Physical Sciences and Mathematics Commons^™

A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko

Dissertations

To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively more-correct. …

Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao

Posters-at-the-Capitol

Gaze tracking has become an established technology that enables using an individual’s gaze as an input signal to support a variety of applications in the context of Human-Computer Interaction. Gaze tracking primarily relies on sensing devices such as infrared (IR) cameras. Nevertheless, in the recent years, several attempts have been realized at detecting gaze by acquiring and processing images acquired from standard RGB cameras. Nowadays, there are only a few publicly available open-source libraries and they have not been tested extensively. In this paper, we present the result of a comparative analysis that studied a commercial eye-tracking device using IR …

Robotic Olfactory-Based Navigation With Mobile Robots, Lingxiao Wang

Doctoral Dissertations and Master's Theses

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. It has been viewed as challenging due to the turbulent nature of airflows and the resulting odor plume characteristics. The key to correctly finding an odor source is designing an effective olfactory-based navigation algorithm, which guides the robot to detect emitted odor plumes as cues in finding the source. This dissertation proposes three kinds of olfactory-based navigation methods to improve search efficiency while maintaining a low computational cost, incorporating different machine learning and artificial intelligence methods.

A. …

Tooth Position Determination By Automatic Cutting And Marking Of Dental Panoramic X-Ray Film In Medical Image Processing, Yen-Cheng Huang, Chiung-An Chen, Tsung-Yi Chen, He-Sheng Chou, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Szu-Yin Lin, Chun-Wei Li, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo

Department of Information Systems & Computer Science Faculty Publications

This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, …

Messiness: Automating Iot Data Streaming Spatial Analysis, Christopher White, Atilio Barreda Ii

Publications and Research

The spaces we live in go through many transformations over the course of a year, a month, or a day; My room has seen tremendous clutter and pristine order within the span of a few hours. My goal is to discover patterns within my space and formulate an understanding of the changes that occur. This insight will provide actionable direction for maintaining a cleaner environment, as well as provide some information about the optimal times for productivity and energy preservation.

Using a Raspberry Pi, I will set up automated image capture in a room in my home. These images will …

Computational Solutions To Exosomal Microrna Biomarker Detection In Pancreatic Cancer, Thuy T. An

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Pancreatic cancer is the fourth leading cause of cancer death in the United States and the 5-year survival rate is only 5% to 10%. There are only a few non-specific symptoms associated with the early-stage cancer, therefore most patients are diagnosed in a late stage. Due to the lack of effective treatments and the fact that the early stage has a 39% 5-year survival rate, the biggest hope to control this disease is early detection. Therefore, discovery of effective and reliable non-invasive biomarkers for early detection of pancreatic cancer has been a major topic. Very recently, exosomal microRNAs have become …

Semantically Meaningful Sentence Embeddings, Rojina Deuja

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Text embedding is an approach used in Natural Language Processing (NLP) to represent words, phrases, sentences, and documents. It is the process of obtaining numeric representations of text to feed into machine learning models as vectors (arrays of numbers). One of the biggest challenges in text embedding is representing longer text segments like sentences. These representations should capture the meaning of the segment and the semantic relationship between its constituents. Such representations are known as semantically meaningful embeddings. In this thesis, we seek to improve upon the quality of sentence embeddings that capture semantic information.

The current state-of-the-art models are …

A Human-Embodied Drone For Dexterous Aerial Manipulation, Dongbin Kim

UNLV Theses, Dissertations, Professional Papers, and Capstones

Current drones perform a wide variety of tasks in surveillance, photography, agriculture, package delivery, etc. However, these tasks are performed passively without the use of human interaction. Aerial manipulation shifts this paradigm and implements drones with robotic arms that allow interaction with the environment rather than simply sensing it. For example, in construction, aerial manipulation in conjunction with human interaction could allow operators to perform several tasks, such as hosing decks, drill into surfaces, and sealing cracks via a drone. This integration with drones will henceforth be known as dexterous aerial manipulation.

Our recent work integrated the worker’s experience into …

Respiratory Compensated Robot For Liver Cancer Treatment: Design, Fabrication, And Benchtop Characterization, Mishek Jair Musa

Graduate Theses and Dissertations

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death in the world. Radiofrequency ablation (RFA) is an effective method for treating tumors less than 5 cm. However, manually placing the RFA needle at the site of the tumor is challenging due to the complicated respiratory induced motion of the liver. This paper presents the design, fabrication, and benchtop characterization of a patient mounted, respiratory compensated robotic needle insertion platform to perform percutaneous needle interventions. The robotic platform consists of a 4-DoF dual-stage cartesian platform used to control the pose of a 1-DoF needle insertion module. The active …

Comparative Analysis Of Kmer Counting And Estimation Tools, Ankitha Vejandla

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The rapid development of next-generation sequencing (NGS) technologies for determining the sequence of DNA has revolutionized genome research in recent years. De novo assemblers are the most commonly used tools to perform genome assembly. Most of the assemblers use de Bruijn graphs that break the sequenced reads into smaller sequences (sub-strings), called kmers, where k denotes the length of the sub-strings. The kmer counting and analysis of kmer frequency distribution are important in genome assembly. The main goal of this research is to provide a detailed analysis of the performance of different kmer counting and estimation tools that are currently …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler

Computer Science and Computer Engineering Undergraduate Honors Theses

Sounds with a high level of stationarity, also known as sound textures, have perceptually relevant features which can be captured by stimulus-computable models. This makes texture-like sounds, such as those made by rain, wind, and fire, an appealing test case for understanding the underlying mechanisms of auditory recognition. Previous auditory texture models typically measured statistics from auditory filter bank representations, and the statistics they used were somewhat ad-hoc, hand-engineered through a process of trial and error. Here, we investigate whether a better auditory texture representation can be obtained via contrastive learning, taking advantage of the stationarity of auditory textures to …

Material Handling With Embodied Loco-Manipulation, Jean Chagas Vaz

UNLV Theses, Dissertations, Professional Papers, and Capstones

Material handling is an intrinsic component of disaster response. Typically, first responders, such as firefighters and/or paramedics, must carry, push, pull, and handle objects, facilitating the transportation of goods. For many years, researchers from around the globe have sought to enable full-sized humanoid robots to perform such essential material handling tasks. This work aims to tackle current limitations of humanoids in the realm of interaction with common objects such as carts, wheelbarrows, etc. Throughout this research, many methods will be applied to ensure a stable Zero Moment Point (ZMP) trajectory to allow a robust gait while loco-manipulating a cart. The …

Evaluation Of Robust Deep Learning Pipelines Targeting Low Swap Edge Deployment, David Carter Cornett

Masters Theses

The deep learning technique of convolutional neural networks (CNNs) has greatly advanced the state-of-the-art for computer vision tasks such as image classification and object detection. These solutions rely on large systems leveraging wattage-hungry GPUs to provide the computational power to achieve such performance. However, the size, weight and power (SWaP) requirements of these conventional GPU-based deep learning systems are not suitable when a solution requires deployment to so called "Edge" environments such as autonomous vehicles, unmanned aerial vehicles (UAVs) and smart security cameras.

The objective of this work is to benchmark FPGA-based alternatives to conventional GPU systems that have the …

Data-Driven Operational And Safety Analysis Of Emerging Shared Electric Scooter Systems, Qingyu Ma

Computational Modeling & Simulation Engineering Theses & Dissertations

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters.

Perceiving the growth of such a micro-mobility …

Joint Linear And Nonlinear Computation With Data Encryption For Efficient Privacy-Preserving Deep Learning, Qiao Zhang

Electrical & Computer Engineering Theses & Dissertations

Deep Learning (DL) has shown unrivalled performance in many applications such as image classification, speech recognition, anomalous detection, and business analytics. While end users and enterprises own enormous data, DL talents and computing power are mostly gathered in technology giants having cloud servers. Thus, data owners, i.e., the clients, are motivated to outsource their data, along with computationally-intensive tasks, to the server in order to leverage the server’s abundant computation resources and DL talents for developing cost-effective DL solutions. However, trust is required between the server and the client to finish the computation tasks (e.g., conducting inference for the newly-input …

Integration Of Internet Of Things And Health Recommender Systems, Moonkyung Yang

Electronic Theses, Projects, and Dissertations

The Internet of Things (IoT) has become a part of our lives and has provided many enhancements to day-to-day living. In this project, IoT in healthcare is reviewed. IoT-based healthcare is utilized in remote health monitoring, observing chronic diseases, individual fitness programs, helping the elderly, and many other healthcare fields. There are three main architectures of smart IoT healthcare: Three-Layer Architecture, Service-Oriented Based Architecture (SoA), and The Middleware-Based IoT Architecture. Depending on the required services, different IoT architecture are being used. In addition, IoT healthcare services, IoT healthcare service enablers, IoT healthcare applications, and IoT healthcare services focusing on Smartwatch …

Let's Read: Designing A Smart Display Application To Support Codas When Learning Spoken Language, Katie Rodeghiero, Yingying Yuki Chen, Annika M. Hettmann, Franceli L. Cibrian

Engineering Faculty Articles and Research

Hearing children of Deaf adults (CODAs) face many challenges including having difficulty learning spoken languages, experiencing social judgment, and encountering greater responsibilities at home. In this paper, we present a proposal for a smart display application called Let's Read that aims to support CODAs when learning spoken language. We conducted a qualitative analysis using online community content in English to develop the first version of the prototype. Then, we conducted a heuristic evaluation to improve the proposed prototype. As future work, we plan to use this prototype to conduct participatory design sessions with Deaf adults and CODAs to evaluate the …

Feel And Touch: A Haptic Mobile Game To Assess Tactile Processing, Ivonne Monarca, Monica Tentori, Franceli L. Cibrian

Engineering Faculty Articles and Research

Haptic interfaces have great potential for assessing the tactile processing of children with Autism Spectrum Disorder (ASD), an area that has been under-explored due to the lack of tools to assess it. Until now, haptic interfaces for children have mostly been used as a teaching or therapeutic tool, so there are still open questions about how they could be used to assess tactile processing of children with ASD. This article presents the design process that led to the development of Feel and Touch, a mobile game augmented with vibrotactile stimuli to assess tactile processing. Our feasibility evaluation, with 5 children …

Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus, Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry

Computer Science Faculty Research

The national highway traffic safety administration (NHTSA) identified cybersecurity of the automobile systems are more critical than the security of other information systems. Researchers already demonstrated remote attacks on critical vehicular electronic control units (ECUs) using controller area network (CAN). Besides, existing intrusion detection systems (IDSs) often propose to tackle a specific type of attack, which may leave a system vulnerable to numerous other types of attacks. A generalizable IDS that can identify a wide range of attacks within the shortest possible time has more practical value than attack-specific IDSs, which is not a trivial task to accomplish. In this …

Normalization Of Simulation System Credibility Index Based On Vague Set, Yuhang Ren, Li Wei, Ma Ping, Yang Ming

Journal of System Simulation

Abstract: Focus on various types of simulation system credibility indexes and the difficulty to convert the index results to credibility, a normalization method of credibility indexes based on Vague sets is proposed, which includes qualitative and quantitative conversion methods; Aiming at the problem of credibility Vague value index synthesis, the weighted arithmetic mean operator and the weighted geometric mean operator based on Vague set are given, and the applications are explained; According to the similarity principle of Vague sets, a method of transforming the credibility Vague value to the credibility single value is proposed, which improves the …

Single-Frame Image Motion Parallax Key Point Estimation Combined With Self-Supervised Learning, Zhihao Huo, Weidong Jin, Tang Peng

Journal of System Simulation

Abstract: The motion parallax key point FOE (Focus of Expansion) is an important parameter of railway catenary video inspection. The current method of calculating FOE requires multi-frame image matching estimation, which has high time complexity. Aiming at the single-frame image FOE estimation, a single-frame image FOE estimation algorithm fused with self-supervised learning is proposed. A full convolutional network F-VGG(Fully-Visual Geometry Group) is built as the FOE predictor, and the training label of the sample data is automatically generated through the fusion agent task, which realizes the end-to-end single-frame image FOE estimation. The experimental results show that the method has an …

Research On Stick-Slip Vibration Level Estimation Of Near-Bit Based On Optimized Xgboost, Hanwen Tang, Zhang Tao, Yumei Li, Li Lei, Jinghua Zhang, Dongliang Hu

Journal of System Simulation

Abstract: Stick-slip vibration is an important limiting factor affecting drilling speed, safety and cost. The establishment of a reliable stick-slip vibration classification model is very important for oil drilling decision-making. A new method based on Bayesian optimization and eXtreme Gradient Boosting (XGBoost) is proposed to evaluate the severity of stick-slip vibration near the bit. The classification processing of the near-bit stick-slip vibration data is carried out. The main feature vectors of the original data is extracted through time domain and frequency domain analysis. A stick-slip vibration level identification and prediction model based on XGBoost is established, and Bayesian algorithm is …

Simulation Of Pedestrian In Multifunctional Passageway Of Metro Station Area Based On Social Force Model, Wang Xi, Zhang Rui, Fei Shuo, Minghang Yang

Journal of System Simulation

Abstract: Transitional passageway connecting subway stations and commercial facilities is generally designed as the multifunctional passageway, in which the traffic function is the main and the service function is the auxiliary. The impact of the service facilities on both sides of the passage on pedestrian traffic is difficult to be quantitatively analyzed and simulated and modeled. Through measurement, it is found that the viscous effect of service facilities on pedestrian traffic is mainly slowing down the speed or changing the trajectory direction. Through analyzing the horizontal influence range of service facilities, dividing the passage into different areas, and introducing the …

Fuzzy Information Granulation And Improved Rvm For Rolling Bearing Life Prediction, Xiaoman Hu, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the low accuracy in life prediction and unpredictable problems of degenerative performance trends and fluctuation ranges, etc. Of the bearing life prediction, an improved complete ensemble empirical mode decomposition with adaptive noise analysis and fuzzy information granulating method of improved relevance vector machine is proposed. Focusing on bearing data containing a lot of noise, through the improved complete ensemble empirical mode decomposition with adaptive noise analysis in combination with wavelet packet denoising, the principal component analysis is carride out by exitracing a variety of characeteristics of the signal, the effective information is extracted by granulating the fuzzy …

Modeling And Simulation Of Radiation Measurement System Based On Monte Carlo Method, Jinghai Cheng, Hongzhi Wang, Luoyuan Xu, Xia Tian

Journal of System Simulation

Abstract: A method is applied to build a virtual simulation radiometric measurement system. The mathematical and physical models of gamma ray interaction with matter, radiation sources, measurement electronics system and protective materials are constructed by using Monte Carlo method. Through numerical calculation and scene simulation of the radiation measurement system, virtual simulation acquisition and energy spectrum processing of radiation measurement data are realized. It, the system, can simulate single channel measurement and computer multi-channel measurement experiments. It can realize energy measurement, activity measurement and energy spectrum measurement of mixed, unknown or custom radiation sources in different size crystals. It can …

Trajectory Tracking Control Of Planetary Entry Phase Based On Neural Network And Fractional Sliding Mode, Cunli Fan, Dai Juan, Haitao Liu, Su Zhong, Zhu Cui, Wenting Xu

Journal of System Simulation

Abstract: A fractional order sliding mode control method based on Radial Basis Function (RBF) neural network is proposed to solve the landing accuracy being affected by the interference during the landing process of planetary probe. Based on sliding mode control, a trajectory tracking control method for the entry phase of the probe is designed. Fractional calculus is introduced to alleviate the chattering caused by sliding mode control. RBF neural network is used to estimate and compensate the atmospheric density uncertainty. The method is applied to Mars landing scene simulation. The simulation results show that the proposed control method can accurately …

Optizimation Of Vaccination Supply Chain Based On Scg In Nanshan District, Zhenning Dong, Shunzhou Huang, Jiajun Chen, Huiqiong Zheng

Journal of System Simulation

Abstract: To optimize the vaccination network, inventory strategy and human resource allocation in Nanshan District, Supply Chain Guru's (SCG) network optimization method is used to select 50 alternative stations to decrease the fixed operating cost. SCG's inventory optimization method is used to set inventory strategy for each station, and simulation method is designed to compare total cost of all schemes. To optimize the opening days of vaccination stations, an medical personnel allocation rule is designed, which reduces some stations' opening days to 2 or 3 days and increases some stations' medical personnel. An simulation method is designed to compare the …

Simulation Of Zero-Speed Correction Algorithm For Underground Space Individual Positioning, Yijing Wang, Su Zhong, Li Qing, Li Lei

Journal of System Simulation

Abstract: In view of the complex and dangerous collapse environment of the tunnel, the related safety hazards of the positioning system of the tunnel rescuer are intensively analyzed, and the simulation of the inertial device worn on the chest, waist, calf, and foot surface shows that the correction on the foot surface is the best. Focus on the error accumulation of inertial devices, according to the fact that the speed is near zero when the sole of the foot fully touches the ground during walking, the algorithm of zero-speed correction for acceleration and angular velocity is compared, and a combination …

Research On Flexible Job-Shop Dynamic Scheduling Based On Game Theory, Yichen You, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: To quickly and effectively respond to the machine fault disturbance events in Flexible Job-shop Scheduling Problem (FJSP), a flexible job-shop dynamic scheduling based on game theory is established. A pre-scheduling scheme is generated under Non-Dominated Sort Genetic Algorithm-Ⅱ (NSGA-Ⅱ) algorithm which introduces self-adapted crossover operators to improve the population diversity. For FJSP dynamic scheduling with machine fault, a multi-stage complete information game model is built to better balance the stability and robustness indicators and respond quickly to the machine fault, in which the stability and robustness indicators are mapped to the game players, and a hybrid Nash Equilibrium which …