Teng, Hoong Chuin Lau, Aldy Gunawan Jun 2018

Instance-Specific Selection Of Aos Methods For Solving Combinatorial Optimisation Problems Via Neural Networks, Teck Hou (Deng Dehao) Teng, Hoong Chuin Lau, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Solving combinatorial optimization problems using a fixed set of operators has been known to produce poor quality solutions. Thus, adaptive operator selection (AOS) methods have been proposed. But, despite such effort, challenges such as the choice of suitable AOS method and configuring it correctly for given specific problem instances remain. To overcome these challenges, this work proposes a novel approach known as I-AOS-DOE to perform Instance-specific selection of AOS methods prior to evolutionary search. Furthermore, to configure the AOS methods for the respective problem instances, we apply a Design of Experiment (DOE) technique to determine promising regions of parameter values …

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Reserved Optimisation: Handling Incident Priorities In Emergency Response Systems, Muralidhar Konda, Supriyo Ghosh, Pradeep Varakantham Jun 2018

Reserved Optimisation: Handling Incident Priorities In Emergency Response Systems, Muralidhar Konda, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Emergency (medical, fire or criminal) Management Systems(EMSs) are crucial for ensuring public safety and security. Typically in many cities, less than 20% of the cases received by EMSs belong to the extremely serious category and require immediate help. Rest of the incidents typically are less serious and thereby allow more flexibility in response time. Therefore, for efficient management of EMS requests, several EMSs now categorise an incoming emergency request into apriority level based on well studied “triaging” methods. Leading research on optimising emergency response has either focussed on data-driven models for settings with homogenous incidents or on generic heuristics (that …

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Risk Assessment Of Dropped Cylindrical Objects In Offshore Operations, Adelina Steven May 2018

Risk Assessment Of Dropped Cylindrical Objects In Offshore Operations, Adelina Steven

LSU New Orleans Theses and Dissertations

Dropped object are defined as any object that fall under its own weight from a previously static position or fell due to an applied force from equipment or a moving object. It is among the top ten causes of injuries and fatality in oil and gas industry. To solve this problem, several in-house tools and guidelines is developed over time to assess the risk of dropped objects on the sub-sea structures. This thesis focuses on compiling and comparing those methods in hope to improve the recommended practices available in the market. A simple modification is done on the in-house tools …

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Bi-Directional Testing For Change Point Detection In Poisson Processes, Moinak Bhaduri May 2018

Bi-Directional Testing For Change Point Detection In Poisson Processes, Moinak Bhaduri

UNLV Theses, Dissertations, Professional Papers, and Capstones

Point processes often serve as a natural language to chronicle an event's temporal evolution, and significant changes in the flow, synonymous with non-stationarity, are usually triggered by assignable and frequently preventable causes, often heralding devastating ramifications. Examples include amplified restlessness of a volcano, increased frequencies of airplane crashes, hurricanes, mining mishaps, among others. Guessing these time points of changes, therefore, merits utmost care. Switching the way time traditionally propagates, we posit a new genre of bidirectional tests which, despite a frugal construct, prove to be exceedingly efficient in culling out non-stationarity under a wide spectrum of environments. A journey surveying …

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Fundamental Tradeoffs In Estimation Of Finite-State Hidden Markov Models, Justin Le May 2018

Fundamental Tradeoffs In Estimation Of Finite-State Hidden Markov Models, Justin Le

UNLV Theses, Dissertations, Professional Papers, and Capstones

Hidden Markov models (HMMs) constitute a broad and flexible class of statistical models that are widely used in studying processes that evolve over time and are only observable through the collection of noisy data. Two problems are essential to the use of HMMs: state estimation and parameter estimation. In state estimation, an algorithm estimates the sequence of states of the process that most likely generated a certain sequence of observations in the data. In parameter estimation, an algorithm computes the probability distributions that govern the time-evolution of states and the sampling of data. Although algorithms for the two problems are …

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Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch May 2018

Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch

Electronic Theses and Dissertations

The performance and stability of the Particle Swarm Optimization algorithm depends on parameters that are typically tuned manually or adapted based on knowledge from empirical parameter studies. Such parameter selection is ineffectual when faced with a broad range of problem types, which often hinders the adoption of PSO to real world problems. This dissertation develops a dynamic self-optimization approach for the respective parameters (inertia weight, social and cognition). The effects of self-adaption for the optimal balance between superior performance (convergence) and the robustness (divergence) of the algorithm with regard to both simple and complex benchmark functions is investigated. This work …

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Effect Of Anthropometric Variability On Middle-Market Aircraft Seating, Tara C. Sriram Feb 2018

Effect Of Anthropometric Variability On Middle-Market Aircraft Seating, Tara C. Sriram

International Journal of Aviation, Aeronautics, and Aerospace

A middle-of-market aircraft, or MoMA, is defined as an aircraft capable of flying 180-250 passengers without refueling for 2,300-5,800 miles(~2,000-5,000 nautical miles). As the name suggests, middle-of-market aircraft are positioned in between the market segments served by narrow body (single-aisle) and wide body (twin-aisle) aircraft. This paper presents the findings of a study on the effect of anthropomorphic variability on economy class seating on middle-market aircraft currently in service. The study found that among 130 middle-market LOPAs, the mean seat pitch was greater for US airlines than for Asian airlines. Furthermore, the sampled Asian airlines had a higher preference …

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Integrated Cooperation And Competition In Multi-Agent Decision-Making, Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein Feb 2018

Integrated Cooperation And Competition In Multi-Agent Decision-Making, Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Observing that many real-world sequential decision problems are not purely cooperative or purely competitive, we propose a new model—cooperative-competitive process (CCP)—that can simultaneously encapsulate both cooperation and competition.First, we discuss how the CCP model bridges the gap between cooperative and competitive models. Next, we investigate a specific class of group-dominant CCPs, in which agents cooperate to achieve a common goal as their primary objective, while also pursuing individual goals as a secondary objective. We provide an approximate solution for this class of problems that leverages stochastic finite-state controllers.The model is grounded in two multi-robot meeting and box pushing domains that …

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Resource-Constrained Scheduling For Maritime Traffic Management, Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau Feb 2018

Resource-Constrained Scheduling For Maritime Traffic Management, Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We address the problem of mitigating congestion and preventing hotspots in busy water areas such as Singapore Straits and port waters. Increasing maritime traffic coupled with narrow waterways makes vessel schedule coordination for just-in-time arrival critical for navigational safety. Our contributions are: 1) We formulate the maritime traffic management problem based on the real case study of Singapore waters; 2) We model the problem as a variant of the resource-constrained project scheduling problem (RCPSP), and formulate mixed-integer and constraint programming (MIP/CP) formulations; 3) To improve the scalability, we develop a combinatorial Benders (CB) approach that is significantly more effective than …

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Dispatch Guided Allocation Optimization For Effective Emergency Response, Supriyo Ghosh, Pradeep Varakantham Feb 2018

Dispatch Guided Allocation Optimization For Effective Emergency Response, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Effective emergency (medical, fire or criminal) response iscrucial for improving safety and security in urban environments. Recent research in improving effectiveness of emergency management systems (EMSs) has utilized data-drivenoptimization models for efficient allocation of emergency response vehicles (ERVs) to base locations. However, thesedata-driven optimization models either ignore the dispatchstrategy of ERVs (typically the nearest available ERV is dispatched to serve an incident) or employ myopic approaches(e.g., greedy approach based on marginal gain). This resultsin allocations that are not synchronised with the real evolution dynamics on the ground or can be improved significantly.To bridge this gap, we make the following contributions: …

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Scalable Urban Mobile Crowdsourcing: Handling Uncertainty In Worker Movement, Shih-Fen Cheng, Cen Chen, Thivya Kandappu, Hoong Chuin Lau, Archan Misra, Nikita Jaiman, Randy Tandriansyah Daratan, Desmond Koh Feb 2018

Scalable Urban Mobile Crowdsourcing: Handling Uncertainty In Worker Movement, Shih-Fen Cheng, Cen Chen, Thivya Kandappu, Hoong Chuin Lau, Archan Misra, Nikita Jaiman, Randy Tandriansyah Daratan, Desmond Koh

Research Collection School Of Computing and Information Systems

In this article, we investigate effective ways of utilizing crowdworkers in providing various urban services. The task recommendation platform that we design can match tasks to crowdworkers based on workers’ historical trajectories and time budget limits, thus making recommendations personal and efficient. One major challenge we manage to address is the handling of crowdworker’s trajectory uncertainties. In this article, we explicitly allow multiple routine routes to be probabilistically associated with each worker. We formulate this problem as an integer linear program whose goal is to maximize the expected total utility achieved by all workers. We further exploit the separable structures …

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Risk-Sensitive Stochastic Orienteering Problems For Trip Optimization In Urban Environments, Pradeep Varakantham, Akshat Kumar, Hoong Chuin Lau, William Yeoh Feb 2018

Risk-Sensitive Stochastic Orienteering Problems For Trip Optimization In Urban Environments, Pradeep Varakantham, Akshat Kumar, Hoong Chuin Lau, William Yeoh

Research Collection School Of Computing and Information Systems

Orienteering Problems (OPs) are used to model many routing and trip planning problems. OPs are a variantof the well-known traveling salesman problem where the goal is to compute the highest reward path thatincludes a subset of vertices and has an overall travel time less than a specified deadline. However, the applicabilityof OPs is limited due to the assumption of deterministic and static travel times. To that end, Campbellet al. extended OPs to Stochastic OPs (SOPs) to represent uncertain travel times (Campbell et al. 2011). Inthis article, we make the following key contributions: (1) We extend SOPs to Dynamic SOPs (DSOPs), …

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Communication Based Control For Dc Microgrids, Mahmoud S. Saleh, Yusef Esa, Ahmed Mohamed Jan 2018

Communication Based Control For Dc Microgrids, Mahmoud S. Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

Centralized communication-based control is one of the main methods that can be implemented to achieve autonomous advanced energy management capabilities in DC microgrids. However, its major limitation is the fact that communication bandwidth and computation resources are limited in practical applications. This can be often improved by avoiding redundant communications and complex computations. In this paper, an autonomous communication-based hybrid state/event driven control scheme is proposed. This control scheme is hierarchical and heuristic, such that on the primary control level, it encompasses state-driven local controllers, and on the secondary control level, an event-driven MG centralized controller (MGCC) is used. This …

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Evaluating Flexibility Metrics On Simple Temporal Networks With Reinforcement Learning, Hamzah I. Khan Jan 2018

Evaluating Flexibility Metrics On Simple Temporal Networks With Reinforcement Learning, Hamzah I. Khan

HMC Senior Theses

Simple Temporal Networks (STNs) were introduced by Tsamardinos (2002) as a means of describing graphically the temporal constraints for scheduling problems. Since then, many variations on the concept have been used to develop and analyze algorithms for multi-agent robotic scheduling problems. Many of these algorithms for STNs utilize a flexibility metric, which measures the slack remaining in an STN under execution. Various metrics have been proposed by Hunsberger (2002); Wilson et al. (2014); Lloyd et al. (2018). This thesis explores how adequately these metrics convey the desired information by using them to build a reward function in a reinforcement learning …

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Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad Jan 2018

Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad

Wayne State University Dissertations

Massive amount of electronic medical records (EMRs) accumulating from patients and populations motivates clinicians and data scientists to collaborate for the advanced analytics to create knowledge that is essential to address the extensive personalized insights needed for patients, clinicians, providers, scientists, and health policy makers. Learning from large and complicated data is using extensively in marketing and commercial enterprises to generate personalized recommendations. Recently the medical research community focuses to take the benefits of big data analytic approaches and moves to personalized (precision) medicine. So, it is a significant period in healthcare and medicine for transferring to a new paradigm. …

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An Attribute Agreement Method For Hfacs Inter-Rater Reliability Assessment, Teddy Steven Cotter, Veysel Yesilbas Jan 2018

An Attribute Agreement Method For Hfacs Inter-Rater Reliability Assessment, Teddy Steven Cotter, Veysel Yesilbas

Engineering Management & Systems Engineering Faculty Publications

Inter-rater reliability can be regarded as the degree of agreement among raters on a given item or a circumstance. Multiple approaches have been taken to estimate and improve inter-rater reliability of the United States Department of Defense Human Factors Analysis and Classification System used by trained accident investigators. In this study, three trained instructor pilots used the DoD-HFACS to classify 347 U.S. Air Force Accident Investigation Board (AIB) Class-A reports between the years of 2000 and 2013. The overall method consisted of four steps: (1) train on HFACS definitions, (2) verify rating reliability, (3) rate HFACS reports, and (4) random …

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A Proposed Taxonomy For The Systems Statistical Engineering Body Of Knowledge, Teddy Steven Cotter Jan 2018

A Proposed Taxonomy For The Systems Statistical Engineering Body Of Knowledge, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

In the ASEM-IAC 2012, Cotter (2012) identified the gaps in knowledge that statistical engineering needs to address, explored additional gaps in knowledge not addressed in the prior works, and set forth a working definition of and body of knowledge for statistical engineering. In the ASEM-IAC 2015, Cotter (2015) proposed a systemic causal Bayesian hierarchical model that addressed the knowledge gap needed to integrate deterministic mathematical engineering causal models within a stochastic framework. Missing, however, is the framework for specifying the hierarchical qualitative systems structures necessary and sufficient for specifying systemic causal Bayesian hierarchical models. In the ASEM-IAC 2016, Cotter (2016) …

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Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant Jan 2018

Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant

Journal of the Arkansas Academy of Science

This paper discusses data pertaining to space missions to astronomical bodies beyond earth. The analyses provide summarizing facts and graphs obtained by mining data about (1) missions launched by all countries that go to the moon and planets, and (2) Earth satellites obtained from a Union of Concerned Scientists (UCS) dataset and lists of publically available satellite data.

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Optimal Supply Delivery Under Military Specific Constraints, Talena Fletcher Jan 2018

Optimal Supply Delivery Under Military Specific Constraints, Talena Fletcher

College of Graduate Studies: Theses & Dissertations

Through-out military history, the need to safely and effectively allocate resources to various military operations was a task of extreme importance. Satisfying the needs of multiple consumers by optimally pairing with appropriate suppliers falls into the category of vehicle routing problems (VRP), which has been intensively studied over the years. In general, finding the optimal solution to VRP is known to be NP-hard. The proposed solutions rely on mathematical programming and the size of the problems that can be optimally solved is typically limited. In military settings, balancing the needs of multiple consumers with the current operational environment has always …

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Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie Jan 2018

Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie

Theses and Dissertations

Preventing cyberterrorism is becoming a necessity for individuals, organizations, and governments. However, current policies focus on technical and managerial aspects without asking for experts and non-experts values and preferences for preventing cyberterrorism. This study employs value focused thinking and public value forum to bare strategic measures and alternatives for complex policy decisions for preventing cyberterrorism. The strategic measures and alternatives are per socio-technical process.

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Location Optimization Of A Coal Power Plant To Balance Coal Supply And Electric Transmission Costs Against Plant’S Emission Exposure, Najam Khan Jan 2018

Location Optimization Of A Coal Power Plant To Balance Coal Supply And Electric Transmission Costs Against Plant’S Emission Exposure, Najam Khan

Electronic Theses and Dissertations

This research is focused on developing a location analysis methodology that can minimize the pollutant exposure to the public while ensuring that the combined costs of electric transmission losses and coal logistics are minimized. Coal power plants will provide a critical contribution towards meeting electricity demands for various nations in the foreseeable future. The site selection for a new coal power plant is extremely important from an investment point of view. The operational costs for running a coal power plant can be minimized by a combined emphasis on placing a coal power plant near coal mines as well as customers. …

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The Impact Of Machine Learning Algorithms On Benchmarking Process In Healthcare Service Delivery, Egbe-Etu Emmanuel Etu Jan 2018

The Impact Of Machine Learning Algorithms On Benchmarking Process In Healthcare Service Delivery, Egbe-Etu Emmanuel Etu

Wayne State University Theses

Currently, organizations have adopted and implemented a variety of innovative quality management philosophies, approaches, and techniques to stay competitive in an ever-changing global economy. Benchmarking is one of such techniques deployed by organizations to stay competitive. The motivation for this research stems from a real-world problem being faced by hospitals in the healthcare industry who have amassed a ton of data and want to embark on benchmarking project to assess the performance of the emergency departments due to challenges faced with poor management of operations which has led to high patient boarding rates, high patient wait-times, poor quality service, low …

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Analyzing Sensor Based Human Activity Data Using Time Series Segmentation To Determine Sleep Duration, Yogesh Deepak Lad Jan 2018

Analyzing Sensor Based Human Activity Data Using Time Series Segmentation To Determine Sleep Duration, Yogesh Deepak Lad

Masters Theses

"Sleep is the most important thing to rest our brain and body. A lack of sleep has adverse effects on overall personal health and may lead to a variety of health disorders. According to Data from the Center for disease control and prevention in the United States of America, there is a formidable increase in the number of people suffering from sleep disorders like insomnia, sleep apnea, hypersomnia and many more. Sleep disorders can be avoided by assessing an individual's activity over a period of time to determine the sleep pattern and duration. The sleep pattern and duration can be …

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Evaluating Microgrid Effectiveness In Transitioning Energy Portfolios, Jacob Marshal Hale Jan 2018

Evaluating Microgrid Effectiveness In Transitioning Energy Portfolios, Jacob Marshal Hale

Masters Theses

"Microgrid energy systems have emerged as a potential solution to rising greenhouse gas emissions from dependence on fossil fuels. This research provides a framework for evaluating the utility of microgrids. Three key findings are presented: use of a state-of-the-art matrix (SAM) analysis to identify gaps in key research areas that inhibit wide-spread microgrid adoption, development of a system dynamics (SD) model, and a cost benefit analysis case study to evaluate microgrid feasibility in partially meeting the energy demand of a building. Governments play a central role in developing clean energy strategies. A SAM was developed to determine if key microgrid …

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Extraction Of Fiber Morphology From Sem Images For Quality Control Of Fiber Reinforced Composites Manufacturing, Md Fashiar Rahman Jan 2018

Extraction Of Fiber Morphology From Sem Images For Quality Control Of Fiber Reinforced Composites Manufacturing, Md Fashiar Rahman

Open Access Theses & Dissertations

The morphology of fibers (e.g. spatial uniformity, orientation, and length) plays a decisive role in determining the material properties or fabrication quality of fiber-reinforced nanocomposites. Hence, determining the morphology becomes a very critical issue in the field of nanocomposite quality control. The conventional way of quality inspection is to take the scanning electron microscopic (SEM) images of the cross-section of composite material and do the visual checking of these SEM images to evaluate the nanofiber alignment and length distribution. But this type of inspection is often subjective, inaccurate and time consuming. Moreover, the extremely small size of nanofibers makes the …

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Wavelet Anova Bisection Method For Identifying Simulation Model Bias, Andrew D. Atkinson, Raymond R. Hill, Joseph J. Pignatiello Jr., G. Geoffrey Vining, Edward D. White, Eric Chicken Jan 2018

Wavelet Anova Bisection Method For Identifying Simulation Model Bias, Andrew D. Atkinson, Raymond R. Hill, Joseph J. Pignatiello Jr., G. Geoffrey Vining, Edward D. White, Eric Chicken

Faculty Publications

High-resolution computer models can simulate complex systems and processes in order to evaluate a solution quickly and inexpensively. Many simulation models produce dynamic functional output, such as a set of time-series data generated during a process. These computer models require verification and validation (V&V) to assess the correctness of these simulations. In particular, the model validation effort evaluates if the model is an appropriate representation of the real-world system that it is meant to simulate. However, when assessing a model capable of generating functional output, it is useful to learn more than simply whether the model is valid or invalid. …

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Evaluating The Role Of Energy Demand Prediction And Renewable Energy Utilization On Energy Dependency Management: A Generic System Dynamics Model, Emad Rabiei Hosseinabad Jan 2018

Evaluating The Role Of Energy Demand Prediction And Renewable Energy Utilization On Energy Dependency Management: A Generic System Dynamics Model, Emad Rabiei Hosseinabad

Graduate Research Theses & Dissertations

Supplying energy has become one of the biggest concerns of developed countries due to the growing energy needs in the last decades. Security of energy supply has forced countries to rely more on energy imports from external sources, and become energy dependent to a greater extent. Utilizing available renewable energy resources has been characterized as a reliable indicator to mitigate energy dependency in countries as well as securing the supplying of energy-based needs in the future. This research explores the impact of renewable energies as trustful resources in mitigating energy imports form external sources with investigation of its viability with …

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Human-Intelligence And Machine-Intelligence Decision Governance Formal Ontology, Faisal Mahmud Jan 2018

Human-Intelligence And Machine-Intelligence Decision Governance Formal Ontology, Faisal Mahmud

Engineering Management & Systems Engineering Theses & Dissertations

Since the beginning of the human race, decision making and rational thinking played a pivotal role for mankind to either exist and succeed or fail and become extinct. Self-awareness, cognitive thinking, creativity, and emotional magnitude allowed us to advance civilization and to take further steps toward achieving previously unreachable goals. From the invention of wheels to rockets and telegraph to satellite, all technological ventures went through many upgrades and updates. Recently, increasing computer CPU power and memory capacity contributed to smarter and faster computing appliances that, in turn, have accelerated the integration into and use of artificial intelligence (AI) in …

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Artificial Olfactory System For Multi-Component Analysis Of Gas Mixtures., Alexander Aleksandrovich Larin Dec 2017

Artificial Olfactory System For Multi-Component Analysis Of Gas Mixtures., Alexander Aleksandrovich Larin

Electronic Theses and Dissertations

Gas analysis is an important part of our world and gas sensing technology is becoming more essential for various aspects of our life. A novel approach for gas mixture analysis by using portable gas chromatography in combination with an array of highly integrated and selective metal oxide (MOX) sensors has been studied. We developed a system with small size (7 x 13 x 16 inches), low power consumption (~10 W) and absence of special carrier gases designed for portable field analysis (assuming apriori calibration). Low ppb and even sub-ppb level of detection for some VOCs was achieved during the analysis …

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Law Enforcement Resource Optimization With Response Time Guarantees, Jonathan Chase, Jiali Du, Na Fu, Truc Viet Le, Hoong Chuin Lau Dec 2017

Law Enforcement Resource Optimization With Response Time Guarantees, Jonathan Chase, Jiali Du, Na Fu, Truc Viet Le, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In a security-conscious world, and with the rapid increase in the global urbanized population, there is a growing challenge for law enforcement agencies to efficiently respond to emergency calls. We consider the problem of spatially and temporally optimizing the allocation of law enforcement resources such that the quality of service (QoS) in terms of emergency response time can be guaranteed. To solve this problem, we provide a spatio-temporal MILP optimization model, which we learn from a real-world dataset of incidents and dispatching records, and solve by existing solvers. One key feature of our proposed model is the introduction of risk …

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