Computer Sciences Commons^™

Abnormal Event Detection In Crowded Scenes Via Bag-Of-Atomic-Events-Based Topic Model, Xing Hu, Shiqiang Hu, Lingkun Luo, Guoxiang Li

Turkish Journal of Electrical Engineering and Computer Sciences

crowded scenes. A new concept of atomic event is introduced into this framework, which is the basic component of video events. Different from previous bag-of-words (BoW) modeling-based methods that represent feature descriptors using only one code word, a feature descriptor is represented using a few more atomic events in bag-of-atomic-events (BoAE) modeling. Consequently, the approximation error is reduced by using the obtained BoAE representation. In the context of abnormal event detection, BoAE representation is more suitable to describe abnormal events than BoW representation, because the abnormal event may not correspond to any code word in BoW modeling. Fast latent Dirichlet …

Effects Of Mica2-Based Discrete Energy Levels On The Lifetime Of Cooperation Neighbor Sensor Networks, Zeydi̇n Pala

Turkish Journal of Electrical Engineering and Computer Sciences

using Mica2 mote discrete power levels on neighbor sensor network lifetime. We built a linear programming framework to qualify the cooperation of sensor networks using a discrete energy model in comparison to noncooperating networks. Our results showed that a wireless sensor neighbor network that uses a discrete radio model can be more energy efficient than a network that uses a nondiscrete energy model.

Dynamic Characteristics Of An Isolated Self-Excited Synchronous Reluctance Generator Driven By A Wind Turbine, Mosaad Mohiedden Ali, Said Mahmoud Allam, Talaat Hamdan Abdel-Moneim

Turkish Journal of Electrical Engineering and Computer Sciences

This paper studies the dynamic characteristics of an isolated three-phase self-excited synchronous reluctance generator (SESRG) driven by a variable-speed wind turbine under different operating conditions. Self-excitation is achieved via capacitors connected across the generator terminals. A detailed mathematical modeling of the proposed self-excited wind generation system is presented. The proposed analysis is based on the dynamic qd-axis model of the SESRG. Magnetic saturation is taken into account and is assumed to be confined to the direct axis and is accounted for as a variable direct-axis magnetizing reactance. Effect of wind-speed variation, excitation-capacitance variation, and loading-conditions variation on the generated output …

Impacts Of Soil Type And Moisture On The Capacity Of Multi-Carrier Modulation In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran

School of Computing: Conference and Workshop Papers

Unique interactions between soil and communication components in wireless underground communications necessitate revisiting fundamental communication concepts from a different perspective. In this paper, capacity profile of wireless underground (UG) channel for multi-carrier transmission techniques is analyzed based on empirical antenna return loss and channel frequency response models in different soil types and moisture values. It is shown that data rates in excess of 124 Mbps are possible for distances up to 12 m. For shorter distances and lower soil moisture conditions, data rates of 362 Mbps can be achieved. It is also shown that due to soil moisture variations, UG …

Table Headers: An Entrance To The Data Mine, George Nagy, Sharad C. Seth

School of Computing: Conference and Workshop Papers

Algorithmic methods are demonstrated for information extraction from table header elements, including data categories and data hierarchies. The table headers are found with the Minimum Index Point Search algorithm. The header-path alignment and header completion algorithms yield database-ready table content and configuration statistics on a random sample of 400 diverse tables with ground truth and 1120 tables without ground truth from international statistical data sites.

Hydro-Geological Flow Analysis Using Hidden Markov Models, Chandrahas Raj Venkat Gurram

Theses and Dissertations

Hidden Markov Models a class of statistical models used in various disciplines for understanding speech, finding different types of genes responsible for cancer and much more. In this thesis, Hidden Markov Models are used to obtain hidden states that can correlate the flow changes in the Wakulla Spring Cave. Sensors installed in the tunnels of Wakulla Spring Cave have recorded huge correlated changes in the water flows at numerous tunnels. Assuming the correlated flow changes are a consequence of system being in a set of discrete states, a Hidden Markov Model is calculated. This model comprising all the sensors installed …

Regular Expression Synthesis For Blast Two-Hit Filtering, Jordan Bradshaw

Theses and Dissertations

Genomic databases are exhibiting a growth rate that is outpacing Moore's Law, which has made database search algorithms a popular application for use on emerging processor technologies. NCBI BLAST is the standard tool for performing searches against these databases, which operates by transforming each database query into a filter that is subsequently applied to the database. This requires a database scan for every query, fundamentally limiting its performance by I/O bandwidth. In this dissertation we present a functionally-equivalent variation on the NCBI BLAST algorithm that maps more suitably to an FPGA implementation. This variation of the algorithm attempts to reduce …

Efficient Partitioning And Allocation Of Data For Workflow Compositions, Annamaria Victoria Kish

Theses and Dissertations

Our aim is to provide efficient partitioning and allocation of data for web service compositions. Web service compositions are represented as partial order database transactions. We accommodate a variety of transaction types, such as read-only and write-oriented transactions, to support workloads in cloud environments. We introduce an approach that partitions and allocates small units of data, called micropartitions, to multiple database nodes. Each database node stores only the data needed to support a specific workload. Transactions are routed directly to the appropriate data nodes. Our approach guarantees serializability and efficient execution.

In Phase 1, we cluster transactions based on data …

Computational Doping For Fuel Cell Material Design Based On Genetic Algorithms And Genetic Programming, Emrah Atilgan

Theses and Dissertations

Developing new materials have historically been time-consuming. Computational material discovery can search large design space to identify promising candidates for experimental verification. Recently, Density Functional Theory (DFT) based first principle calculation has been able to calculate many electrical and physical properties of materials, making them suitable for computational doping based material discovery. In material doping, given a base material, one can change its properties by substituting some elements with new ones or adding additional elements. In computational doping, we have a grid of atoms in a supercell, some of which can be substituted with dopant atoms. There are many possible …

An Efficient Solution To The Mixed Shop Scheduling Problem Using A Modified Genetic Algorithm, V. Nguyen, H. P. Bao

Mechanical & Aerospace Engineering Faculty Publications

The mixed job shop scheduling problem is one in which some jobs have fixed machine orders and other jobs may be processed in arbitrary orders. In past literature, optimal solutions have been proposed based on adaptations of classical solutions such as by Johnson, Thompson and Giffler among many others, by pseudopolynomial algorithms, by simulation, and by Genetic Algorithms (GA). GA based solutions have been proposed for flexible Job shops. This paper proposes a GA algorithm for the mixed job shop scheduling problem. The paper starts with an analysis of the characteristics of the so-called mixed shop problem. Based on those …

Challenging The Efficient Market Hypothesis With Dynamically Trained Artificial Neural Networks, Kevin M. Harper

UNF Graduate Theses and Dissertations

A review of the literature applying Multilayer Perceptron (MLP) based Artificial Neural Networks (ANNs) to market forecasting leads to three observations: 1) It is clear that simple ANNs, like other nonlinear machine learning techniques, are capable of approximating general market trends 2) It is not clear to what extent such forecasted trends are reliably exploitable in terms of profits obtained via trading activity 3) Most research with ANNs reporting profitable trading activity relies on ANN models trained over one fixed interval which is then tested on a separate out-of-sample fixed interval, and it is not clear to what extent these …

Locality-Aware Dynamic Task Graph Scheduling, Jordyn Maglalang, Sriram Krishnamoorthy, Kunal Agrawal

All Computer Science and Engineering Research

Dynamic task graph schedulers automatically balance work across processor cores by scheduling tasks among available threads while preserving dependences. In this paper, we design NabbitC, a provably efficient dynamic task graph scheduler that accounts for data locality on NUMA systems. NabbitC allows users to assign a color to each task representing the location (e.g., a processor core) that has the most efficient access to data needed during that node’s execution. NabbitC then automatically adjusts the scheduling so as to preferentially execute each node at the location that matches its color—leading to better locality because the node is likely to make …

Geometric Consideration Of Nanostructures For Energy Storage Systems, Jonghyun Park, Jie Li, Wei Lu, Ann Marie Sastry

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Battery performance and its fade are determined by various aspects such as the transport of ions and electrons through heterogeneous internal structures; kinetic reactions at the interfaces; and the corresponding interplay between mechanical, chemical, and thermal responses. The fundamental factor determining this complex multiscale and multiphysical nature of a battery is the geometry of active materials. In this work, we systematically consider the tradeoffs among a selection of limiting geometries of media designed to store ions or other species via a diffusion process. Specifically, we begin the investigation by considering diffusion in spheres, rods, and plates at the particle level, …

Coupled Crystal Orientation-Size Effects On The Strength Of Nano Crystals, Rui Yuan, Irene J. Beyerlein, Caizhi Zhou

Materials Science and Engineering Faculty Research & Creative Works

We study the combined effects of grain size and texture on the strength of nanocrystalline copper (Cu) and nickel (Ni) using a crystal-plasticity based mechanics model. Within the model, slip occurs in discrete slip events exclusively by individual dislocations emitted statistically from the grain boundaries. We show that a Hall-Petch relationship emerges in both initially texture and non-textured materials and our values are in agreement with experimental measurements from numerous studies. We find that the Hall-Petch slope increases with texture strength, indicating that preferred orientations intensify the enhancements in strength that accompany grain size reductions. These findings reveal that texture …

Information-Theoretic Secure Outsourced Computation In Distributed Systems, Zhaohong Wang

Theses and Dissertations--Electrical and Computer Engineering

Secure multi-party computation (secure MPC) has been established as the de facto paradigm for protecting privacy in distributed computation. One of the earliest secure MPC primitives is the Shamir's secret sharing (SSS) scheme. SSS has many advantages over other popular secure MPC primitives like garbled circuits (GC) -- it provides information-theoretic security guarantee, requires no complex long-integer operations, and often leads to more efficient protocols. Nonetheless, SSS receives less attention in the signal processing community because SSS requires a larger number of honest participants, making it prone to collusion attacks. In this dissertation, I propose an agent-based computing framework using …

An Autoencoder-Based Image Descriptor For Image Matching And Retrieval, Chenyang Zhao

Browse all Theses and Dissertations

Local image features are used in many computer vision applications. Many point detectors and descriptors have been proposed in recent years; however, creation of effective descriptors is still a topic of research. The Scale Invariant Feature Transform (SIFT) developed by David Lowe is widely used in image matching and image retrieval. SIFT detects interest points in an image based on Scale-Space analysis, which is invariant to change in image scale. A SIFT descriptor contains gradient information about an image patch centered at a point of interest. SIFT is found to provide a high matching rate, is robust to image transformations; …

Intelligent Caching To Mitigate The Impact Of Web Robots On Web Servers, Howard Nathan Rude

Browse all Theses and Dissertations

With an ever increasing amount of data that is shared and posted on the Web, the desire and necessity to automatically glean this information has led to an increase in the sophistication and volume of software agents called web robots or crawlers. Recent measurements, including our own across the entire logs of Wright State University Web servers over the past two years, suggest that at least 60\% of all requests originate from robots rather than humans. Web robots display different statistical and behavioral patterns in their traffic compared to humans, yet present Web server optimizations presume that traffic exhibits predominantly …

The Woz Recognizer: A Tool For Understanding User Perceptions Of Sketch-Based Interfaces, Jared Bott

Electronic Theses and Dissertations

Sketch recognition has the potential to be an important input method for computers in the coming years; however, designing and building an accurate and sophisticated sketch recognition system is a time consuming and daunting task. Since sketch recognition is still at a level where mistakes are common, it is important to understand how users perceive and tolerate recognition errors and other user interface elements with these imperfect systems. A problem in performing this type of research is that we cannot easily control aspects of recognition in order to rigorously study the systems. We performed a study examining user perceptions of …

Optimal Digital Control Of A Three-Phase Four-Leg Voltage Source Inverter, Ayhan Özdemi̇r, Zeki̇ye Erdem

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Techniques For Automated Parameter Estimation In Computational Models Of Probabilistic Systems, Faraz Hussain

Electronic Theses and Dissertations

The main contribution of this dissertation is the design of two new algorithms for automatically synthesizing values of numerical parameters of computational models of complex stochastic systems such that the resultant model meets user-specified behavioral specifications. These algorithms are designed to operate on probabilistic systems – systems that, in general, behave differently under identical conditions. The algorithms work using an approach that combines formal verification and mathematical optimization to explore a model's parameter space. The problem of determining whether a model instantiated with a given set of parameter values satisfies the desired specification is first defined using formal verification terminology, …

Transcriptional And Post-Transcriptional Regulation Of Gene Expression, Jun Ding

Electronic Theses and Dissertations

Regulation of gene expression includes a variety of mechanisms to increase or decrease specific gene products. Gene expression can be regulated at any stage from transcription to post-transcription and it's essential to almost all living organisms, as it increases the versatility and adaptability by allowing the cell to express the needed proteins. In this dissertation, we comprehensively studied the gene regulation from both transcriptional and post-transcriptional points of view. Transcriptional regulation is by which cells regulate the transcription from DNA to RNA, thereby directing gene activity. Transcriptional factors (TFs) play a very important role in transcriptional regulation and they are …

Optimization Of Automatic Steering Control On A Vehiclewith A Steer-By-Wire System Using Particle Swarm Optimization, Fachrudin Hunaini, Imam Robandi, Nyoman Sutantra

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a simulation of the automatic steering control system on a vehicle model using particle swarm optimization (PSO) to optimize the parameters of the control system. The control system involves fuzzy logic control (FLC) and proportional-integral-derivative (PID) control working in a cascade; the main control (FLC) is used to control lateral motion, and the secondary control (PID) is an enhancement to control the yaw motion in vehicle models representing 10 degrees of freedom of the vehicle dynamics system. Optimization by PSO is carried out simultaneously on both control systems. On FLC it is done by setting the width …

Design Of A Fuzzy Logic Controlled Thermoelectric Brain Hypothermia System, Abdullah Hakan Yavuz

Turkish Journal of Electrical Engineering and Computer Sciences

Brain cooling in medicine is the most effective method in protecting brain cells during strokes, heart attacks, and brain traumas. This method, called brain hypothermia, is based on the principle that the brain is superficially cooled under controlled conditions in order to minimize cell death. In this study a helmet was designed to locally cool the brain and an effective controller was designed and tested using fuzzy logic in order to test the effectiveness of the helmet for brain hypothermia. For testing the cooling and heating performances of the helmet, currents between 0 and 60 A were applied to the …

Improving Fairness In Peer-To-Peer Networks By Separating The Role Of Seeders In Network Infrastructures, Alireza Naghizadeh

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Energy-Efficient And Environmentally Friendly Power Dispatch By Trigeneration With Renewable Energy And Energy Storage, Faisal Pazheri, Mohd Fauzi Othman, Nazar H. Malik, Abdulrehman Ali Al-Arainy

Turkish Journal of Electrical Engineering and Computer Sciences

The importance of energy-efficient power generation that effectively utilizes the available fossil fuels is increasing due to the gradual decline in fossil fuel reserves. Furthermore, concern about global warming has led to rapid growth in renewable energy and energy storage technologies. This trend is encouraging power utilities to effectively exploit the use of renewable energy resources (RESs) and energy storage facilities (ESFs) for power supply systems. In this regards, trigeneration in the presence of RESs and ESFs can play an important role for efficient and clean power dispatch. This paper discusses the optimum power dispatch using a hybrid power plant …

Low Budget Forensic Drive Imaging Using Arm Based Single Board Computers, Eric Olson, Narasimha Shashidhar

Journal of Digital Forensics, Security and Law

Traditional forensic analysis of hard disks and external media typically involves a powered down machine and “dead analysis” of these devices. Forensic acquisition of hard drives and external media has traditionally been by one of several means: standalone forensic duplicator; using a hardware write-blocker or dock attached to a laptop, computer, workstation, etc., forensic operating systems that live boot from a USB, CD/DVD or virtual machines with preinstalled operating systems. Standalone forensics acquisition and imaging devices generally cost thousands of dollars. In this paper, we propose the use of single board computers as forensic imaging devices. Single board computers can …

In-The-Wild Residual Data Research And Privacy, William B. Glisson, Tim Storer, Andrew Blyth, George Grispos, Matt Campbell

Journal of Digital Forensics, Security and Law

As the world becomes increasingly dependent on technology, researchers in both industry and academia endeavor to understand how technology is used, the impact it has on everyday life, the artifact life-cycle and overall integrations of digital information. In doing so, researchers are increasingly gathering 'real-world' or 'in-the-wild' residual data, obtained from a variety of sources, without the explicit consent of the original owners. This data gathering raises significant concerns regarding privacy, ethics and legislation, as well as practical considerations concerning investigator training, data storage, overall security and data disposal. This research surveys recent studies of residual data gathered in-the-wild and …

Bytewise Approximate Matching: The Good, The Bad, And The Unknown, Vikram S. Harichandran, Frank Breitinger, Ibrahim Baggili

Journal of Digital Forensics, Security and Law

Hash functions are established and well-known in digital forensics, where they are commonly used for proving integrity and file identification (i.e., hash all files on a seized device and compare the fingerprints against a reference database). However, with respect to the latter operation, an active adversary can easily overcome this approach because traditional hashes are designed to be sensitive to altering an input; output will significantly change if a single bit is flipped. Therefore, researchers developed approximate matching, which is a rather new, less prominent area but was conceived as a more robust counterpart to traditional hashing. Since the conception …

Security Analysis Of Mvhash-B Similarity Hashing, Donghoon Chang, Somitra Sanadhya, Monika Singh

Journal of Digital Forensics, Security and Law

In the era of big data, the volume of digital data is increasing rapidly, causing new challenges for investigators to examine the same in a reasonable amount of time. A major requirement of modern forensic investigation is the ability to perform automatic filtering of correlated data, and thereby reducing and focusing the manual effort of the investigator. Approximate matching is a technique to find “closeness” between two digital artifacts. mvHash-B is a well-known approximate matching scheme used for finding similarity between two digital objects and produces a ‘score of similarity’ on a scale of 0 to 100. However, no security …

An Automated Approach For Digital Forensic Analysis Of Heterogeneous Big Data, Hussam Mohammed, Nathan Clarke, Fudong Li

Journal of Digital Forensics, Security and Law

The major challenges with big data examination and analysis are volume, complex interdependence across content, and heterogeneity. The examination and analysis phases are considered essential to a digital forensics process. However, traditional techniques for the forensic investigation use one or more forensic tools to examine and analyse each resource. In addition, when multiple resources are included in one case, there is an inability to cross-correlate findings which often leads to inefficiencies in processing and identifying evidence. Furthermore, most current forensics tools cannot cope with large volumes of data. This paper develops a novel framework for digital forensic analysis of heterogeneous …