Digital Commons Network^™

Detection And Analysis Of Malware Evolution, Sunhera Barunkumar Paul

Master's Projects

Malware is a malicious software that causes disruption, allows access to unapproved resources, or performs other unauthorized activity. Developing effective malware detection techniques is a critical aspect of information security. One difficulty that arises is that malware often evolves over time, due to changing goals of malware developers, or to counter advances in detection. This evolution can occur through various modifications in malware code. To maintain effective malware detection, it is necessary to detect and analyze malware evolution so that appropriate countermeasures can be taken. We perform a variety of experiments to detect points in time where a malware family …

Video Synthesis From The Stylegan Latent Space, Lei Zhang

Master's Projects

Generative models have shown impressive results in generating synthetic images. However, video synthesis is still difficult to achieve, even for these generative models. The best videos that generative models can currently create are a few seconds long, distorted, and low resolution. For this project, I propose and implement a model to synthesize videos at 1024x1024x32 resolution that include human facial expressions by using static images generated from a Generative Adversarial Network trained on the human facial images. To the best of my knowledge, this is the first work that generates realistic videos that are larger than 256x256 resolution from single …

Word Embedding Techniques For Malware Classification, Aniket Chandak

Master's Projects

Word embeddings are often used in natural language processing as a means to quantify relationships between words. More generally, these same word embedding techniques can be used to quantify relationships between features. In this paper, we conduct a series of experiments that are designed to determine the effectiveness of word embedding in the context of malware classification. First, we conduct experiments where hidden Markov models (HMM) are directly applied to opcode sequences. These results serve to establish a baseline for comparison with our subsequent word embedding experiments. We then experiment with word embedding vectors derived from HMMs— a technique that …

Ai Quantification Of Language Puzzle To Language Learning Generalization, Harita Shroff

Master's Projects

Online language learning applications provide users multiple ways/games to learn a new language. Some of the ways include rearranging words in the foreign language sentences, filling in the blanks, providing flashcards, and many more. Primarily this research focused on quantifying the effectiveness of these games in learning a new language. Secondarily my goal for this project was to measure the effectiveness of exercises for transfer learning in machine translation. Currently, very little research has been done in this field except for the research conducted by the online platforms to provide assurance to their users [12]. Machine learning has been used …

An Ai For A Modification Of Dou Di Zhu, Xuesong Luo

Master's Projects

We describe our implementation of AIs for the Chinese game Dou Di Zhu. Dou Di Zhu is a three-player game played with a standard 52 card deck together with two jokers. One player acts as a landlord and has the advantage of receiving three extra cards, the other two players play as peasants. We designed and implemented a Deep Q-learning Neural Network (DQN) agent to play the Dou Di Zhu. At the same time, we also designed and made a pure Q-learning based agent as well as a Zhou rule-based agent to compare with our main agent. We show the …

Housing Market Crash Prediction Using Machine Learning And Historical Data, Parnika De

Master's Projects

The 2008 housing crisis was caused by faulty banking policies and the use of credit derivatives of mortgages for investment purposes. In this project, we look into datasets that are the markers to a typical housing crisis. Using those data sets we build three machine learning techniques which are, Linear regression, Hidden Markov Model, and Long Short-Term Memory. After building the model we did a comparative study to show the prediction done by each model. The linear regression model did not predict a housing crisis, instead, it showed that house prices would be rising steadily and the R-squared score of …

Computational Astronomy: Classification Of Celestial Spectra Using Machine Learning Techniques, Gayatri Milind Hungund

Master's Projects

Lightyears beyond the Planet Earth there exist plenty of unknown and unexplored stars and Galaxies that need to be studied in order to support the Big Bang Theory and also make important astronomical discoveries in quest of knowing the unknown. Sophisticated devices and high-power computational resources are now deployed to make a positive effort towards data gathering and analysis. These devices produce massive amount of data from the astronomical surveys and the data is usually in terabytes or petabytes. It is exhaustive to process this data and determine the findings in short period of time. Many details can be missed …

Using Deep Learning And Linguistic Analysis To Predict Fake News Within Text, John Nguyen

Master's Projects

The spread of information about current events is a way for everybody in the world to learn and understand what is happening in the world. In essence, the news is an important and powerful tool that could be used by various groups of people to spread awareness and facts for the good of mankind. However, as information becomes easily and readily available for public access, the rise of deceptive news becomes an increasing concern. The reason is due to the fact that it will cause people to be misled and thus could affect the livelihood of themselves or others. The …

Yoga Pose Classification Using Deep Learning, Shruti Kothari

Master's Projects

Human pose estimation is a deep-rooted problem in computer vision that has exposed many challenges in the past. Analyzing human activities is beneficial in many fields like video- surveillance, biometrics, assisted living, at-home health monitoring etc. With our fast-paced lives these days, people usually prefer exercising at home but feel the need of an instructor to evaluate their exercise form. As these resources are not always available, human pose recognition can be used to build a self-instruction exercise system that allows people to learn and practice exercises correctly by themselves. This project lays the foundation for building such a system …

Sentiment Analysis For Troll Activity Detection On Sina Weibo, Zidong Jiang

Master's Projects

The impact of social media on the modern world is difficult to overstate. Virtually all companies and public figures have social media accounts on popular platforms such as Twitter and Facebook. In China, the micro-blogging service provider Sina Weibo is the most popular such service. To overcome negative publicity, Weibo trolls the so called Water Army can be hired to post deceptive comments.

In recent years, troll detection and sentiment analysis have been studied, but we are not aware of any research that considers troll detection based on sentiment analysis. In this research, we focus on troll detection via sentiment …

Comparison Of Word2vec With Hash2vec For Machine Translation, Neha Gaikwad

Master's Projects

Machine Translation is the study of computer translation of a text written in one human language into text in a different language. Within this field, a word embedding is a mapping from terms in a language into small dimensional vectors which can be processed using mathematical operations. Two traditional word embedding approaches are word2vec, which uses a Neural Network, and hash2vec, which is based on a simpler hashing algorithm. In this project, we have explored the relative suitability of each approach to sequence to sequence text translation using a Recurrent Neural Network (RNN). We also carried out experiments to test …

Improved Chinese Language Processing For An Open Source Search Engine, Xianghong Sun

Master's Projects

Natural Language Processing (NLP) is the process of computers analyzing on human languages. There are also many areas in NLP. Some of the areas include speech recognition, natural language understanding, and natural language generation.

Information retrieval and natural language processing for Asians languages has its own unique set of challenges not present for Indo-European languages. Some of these are text segmentation, named entity recognition in unsegmented text, and part of speech tagging. In this report, we describe our implementation of and experiments with improving the Chinese language processing sub-component of an open source search engine, Yioop. In particular, we rewrote …

Virtual Robot Locomotion On Variable Terrain With Adversarial Reinforcement Learning, Phong Nguyen

Master's Projects

Reinforcement Learning (RL) is a machine learning technique where an agent learns to perform a complex action by going through a repeated process of trial and error to maximize a well-defined reward function. This form of learning has found applications in robot locomotion where it has been used to teach robots to traverse complex terrain. While RL algorithms may work well in training robot locomotion, they tend to not generalize well when the agent is brought into an environment that it has never encountered before. Possible solutions from the literature include training a destabilizing adversary alongside the locomotive learning agent. …

Network Traffic Based Botnet Detection Using Machine Learning, Anand Ravindra Vishwakarma

Master's Projects

The field of information and computer security is rapidly developing in today’s world as the number of security risks is continuously being explored every day. The moment a new software or a product is launched in the market, a new exploit or vulnerability is exposed and exploited by the attackers or malicious users for different motives. Many attacks are distributed in nature and carried out by botnets that cause widespread disruption of network activity by carrying out DDoS (Distributed Denial of Service) attacks, email spamming, click fraud, information and identity theft, virtual deceit and distributed resource usage for cryptocurrency mining. …

Real-Time Ad Click Fraud Detection, Apoorva Srivastava

Master's Projects

With the increase in Internet usage, it is now considered a very important platform for advertising and marketing. Digital marketing has become very important to the economy: some of the major Internet services available publicly to users are free, thanks to digital advertising. It has also allowed the publisher ecosystem to flourish, ensuring significant monetary incentives for creating quality public content, helping to usher in the information age. Digital advertising, however, comes with its own set of challenges. One of the biggest challenges is ad fraud. There is a proliferation of malicious parties and software seeking to undermine the ecosystem …

Prediction Of Drug-Drug Interaction Potential Using Machine Learning Approaches, Joseph Scavetta

Theses and Dissertations

Drug discovery is a long, expensive, and complex, yet crucial process for the benefit of society. Selecting potential drug candidates requires an understanding of how well a compound will perform at its task, and more importantly, how safe the compound will act in patients. A key safety insight is understanding a molecule's potential for drug-drug interactions. The metabolism of many drugs is mediated by members of the cytochrome P450 superfamily, notably, the CYP3A4 enzyme. Inhibition of these enzymes can alter the bioavailability of other drugs, potentially increasing their levels to toxic amounts. Four models were developed to predict CYP3A4 inhibition: …

Using Color Thresholding And Contouring To Understand Coral Reef Biodiversity, Scott Vuong Tran

Master's Projects

This paper presents research outcomes of understanding coral reef biodiversity through the usage of various computer vision applications and techniques. It aims to help further analyze and understand the coral reef biodiversity through the usage of color thresholding and contouring onto images of the ARMS plates to extract groups of microorganisms based on color. The results are comparable to the manual markup tool developed to do the same tasks and shows that the manual process can be sped up using computer vision. The paper presents an automated way to extract groups of microorganisms based on color without the use of …

Design And Research On Semi-Physical Simulation Test System Of Aero Engine, Jingfeng Shen, Chulei Li, Dianliang Wu, Jiaxin Zhang

Journal of System Simulation

Abstract: Aiming at the high danger and difficulty of the operation in the aero-engine test, a semi-physical simulation test system that integrates the functions of the test-run operation training, process analysis, simulation of the typical engine performance fault is proposed. Based on the fast response, accurate calculation and high human operation simulation of the engine digital model, the key problems of the research and implementation, such as the structural design of the distributed semi-physical simulation system, visualization of the calculation model of the engine subsystem and real-time visualization of the aero-engine test data displaying in the three-dimensional cave automatic …

Simulation Of Human Body Temperature Distribution Based On New Solution For Heat Conduction Differential Equation, Sina Dang, Hongjun Xue, Xiaoyan Zhang, Chengwen Zhong, Caiyong Tao

Journal of System Simulation

Abstract: In the traditional rectangular coordinate system, the human body characteristics can not match the differential equation. This leads to the low accuracy of the simulation results. Based on the geometric characteristics of the elliptic cylinder, the differential equation of the heat conduction is transformed from the rectangular coordinate system to the elliptic one, and the finite volume method of the alternating direction full implicit scheme pair is adopted. The improved heat conduction differential equation is applied to the simulation of the human body temperature. The simulation results, compared with the calculated values of the traditional differential equation …

A New Interactive Simulation Method For Virtual Tape Measurement, Dongjin Huang, Chenfeng Jiang, Xianglong Wang, Linhui Gu

Journal of System Simulation

Abstract: The virtual tape measurement is an extremely important process in the industrial training systems, and the fidelity of the measurement depends on the stability of the grasp and the accuracy of the tape measure. Combined with the virtual hand, a new interactive simulation method for the virtual tape measurement is proposed and applied to the wind-driven generator alignment training simulation system. The fusion of the geometric rules and physical rules improves the grasping judgment method, and the quaternion adjusts the grasp gesture. Based on the 3D algorithm, the tape width uneven is solved by optimizing the vertex setting to …

Modeling Analysis And Prediction On Ncp Epidemic Transmission, Huaxiong Sheng, Wu Lin, Changliang Xiao

Journal of System Simulation

Abstract: The modeling analysis on the NCP (Novel Coronavirus Pneumonia) epidemic transmission before and after the closure of Wuhan is presented. On the basis of preprocessing the epidemic data, the classical SIR model and differential recurrence method are used to analyze and forecast the epidemic situation in the stage of control. The theoretical value and measured value fits well. In the stage of free transmission, the logistic model is used to compare and analyze the epidemic data five days in advance or later with the actual data to show the importance of taking the epidemic prevention measures in time. The …

Research On Failure Modes Analysis Based On Weighted Evidence Theory, Lulu Shao, Jihong Han, Niu Kan, Xiaohu Liu, Shao Fang

Journal of System Simulation

Abstract: Aiming at the risk priority numbers of different failure modes being equal and the criticality of the fault modes changing greatly due to the tiny change of the risk parameters, a method of the failure modes analysis based on the weighted evidence theory is proposed from the perspective of the methodology of dealing with the uncertainty problem. The method qualifies the epistemic uncertainty existing in the expert evaluation of the risk parameters into the basic belief assignment and expert attribute weight respectively, and the information propagation and processing of the epistemic uncertainty is solved, and the ordered arrangement …

Design And Implementation Of Reconfigurable Video Array Processor Test Platform, Jiang Lin, Feilong He, Shan Rui, Wang Shuai, Haoyue Wu, Wu Xin

Journal of System Simulation

Abstract: Aiming at the design requirements of the reconfigurable video array processor and the problem of traditional method testing the video codec system with slow speed, low precision and poor observability. A Qt-based user interface is developed, and a hardware-software co-testing platform based on FPGA is designed and implemented. The platform realizes the data transmission and image reproduction based on the software simulation on the PC side, and the parallel mapping of the video encoding and decoding algorithms based on the reconfigurable video array processor on the FPGA side. The experiment results show that the data can be transmitted correctly …

Force/Position Hybrid Control Method For Surface Parts Polishing Robot, Yufeng Ding, Xinpu Min

Journal of System Simulation

Abstract: A force/position hybrid control method for polishing the complex surface with an industrial robot is put forward. The method can achieve the stable force control and precise position control to ensure the consistency of the material removal rate at different normal vectors. After the trajectory of the normal vector is planned in CAD software, the force signal feedback from the sensor and the PI controller in the normal vector direction are combined,and the robot end tool corrects the motion trajectory in the vector direction of the surface to indirectly control the contact force between the tool and the surface. …

High-Fidelity Simulation Of Video-Assisted Thoracoscopic Surgery Lobectomy, Peng Liu, Weixin Si, Zheng Rui, Xiangyun Liao, Dongliang Xu, Ping'an Wang

Journal of System Simulation

Abstract: The virtual reality simulator of the video-assisted thoracoscopic (VATS) surgery lobectomy is of great value to the surgeon's surgical training and planning. In order to simulate the high-fidelity video-assisted thoracoscopic lobectomy, a VATS lobectomy simulator to realistically and efficiently simulate the different surgical operations during the VATS lobectomy procedure is developed. Based on the Position-Based Dynamics framework, the deformation induced by tool-tissue and tissue-tissue interactions, soft tissue cuts as well as subsequent surgical suture operations is simulated. The Marching Cubes algorithm is employed to achieve the surface rendering, especially for the cutting process. The GPU parallel computing technique is …

Application Of Improved Inverse Decoupling Active Disturbance Rejection Internal Model Control In Grinding, Zhou Ying, Qiaojuan Jia, Zhang Yan, Mingxin Chang

Journal of System Simulation

Abstract: Aiming at the characteristics of the multivariable, strong coupling and large time delay of the grinding classification system, the improved inverse decoupling active disturbance rejection internal model control method is proposed. The inverse decoupling method is used to realize the decoupling of the grinding classification system, and the improved internal model control and linear active disturbance rejection control are adopted for the decoupled subsystem. By introducing the internal model compensator and the gain to compensate the time delay, the dependence of the system upon the model is reduced .The model mismatch, external disturbance and uncertainties are suppressed by adjusting …

Simulation And Analysis Of Kinematic Parameters Of Vehicle Offset And Rear-End Collision Accident, Wenhui Zhang, Yongmin Su, Shurui Sun

Journal of System Simulation

Abstract: In order to deeply study the motion behavior of vehicles in the rear-end collision, a vehicle rear end collision accident model is established in the PC-Crash simulation environment. Considering with the relative velocity, offset, speed of the rear-end vehicle and wheel angle, the acceleration, yaw angle and yaw rate of the vehicle are obtained. The research results show that when the bias degree is 20%, the yaw angles of the rear-end vehicle and rear tracked vehicle is the biggest, and is easy to induce the secondary accidents such as rollover and fixtures crash. The larger the relative …

A Route Recovery Mechanism Using Hybrid Anti-Interference Method, Ziwen Sun, Yanqi Zhang, Yimin Xu

Journal of System Simulation

Abstract: Aiming at the jamming attacks in the industrial wireless sensor networks, a route recovery mechanism based on the WirelessHART graph routing is proposed. The jamming attack detection method is used to obtain the node and area being attacked by the jamming attack, the uncoordinated frequency hopping spread spectrum is used to generate the frequency hopping sequence of the node of being attacked by the jamming attack and that of the surrounding nodes, so that the traditional frequency hopping spread spectrum is performed on the nodes. Detects again, and combines the routing cost and the WirelessHART graph routing …

Simulation On A Car-Following Strategy For Adaptive Cruise Control System, Zhiqiang Zhai, Jinliang Xu, Yuan Hao, Yongming Zhou, Longfei Zhao, Shiqian Wang

Journal of System Simulation

Abstract: A car-following strategy based on the variable distance is proposed to improve the applicability of the ACC (Adaptive cruise control) system. The curvature radius of centroid trajectory of the host vehicle is computed by the kinetic model based on the unscented Kalman filter. In order to identify the car-following object, a vehicle tracking model is presented according to the relative kinetic states between the front vehicle and the host vehicle. The ACC system adjust the velocity of the host vehicle to control the safe distance between the host vehicle and the object vehicle. A complex condition with the lane-changing …

Research On Sliding Mode Control Of Robotic Arm Based On Fractional Calculus, Zhang Xin, Jiaxin Li

Journal of System Simulation

Abstract: An effective fractional order sliding mode control method is proposed for the nonlinear and uncertain robotic arm system by combining the advantages of the fractional calculus theory and the sliding mode control strategy. In the design of the controller, the fractional calculus is introduced into the sliding mode control by using the fractional order reaching law and the fractional order sliding mode control law respectively, and is proved by the Lyapunov theory to ensure the stability of the system. The proposed control method is applied to a two-joint robotic arm and is verified by the MATLAB simulation software. The …