Computer Sciences Commons^™

Malware Classification With Gaussian Mixture Model-Hidden Markov Models, Jing Zhao

Master's Projects

Discrete hidden Markov models (HMM) are often applied to the malware detection and classification problems. However, the continuous analog of discrete HMMs, that is, Gaussian mixture model-HMMs (GMM-HMM), are rarely considered in the field of cybersecurity. In this study, we apply GMM-HMMs to the malware classification problem and we compare our results to those obtained using discrete HMMs. As features, we consider opcode sequences and entropy-based sequences. For our opcode features, GMM-HMMs produce results that are comparable to those obtained using discrete HMMs, whereas for our entropy-based features, GMM-HMMs generally improve on the classification results that we can attain with …

Analyzing Performance, Energy Consumption, And Reliability Of Mobile Applications, Osama Barack

Computer Science and Engineering Theses and Dissertations

Mobile applications have become a high priority for software developers. Researchers and practitioners are working toward improving and optimizing the energy efficiency and performance of mobile applications due to the capacity limitation of mobile device processors and batteries. In addition, mobile applications have become popular among end-users, developers have introduced a wide range of features that increase the complexity of application code.

To improve and enhance the maintainability, extensibility, and understandability of application code, refactoring techniques were introduced. However, implementing such techniques to mobile applications affects energy efficiency and performance. To evaluate and categorize software implementation and optimization efficiency, several …

Deep Neural Network Based Student Response Modeling With Uncertainty, Multimodality And Attention, Xinyi Ding

Computer Science and Engineering Theses and Dissertations

In this thesis, I investigate deep neural network based student response modeling, more specifically Knowledge Tracing (KT). Knowledge Tracing allows Intelligent Tutoring Systems to infer which topics or skills a student has mastered, thus adjusting curriculum accordingly. Deep neural network based knowledge tracing models like Deep Knowledge Tracing (DKT) and Dynamic Key-Value Memory Network (DKVMN) have achieved significant improvements compared with conventional probabilistic models. There are mainly two goals in this thesis: 1) To have a better understanding of existing deep neural network based models and their predictions through visualization and through incorporating uncertainties. 2) To improve the performance of …

Analysis Of Github Pull Requests, Canon Ellis

Computer Science and Engineering Theses and Dissertations

The popularity of the software repository site GitHub has created a rise in the Pull Based Development Models' use. An essential portion of pull-based development is the creation of Pull Requests. Pull Requests often have to be reviewed by an individual to be approved and accepted into the Master branch of a software repository. The reviewing process can often be time-consuming and introduce a relatively high level of lost development time. This paper examines thousands of pull requests to understand the most valuable metadata of pull requests. We then introduce metrics in comparing the metadata of pull requests to understand …

The Use Of Evidential Reasoning Model With Biomarkers In Pancreatic Cancer Prediction, Qianhui Fan

Master's Projects

In this project, an evidential reasoning model is built to amalgamate factors that could be used in early detection of pancreatic cancer. Our machine learning model outputs a probability of a given patient having prostate cancer based on various input variables. These variables include health history factors, such as smoking and medical history, technical artifacts, such as biopsy sequencing technology, and genomic biomarkers such as mutational, transcriptional and methylomic profiles, cfDNA, and copy number variation. The dataset used in this project is a part of The Cancer Genome Atlas (TCGA) project and was collected from the National Cancer Institute (NIH) …

Multigrid For The Nonlinear Power Flow Equations, Enrique Pereira Batista

Mathematics Theses and Dissertations

The continuously changing structure of power systems and the inclusion of renewable
energy sources are leading to changes in the dynamics of modern power grid,
which have brought renewed attention to the solution of the AC power flow equations.
In particular, development of fast and robust solvers for the power flow problem
continues to be actively investigated. A novel multigrid technique for coarse-graining
dynamic power grid models has been developed recently. This technique uses an
algebraic multigrid (AMG) coarsening strategy applied to the weighted
graph Laplacian that arises from the power network's topology for the construction
of coarse-grain approximations to …

Improving A Wireless Localization System Via Machine Learning Techniques And Security Protocols, Zachary Yorio

Masters Theses, 2020-current

The recent advancements made in Internet of Things (IoT) devices have brought forth new opportunities for technologies and systems to be integrated into our everyday life. In this work, we investigate how edge nodes can effectively utilize 802.11 wireless beacon frames being broadcast from pre-existing access points in a building to achieve room-level localization. We explain the needed hardware and software for this system and demonstrate a proof of concept with experimental data analysis. Improvements to localization accuracy are shown via machine learning by implementing the random forest algorithm. Using this algorithm, historical data can train the model and make …

The Algorithm Project Research And Modeling Of Information Systems, Victoria Kuznetsova, S.B. Dovletova, Mixriddin Raximov, Gulnora Muxtorova, Kim Yelena

Bulletin of TUIT: Management and Communication Technologies

Pre-project research is a strategic stage of the object design process, based on the results of which a decision is made on the level of competitiveness, development prospects, setting a task for the project, labor intensity and feasibilityof creating a system in general.

The existing methods of pre-project research have a high degree of generalization and are practically not formalized in any way. The disadvantage of these methods is that they consider only specific individual prototypes and are aimed at finding solutions to current problems and eliminating individual shortcomings of a particular prototype. Thus, it Is Concluded that It Is …

Machine Learning Model Selection For Predicting Global Bathymetry, Nicholas P. Moran

LSU New Orleans Theses and Dissertations

This work is concerned with the viability of Machine Learning (ML) in training models for predicting global bathymetry, and whether there is a best fit model for predicting that bathymetry. The desired result is an investigation of the ability for ML to be used in future prediction models and to experiment with multiple trained models to determine an optimum selection. Ocean features were aggregated from a set of external studies and placed into two minute spatial grids representing the earth's oceans. A set of regression models, classification models, and a novel classification model were then fit to this data and …

A Federated Deep Autoencoder For Detecting Iot Cyber Attacks, Christopher M. Regan

Master of Science in Computer Science Theses

Internet of Things (IoT) devices are mass-produced and rapidly released to the public in a rough state. IoT devices are produced by various companies satisfying various goals, such as monitoring the environment, senor trigger cameras, on-demand electrical switches. These IoT devices are produced by companies to meet a market demand quickly, producing a rough software solution that customers or other enterprises willingly buy with the expectation they will have software updates after production. These IoT devices are often heterogeneous in nature, only to receive updates at infrequently intervals, and can remain out of sight on a home or office network …

Visualization Of Large Networks Using Recursive Community Detection, Xinyuan Fan

Master's Projects

Networks show relationships between people or things. For instance, a person has a social network of friends, and websites are connected through a network of hyperlinks. Networks are most commonly represented as graphs, so graph drawing becomes significant for network visualization. An effective graph drawing can quickly reveal connections and patterns within a network that would be difficult to discern without visual aid. But graph drawing becomes a challenge for large networks. Am- biguous edge crossings are inevitable in large networks with numerous nodes and edges, and large graphs often become a complicated tangle of lines. These issues greatly reduce …

Methodological Aspects Of Distance Learning For Developing The Professional Competence Of Students Of The Direction "Computer Engineering, B Kuznetsova, Gulnora Muxtarova, Umida Azimova, Kim Yelena

Bulletin of TUIT: Management and Communication Technologies

This work is based on the use of distance learning technologies in education, which will make it possible to individualize training, and in turn contributes to the formation of professionally important qualities for students of the direction of "Computer Engineering". The experimental work was aimed at developing a technology for the formation of students' professional competence.

The article shows that the mastery by students of knowledge, skills and abilities in the field of computer engineering was aimed at their conscious application in solving problems of the educational and cognitive process, and subsequently in professional activity.

The article presents the results …

Bioinformatics Metadata Extraction For Machine Learning Analysis, Zachary Tom

Master's Projects

Next generation sequencing (NGS) has revolutionized the biological sciences. Today, entire genomes can be rapidly sequenced, enabling advancements in personalized medicine, genetic diseases, and more. The National Center for Biotechnology Information (NCBI) hosts the Sequence Read Archive (SRA) containing vast amounts of valuable NGS data. Recently, research has shown that sequencing errors in conventional NGS workflows are key confounding factors for detecting mutations. Various steps such as sample handling and library preparation can introduce artifacts that affect the accuracy of calling rare mutations. Thus, there is a need for more insight into the exact relationship between various steps of the …

Malware Classification Using Lstms, Dennis Dang

Master's Projects

Signature and anomaly based detection have long been quintessential techniques used in malware detection. However, these techniques have become increasingly ineffective as malware becomes more complex. Researchers have therefore turned to deep learning to construct better performing models. In this project, we create four different long-short term memory (LSTM) models and train each model to classify malware by family type. Our data consists of opcodes extracted from malware executables. We employ techniques used in natural language processing (NLP) such as word embedding and bidirection LSTMs (biLSTM). We also use convolutional neural networks (CNN). We found that our model consisting of …

Quantifying Deepfake Detection Accuracy For A Variety Of Natural Settings, Pratikkumar Prajapati

Master's Projects

Deep fakes are videos generated from a starting video of a person where that person's face has been swapped for someone else's. In this report, we describe our work to develop general, deep learning-based models to classify Deep Fake content. Our first experiments involved simple Convolution Neural Network (CNN)-based models where we varied how individual frames from the source video were passed to the CNN. These simple models tended to give low accuracy scores for discriminating fake versus non-fake videos of less than 60%. We then developed three more sophisticated models: one based on choosing test frames, one based on …

A Preliminary Analysis Of How A Software Organization’S Maturity And Size Affect Its Intellectual Property Portfolio, Daniel Gifford

Master of Science in Software Engineering Theses

Intellectual property, commonly known as IP, is complex. The four main types of software IP, which is what this thesis will focus on, are patents, trade secrets, trademarks, and copyright. Patents, trade secrets, and copyrights were all studied by this thesis. Software IP is unique in that it can by copyrighted. Different IP owners, which can be businesses of different types, individuals, and universities, often have different strategies as to how to use their IP portfolio. This thesis studies differences in IP usage between these entities specifically in the field of software. Large and small software companies were analyzed specifically. …

Research On Recovering Of Complex Networks Based On Boundary Nodes Of Giant Connected Component, Zhe Wang, Jianhua Li, Kang Dong

Journal of System Simulation

Abstract: Network recovery is an important way to solve the inevitable failure,and the reasonable recovery strategy can reduce the cost of resource and improve the network robustness.In order to study the dynamic behavior of recovery process and the relationship between recovery and network robustness,a Recovery Model of Boundary Nodes (RMBN) based on boundary of giant connected component is proposed,and two network Recovery strategies,Average Recovery of Boundary Nodes (ARBN) strategy and Priority Recovery of Boundary Nodes (PRBN) strategy are designed.The simulation results of different recovery strategies on three network models show that with the increase of recovery ratio,the …

Multi-Agent Behavior Simulation For Metro Station Passenger, Zequn Li, Fengting Yan, Zhicai Shi, Yumei Jian, Changhua Hua, Yongzhan Si, Xiang Yang

Journal of System Simulation

Abstract: Metro station is a typical public place with large crowd density.The characteristics of crowd behavior and the guidance based on the characteristics of crowd behavior can effectively train the crowd for emergency evacuation.Adopting the method of multi-agent and characteristics by measuring station building scene,analyzing the influence factors of passenger behavior characteristics,based on the passenger conformity rule,the single-agent passenger route choice behavior model is established.The multiple agents behavioral decision system in the virtual metro stations is established,the WebVR experiment is used to research the influencing factors of passenger herd behavior and decision-making behavior,which provides a theoretical basis for …

Analyzing Dispatching Wave Policies For E-Commerce Logistics Based On The Multi-Agent-Based Simulation, Zhiqiang Niu, Chaoyang Li, Hongyu Dong, Zhang Feng, Lingyun Meng, Tong Lu, Shengnan Wu

Journal of System Simulation

Abstract: To provide superior on-line shopping experiences and maintain sustained profitability,e-commerce logistics companies need design an effective dispatching wave policy strategy to handle the tradeoff between the advantage of economies of scale and fast-pace delivery services.A multi-agent-based simulation framework is proposed,where business processes in logistics are built as different nodes in the simulation network.Case studies are conducted to test the order delivery process with various wave strategies in the Beijing metropolitan area.Experimental results show that situation-dependent wave strategies are sensitive to different patterns of online shopping demands.

Prediction Of Epidemic Transmission And Evaluation Of Prevention And Control Measures Based On Artificial Society, Bin Chen, Yang Mei, Chuan Ai, Ma Liang, Zhengqiu Zhu, Hailiang Chen, Mengna Zhu, Xu Wei

Journal of System Simulation

Abstract: The COVID-19 has been controlled under the strict measures,but how to normalize it deserves in-depth study.The COVID-19 transmission model and the human contact network are established separately based on SEIR model and the artificial social scenario.With the support of the multi-agent computational experiment method,a large sample calculation experiment was performed on the Tianhe supercomputer to simulate the epidemic transmission in typical areas such as communities,schools,and workplaces in artificial cities,and to predict and evaluate the risk of epidemic spread after resumption of work and school.The results show that epidemic prevention and control must be prepared for a …

Application Of Simulation Technology In Football Overall Attack Training, Xu Nuo, Shuanglong Liu, Fugao Jiang

Journal of System Simulation

Abstract: Simulation technology has a broad prospect in the field of football application.At present,football attack training is mainly based on audio-visual,experience and on-the-spot practice,but it lacks professional scene representation and systematic theoretical support. Visual C++ development platform and simulation programming method are used to virtualize the football training and reproduce the overall attack drill of football under different training scenes.The results show that the simulation technology can achieve more training situations. It can be used as an auxiliary tool for football overall attack training,enrich the training means,help players accurately understand the tactical system,and promote the scientific development of football training.

Optimization Algorithm For Planar Led Distribution And Connection, Fei Yue, Zhiqiang Gui, Yuyou Yao, Benzhu Xu, Liping Zheng

Journal of System Simulation

Abstract: The distribution and grouping of planar LED can be modeled as a multi constraint optimization problem.A novel algorithm based on the centroidal capacity-constrained power diagram for LED distribution is proposed,to achieve the goal of uniform illumination of planar LED.An optimization algorithm of LED combination and connection based on the greedy strategy is proposed to save materials.The experiment results show that the proposed algorithms are simple,effective in layout and grouping with rapid convergence,and can be used in practical applications.

An Online Evaluation Framework Of Complex Simulation System Based On Acceptability Criteria, Zhenglin Sun, Weiqiang Yuan, Weiqing Li

Journal of System Simulation

Abstract: An online simulation evaluation method based on Acceptability Criteria (AC) for the lag of current complex simulation systems is proposed.A qualitative and quantitative AC to index mapping model is used to establish an evaluation index system.Based on index sets and evaluation functions,a seven-tuple model of a simulation process finite automaton is proposed,and a mapping of the simulation process to automata and a data-driven state transfer mechanism are given.Based on the above results,an online evaluation tool is designed and the effectiveness is verified through a case.The result that the method can effectively solve lag in the evaluation …

Frequency Regulation Signal Reduction Methods For Aluminum Smelters, Zejian Feng, Shengfei Li, Shouzhen Zhu, Zhiyun Li, Xiaomin Bai

Journal of System Simulation

Abstract: The motion delay of tap changer of aluminum smelter rectifier downgrades frequency response precision in following high frequency regulation signals.Aiming to improve the regulation performance of aluminum smelter loads based on adjusting dynamics,a fast regulation signal reduction technique is proposed,which is motion control threshold-based.A simulation-based decision technique of threshold values of the signal reduction algorithm's is devised to improve the performances of frequency response.Simulation results verify the efficacy of the techniques in promoting the frequency response precision to a certain production level,and contribute a practical way to support aluminum smelter‘s provision of frequency regulation services …

Amorphous Sio2/Si Interface Defects And Mechanism Of Passivation/Depassivation Reaction, Zhuocheng Hong, Zuo Xu

Journal of System Simulation

Abstract: The amorphous silicon dioxide/silicon (a-SiO₂/Si) interface is an important part of semiconductor devices.The passivation and depassivation process of silicon dangling bond defects (P_b-type defects) at the SiO₂/Si interface has a significant impact on semiconductor devices.Based on molecular dynamics and first-principles calculation methods,a-SiO₂/Si(111) interface model is constructed based on a-SiO₂ and crystalline Si.The CI-NEB (Climbing Image-Nudged Elastic Band) method is used to study the passivation and depassivation reactions of H₂ and H atoms of P_b defects at the a-SiO₂/Si(111) interface. The curves,barriers,and transition state structures of …

Fault Diagnosis For Bearings Of Unbalanced Data Based On Feature Generation, Minglu Fan, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: Focus on the sample imbalance and insufficiency caused by the difficulty to obtain a sufficient number of fault samples in actual production.A model for rolling bearings by combining Convolutional Neural Networks and Synthetic Oversampling is presented.The frequency domain signals is used as the input of the model,and the features are extracted by the Convolutional Neural Network.The new features are generated by Synthetic Oversampling and the data equalization is realized.The model completes the classification by putting all of the features into the Support Vector Machine,and the fault diagnosis of the rolling bearings is carried out.The comparison experiments results …

A Survey On Underwater Bionic Electric Perception, Guangming Xie, Junzheng Zheng, Wang Chen

Journal of System Simulation

Abstract: Sensing and detection technologies for underwater robots in complex underwater environments have been urgently needed.Weakly electric fields-based underwater bionic electric perception is a promising technical route.A kind of fish in nature,called weakly electric fish,can perceive their surrounding environment and other creatures through the varied electric field generated by themselves.Inspired by the electric fish,researchers have focused on the principle and methods of underwater perception based on weakly electric fields and the applications for intelligent underwater robots.The biological mechanism of weakly electric fish,the modeling and perception theory of underwater electric field,the underwater electric perception technology,and their applications are reviewed,and the …

Research On Dissemination And Control Of Public Opinion Based On Multilayer Coupled Network, Chen Shuai

Journal of System Simulation

Abstract: In order to study the influence of information interaction between multi-platforms on the dissemination and control of public opinion,taking Wechat and Weibo for example,a public opinion communication and control model based on multi-layer coupled network including Wechat layer,Weibo layer and control layer is constructed using multi-agent modeling method and improved SEIR model.On Anylogic platform,a simulation experiment was conducted on the event that “the use of materials by the Hubei Red Cross Society raises doubts”,and the effects factors such as single/dual platform,control range,control dynamics,control time and interaction between platforms were analyzed.The media guidance and government intervention strategies under multi-platform …

Parallel Finite Element Simulations On Radiation Damage Effects Of Lateral Pnp Bjts, Wang Qin, Zhaocan Ma, Hongliang Li, Linbo Zhang, Benzhuo Lu

Journal of System Simulation

Abstract: The Zlamal finite element discretization is applied in the drift-diffusion model for the simulations of semiconductor devices.Combined with the coupled ionization damage model,the ionization damage effects of lateral PNP (LPNP) bipolar junction transistors (BJT) are simulated.The model and algorithm are implemented based on the three-dimensional parallel adaptive finite element toolbox PHG (Parallel Hierarchical Grid).The phenomena of excess base current and current gain degradation in LPNP BJTs are successfully simulated via numerical calculation. A large-scale numerical experiment with 100 million elements and 1 024 MPI processes is carried out,demonstrating the good parallel scalability of the algorithm.

Non-Cooperative Target Feature Point Cloud Registration Optimization Based On Icp Algorithm, Wei Liang, Muyao Xue, Huo Ju, Jinjie Zhang

Journal of System Simulation

Abstract: Aiming at the pose measurement caused by non-cooperative targets in visual measurement that cannot provide cooperation information,the ICP(Iterative Closest Point) algorithm is used to register the point cloud down-sampling data acquired at different times to complete the relative pose measurement of the target.The point cloud data of the target at the current moment is obtained using the structure from motion algorithm and the feature point matching algorithms are compared based on threshold matching and optical flow matching method.The extracted feature points are reconstructed by triangulation.The relative pose changes of the object at different times are calculated by using …