Physical Sciences and Mathematics Commons^™

Data Clustering Using Seed Disperser Ant Algorithm, Wen Liang Chang, Jeevan Kanesan, Anand Jayant Kulkarni, Harikrishnan Ramiah

Turkish Journal of Electrical Engineering and Computer Sciences

Nature-inspired optimization algorithms have become popular in the past decade. They have been applied to solve various kinds of problems. Among these would be data clustering, which has become popular in data mining in recent times due to the data explosion. In the last decade, many metaheuristic algorithms have been used to obtain improved data clustering optimization for solving data mining problems. In this paper, we applied the seed disperser ant algorithm (SDAA), which mimics the evolution of an Aphaenogaster senilis ant colony, and we introduced a modified SDAA that is a hybrid of K-means and SDAA for solving data …

A Modified Genetic Algorithm For A Special Case Of The Generalized Assignment Problem, Murat Dörterler, Ömer Faruk Bay, Mehmet Ali̇ Akcayol

Turkish Journal of Electrical Engineering and Computer Sciences

Many central examinations are performed nationwide in Turkey. These examinations are held simultaneously throughout Turkey. Examinees attempt to arrive at the examination centers at the same time and they encounter problems such as traffic congestion, especially in metropolises. The state of mind that this situation puts them into negatively affects the achievement and future goals of the test takers. Our solution to minimize the negative effects of this issue is to assign the test takers to closest examination centers taking into account the capacities of examination halls nearby. This solution is a special case of the generalized assignment problem (GAP). …

Comparing Of Phase Shifting Method And One-Dimensional Continuous Wavelet Transform Method For Reconstruction Using Phase-Only Information, Gülhan Ustabaş Kaya, Zehra Saraç

Turkish Journal of Electrical Engineering and Computer Sciences

The one-dimensional continuous wavelet transform method has some advantages in hologram reconstruction, when used in the only phase, compared with the phase shifting method. This paper aims to discuss these advantages. One advantage is related to image quality. Another advantage is less power spent and saving time, because the one-dimensional continuous wavelet transform method uses only one hologram and the phase shifting method uses four holograms for recording and reconstruction processes. One final advantage is that the one-dimensional continuous wavelet transform method can also be used in real-time applications. Within the context of the ongoing optimization studies, this study will …

An Improved Clonal Selection Algorithm Using A Tournament Selection Operator And Its Application To Microstrip Coupler Design, Ezgi̇ Deni̇z Ülker

Turkish Journal of Electrical Engineering and Computer Sciences

The clonal selection algorithm (CLONALG) is a nature-inspired metaheuristic algorithm that has been applied to various complex optimization problems from different fields of study. Tournament selection (TS) is a selection operator that is mainly used in genetic algorithms. In this paper, a novel improved clonal selection algorithm by using the TS operator (ICSAT) is introduced. To observe the improvement, ICSAT was first tested on selected benchmark functions and then to validate its efficiency ICSAT was applied to a microstrip coupler design problem. Although showing some disadvantages that generally exist in all modified algorithms, it is observed that ICSAT has a …

A Novel Generation And Capacitor Integration Technique For Today's Distribution Systems, Okan Özgönenel, Serap Karagöl

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, the problem of optimally placing shunt capacitors and generators in radial distribution systems is handled and a new calculation technique based on wavelet neural network (WNN), which is computationally effective compared to well-known techniques, is proposed. The objectives for the proposed method are simply selected as the minimum cost of peak power and losses and maximum voltage stability. The suggested optimization technique is tested on various IEEE radial buses and then compared to the well-known methods in the literature, i.e. golden section search, grid search, and Acharya's heuristic method. The proposed and conventional methods are applied to …

Stochastic Optimization Of Adaptive Enrichment Designs For Two Subpopulations, Aaron Fisher, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

An adaptive enrichment design is a randomized trial that allows enrollment criteria to be modified at interim analyses, based on a preset decision rule. When there is prior uncertainty regarding treatment effect heterogeneity, these trial designs can provide improved power for detecting treatment effects in subpopulations. We present a simulated annealing approach to search over the space of decision rules and other parameters for an adaptive enrichment design. The goal is to minimize the expected number enrolled or expected duration, while preserving the appropriate power and Type I error rate. We also explore the benefits of parallel computation in the …

Traffic Simulation Model For Port Planning And Congestion Prevention, Baoxiang Li, Kar Way Tan, Trong Khiem Tran

Research Collection School Of Computing and Information Systems

Effective management of land-side transportation provides the competitive advantage to port terminal operators in improving services and efficient use of limited space in an urban port. We present a hybrid simulation model that combines traffic-flow modeling and discrete-event simulation for land-side port planning and evaluation of traffic conditions for a number of what-if scenarios. We design our model based on a real-world case of a bulk cargo port. The problem is interesting due to complexity of heterogeneous closed-looped internal vehicles and external vehicles traveling in spaces with very limited traffic regulation (no traffic lights, no traffic wardens) and the traffic …

Improved 2d And 3d Resistivity Surveys Using Buried Electrodes And Optimized Arrays: The Multi-Electrode Resistivity Implant Technique (Merit), Henok Gidey Kiflu

USF Tampa Graduate Theses and Dissertations

This thesis presents a novel resistivity method called Multi-Electrode resistivity technique (MERIT) that is used for high resolution imaging of complex geologic features at depth and near the edges of survey lines. The MERIT electrodes are especially shaped and designed to be self-driven using a robust-direct push technique. Measurements are taken using optimized arrays that are generated using a modified version of the “Compare-R” optimization algorithm. This work focused on both two-dimensional (MERIT2D) and three-dimensional (MERIT3D) applications of the buried array and show the relevance of the additional information gained by the addition of deep electrodes especially in sites with …

Partitioning Uncertain Workloads, Freddy Chua, Bernardo A. Huberman

Research Collection School Of Computing and Information Systems

We present a method for determining the ratio of the tasks when breaking any complex workload in such a way that once the outputs from all tasks are joined, their full completion takes less time and exhibit smaller variance than when running on the undivided workload. To do that, we have to infer the capabilities of the processing unit executing the divided workloads or tasks. We propose a Bayesian Inference algorithm to infer the amount of time each task takes in a way that does not require prior knowledge on the processing unit capability. We demonstrate the effectiveness of this …

Computer-Aided Design Of Algorithms Of Pulsed Control Of Arc Welding Process Based On Numerical Simulation, Oksana I. Shpigunova, Anatoliy A. Glazunov

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Optimization And Coding Of A Lcls Control Program, Tanner M. Worden

STAR Program Research Presentations

SLAS’s, Linac Coherent Light Source (LCLS) also known as X-ray free-electron laser (XFEL) is the first X-ray laser of its kind. It gave Scientist from around the world the unique ability to observe the world at a subatomic level. Allowing for major advancements in the field of biological chemistry, drug science, material science and many more. Since the LCLS is a fairly unique scientific instrument, the demand for its use by the scientific community has always been high since it turned on back in 2009. This means that any and all time that the laser is not being used for …

Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong

Research Collection School Of Computing and Information Systems

Purpose: Many manufacturing companies that ship goods through full container loads found themselves under-utilizing the containers and resulting in higher carbon footprint per volume shipment. One of the reasons is the choice of non-ideal container sizes for their shipments. Consolidation fills up the containers more efficiently that reduces the overall carbon footprint. The objective of this paper is to support decisions on selection of appropriate combination of container sizes and shipment consolidation for a manufacturing company. We develop two-steps model which first takes the volumes to be shipped as an input and provide the combination of container sizes required; then …

Prediction And Optimal Scheduling Of Advertisements In Linear Television, Mark J. Panaggio, Pak-Wing Fok, Ghan S. Bhatt, Simon Burhoe, Michael Capps, Christina J. Edholm, Fadoua El Moustaid, Tegan Emerson, Star-Lena Estock, Nathan Gold, Ryan Halabi, Madelyn Houser, Peter R. Kramer, Hsuan-Wei Lee, Qingxia Li, Weiqiang Li, Dan Lu, Yuzhou Qian, Louis F. Rossi, Deborah Shutt, Vicky Chuqiao Yang, Yingxiang Zhou

Mathematical Sciences Faculty Research

Advertising is a crucial component of marketing and an important way for companies to raise awareness of goods and services in the marketplace. Advertising campaigns are designed to convey a marketing image or message to an audience of potential consumers and television commercials can be an effective way of transmitting these messages to a large audience. In order to meet the requirements for a typical advertising order, television content providers must provide advertisers with a predetermined number of "impressions" in the target demographic. However, because the number of impressions for a given program is not known a priori and because …

Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis

The Summer Undergraduate Research Fellowship (SURF) Symposium

Multi-objective optimization (MOO) problems arise frequently in science and engineering situations. In an optimization problem, we want to find the set of input parameters that generate the set of optimal outputs, mathematically known as the Pareto frontier (PF). Solving the MOO problem is a challenge since expensive experiments can be performed only a constrained number of times and there is a limited set of data to work with, e.g. a roll-to-roll microwave plasma chemical vapor deposition (MPCVD) reactor for manufacturing high quality graphene. State-of-the-art techniques, e.g. evolutionary algorithms; particle swarm optimization, require a large amount of observations and do not …

Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan

Doctoral Dissertations

With the explosive increase in the amount of data being generated by various applications, large-scale distributed and parallel storage systems have become common data storage solutions and been widely deployed and utilized in both industry and academia. While these high performance storage systems significantly accelerate the data storage and retrieval, they also bring some critical issues in system maintenance and management. In this dissertation, I propose three methodologies to address three of these critical issues.

First, I develop an optimal resource management and spare provisioning model to minimize the impact brought by component failures and ensure a highly operational experience …

Automated Microscopy Platform For High-Throughput Analysis Of Cellular Characteristics, Hussam Ibrahim

Physics: Student Scholarship & Creative Works

Existing microscopy platforms allow analysis post-hoc, but not in real time. This is an issue in the world of Bioengineering because you are limited to performing further analysis on specimen. The aim of my research was to design a sophisticated system whereby information can be exchanged between the software which acquires images and software that analyzes the images immediately after acquisition. In this system, images would be acquired by the microscope and analyzed by customized scripts (MATLAB, Mathworks) in real time. Specifically, MATLAB would wait for new images to be saved on the hard drive, import these images, and perform …

A Multi-Objective Approach To Tactical Maneuvering Within Real Time Strategy Games, Christopher D. Ball

Theses and Dissertations

The real time strategy (RTS) environment is a strong platform for simulating complex tactical problems. The overall research goal is to develop artificial intelligence (AI) RTS planning agents for military critical decision making education. These agents should have the ability to perform at an expert level as well as to assess a players critical decision-making ability or skill-level. The nature of the time sensitivity within the RTS environment creates very complex situations. Each situation must be analyzed and orders must be given to each tactical unit before the scenario on the battlefield changes and makes the decisions no longer relevant. …

Model For The Electrolysis Of Water And Its Use For Optimization, Roger Lascorz, Javier E. Hasbun Dr

Georgia Journal of Science

The goal of this research was to study the optimization of the electrolysis of water both theoretically and experimentally. For accuracy, 3 hr experiments were made with measurements recorded every 15 min. The results show that a better model than the classical one is needed for water electrolysis. A new model that fits experimental data better is proposed. The results of this new model not only predict hydrogen production in electrolysis of water better, but show a way to predict gas production of any liquid as well as what voltage to use to optimize it.

Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for …

Geometric Aspects And Auxiliary Features To Top-K Processing [Advanced Seminar], Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Top-k processing is a well-studied problem with numerous applications that is becoming increasingly relevant with the growing availability of recommendation systems and decision making software on PCs, PDAs and smart-phones. The objective of this seminar is twofold. First, we will delve into the geometric aspects of top-k processing. Second, we will cover complementary features to top-k queries that have a strong geometric nature. The seminar will close with insights in the effect of dimensionality on the meaningfulness of top-k queries, and interesting similarities to nearest neighbor search.

A General Framework Of Large-Scale Convex Optimization Using Jensen Surrogates And Acceleration Techniques, Soysal Degirmenci

McKelvey School of Engineering Theses & Dissertations

In a world where data rates are growing faster than computing power, algorithmic acceleration based on developments in mathematical optimization plays a crucial role in narrowing the gap between the two. As the scale of optimization problems in many fields is getting larger, we need faster optimization methods that not only work well in theory, but also work well in practice by exploiting underlying state-of-the-art computing technology.

In this document, we introduce a unified framework of large-scale convex optimization using Jensen surrogates, an iterative optimization method that has been used in different fields since the 1970s. After this general treatment, …

Robust Influence Maximization, Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar

Research Collection School Of Computing and Information Systems

Influence Maximization is the problem of finding a fixed size set of nodes, which will maximize the expected number of influenced nodes in a social network. The number of influenced nodes is dependent on the influence strength of edges that can be very noisy. The noise in the influence strengths can be modeled using a random noise or adversarial noise model. It has been shown that all random processes that independently affect edges of the graph can be absorbed into the activation probabilities themselves and hence random noise can be captured within the independent cascade model. On the other hand, …

Improving Ventricular Catheter Design Through Computational Fluid Dynamics, Sofy Hefets Weisenberg

Masters Theses

Cerebrospinal fluid (CSF) shunts are fully implantable medical devices that are used to treat patients suffering from conditions characterized by elevated intracranial pressure, such as hydrocephalus. In cases of shunt failure or malfunction, patients are often required to endure one or more revision surgeries to replace all or part of the shunt. One of the primary causes of CSF shunt failure is obstruction of the ventricular catheter, a component of the shunt system implanted directly into the brain's ventricular system. This work aims to improve the design of ventricular catheters in order to reduce the incidence of catheter obstruction and …

Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study the problem of optimizing the trajectories of agents moving over a network given their preferences over which nodes to visit subject to operational constraints on the network. In our running example, a theme park manager optimizes which attractions to include in a day-pass to maximize the pass’s appeal to visitors while keeping operational costs within budget. The first challenge in this combinatorial optimization problem is that it involves quantities (expected visit frequencies of each attraction) that cannot be expressed analytically, for which we use the Sample Average Approximation. The second challenge is that while sampling is typically done …

Optimal Scheduling Of Pev Charging/Discharging In Microgrids With Combined Objectives, Chong Cao, Ming Cheng, Bo Chen

Michigan Tech Publications

While renewable power generation and vehicle electrification are promising solutions to reduce greenhouse gas emissions, it faces great challenges to effectively integrate them in a power grid. The weather-dependent power generation of renewable energy sources, such as Photovoltaic (PV) arrays, could introduce significant intermittency to a power grid. Meanwhile, uncontrolled PEV charging may cause load surge in a power grid. This paper studies the optimization of PEV charging/discharging scheduling to reduce customer cost and improve grid performance. Optimization algorithms are developed for three cases: 1) minimize cost, 2) minimize power deviation from a pre-defined power profile, and 3) combine objective …

An Optimized Multiple Right-Hand Side Dslash Kernel For Intel Xeon Phi, Aaron Walden

Computer Science Theses & Dissertations

Lattice quantum chromodynamics (LQCD) stands unique as the only computationally tractable, non-perturbative, and model-independent quantum field theory of the strong nuclear force. The computational core of LQCD is the Wilson Dslash operator, a nearest neighbor stencil operator summing matrix-vector multiplications over lattice points, whose performance is bandwidth-bound on most architectures. Reportedly, up to 90\% of LQCD running time may be spent computing Dslash. In recent years, efforts have been made by researchers to optimize LQCD calculations for floating point coprocessor cards such as GPUs and Intel Xeon Phi Knights Corner (KNC), which boast powerful vector processing units. Most of these …

Enabling Optimizations Through Demodularization, Blake Dennis Johnson

Theses and Dissertations

Programmers want to write modular programs to increase maintainability and create abstractions, but modularity hampers optimizations, especially when modules are compiled separately or written in different languages. In languages with syntactic extension capabilities, each module in a program can be written in a separate language, and the module system must ensure that the modules interoperate correctly. In Racket, the module system ensures this by separating module code into phases for runtime and compile-time and allowing phased imports and exports inside modules. We present an algorithm, called demodularization, that combines all executable code from a phased modular program into a single …

Probability Models For Health Care Operations With Application To Emergency Medicine, Azaz Bin Sharif

Electronic Thesis and Dissertation Repository

This thesis consists of four contributing chapters; two of which are inspired by practical problems related to emergency department (ED) operations management and the remaining two are motivated by the theoretical problem related to the time-dependent priority queue. Unlike classical priority queue, priorities in the time-dependent priority queue depends on the amount of time an arrival waits for service in addition to the priority class they belong. The mismatch between the demand for ED services and the available resources have direct and indirect negative consequences. Moreover, ED physician pay in some jurisdictions reflects pay-for-performance contracts based on operational benchmarks. To …

Cost Optimization With Solar And Conventional Energy Production, Energy Storage, And Real Time Pricing, Ata Raziei, Kevin Hallinan, Robert Brecha

Robert J. Brecha

Research is presented that investigates the potential for solar power generation with battery energy storage for reducing the effective cost of energy delivered to residential customers if real time pricing is present. A linear optimization approach is developed based upon a two-step process. In step one, given a specified solar array area and battery capacity, the optimal means to meet loads based upon grid power, solar power, and/or battery power is determined. This analysis considers an expected lifespan of the solar panel. With these results established, in the next step, the capital costs for the solar arrays and batteries are …

Multiagent Based Algorithmic Approach For Fast Response In Railway Disaster Handling, Poulami Dalapati, Arambam James Singh, Animesh Dutta

Research Collection School Of Computing and Information Systems

Disaster management in railway network is an important issue. It requires to minimize negative impact and also fast, efficient recovery from the disturbances. The main challenge here is that, the effect of inconvenience spreads out very fast in time and space. It takes noticeable amount of time to get back everything in the previous situation. This paper proposes a multi agent based algorithmic approach for disaster handling in Railway Network. This takes care of fast response to get total number of affected trains in a fast and efficient manner. We propose few algorithms to handle this situation and simulate it …