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Articles 2431 - 2460 of 13561

Full-Text Articles in Computer Engineering

Survey Of Ship Detection In Video Surveillance Based On Shallow Machine Learning, Zhenbo Bi, Shiyou Zhang, Yang Hua, Yuanhong Wu Jan 2022

Survey Of Ship Detection In Video Surveillance Based On Shallow Machine Learning, Zhenbo Bi, Shiyou Zhang, Yang Hua, Yuanhong Wu

Journal of System Simulation

Abstract: At present, detection of ship targets in video surveillance based on shallow machine learning methods is still attracting attention in the fields of underwater cultural heritage protection, marine aquaculture, maritime traffic, and port management. This paper provides a review and discussion for this kind of ship detection methods. The ship target detection based on video surveillance is divided into five parts according to the key technologies involved: preprocessing, region of interest extraction, target segmentation, ship feature extraction and ship type recognition. According to different functional modules, the core problems involved in them are pointed out, and the core ideas, …

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Real-Time Simulation Technology Of Fluid-Thermo-Solid Coupling Of Hypersonic Vehicle, Yunqin Liu, Li Ni, Luming Zhao, Jinpeng Bai, Tingjun Li, Chenguang Wang Jan 2022

Real-Time Simulation Technology Of Fluid-Thermo-Solid Coupling Of Hypersonic Vehicle, Yunqin Liu, Li Ni, Luming Zhao, Jinpeng Bai, Tingjun Li, Chenguang Wang

Journal of System Simulation

Abstract: The solution of the coupling characteristics of fluid-thermo-solid physics in the modeling of hypersonic vehicle is an unavoidable difficulty, and the real-time simulation of fluid-thermo-solid coupling is particularly challenging. Aiming at the conflicting problem of solution accuracy and solution efficiency in fluid-thermo-solid coupling real-time simulation, a CFD (Computational Fluid Dynamics)/ CSD (Computational Structural Dynamics)-based fluid-thermo-solid coupling characteristic solution method is established, which realizes the high-precision solution of the fluid, temperature, and structural deformation field coupling. According to the multi-condition offline solution set modeling method, by accumulating a large number of offline solutions as effective support for online …

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A Data-Driven Modeling Method For Game Adversity Agent, Zeng Bi, Fang Xiao, Deshuai Kong, Xiangxiang Song, Zhengxuan Jia, Tingyu Lin Jan 2022

A Data-Driven Modeling Method For Game Adversity Agent, Zeng Bi, Fang Xiao, Deshuai Kong, Xiangxiang Song, Zhengxuan Jia, Tingyu Lin

Journal of System Simulation

Abstract: Aiming at the problems of collaborative modeling of formation behavior and intelligent generation of decision-making in complex confrontation scenarios, based on the serious game to simulate the confrontation scenarios of complex maritime equipment against the air, this paper proposes a data-driven modeling method for game agent and uses a distributed modeling technology of parallel adversarial scenarios and opportunistic decision making technology of smart targets to achieve agent modeling. It provides support for the further exploration of multi-objective collaborative modeling in complex confrontation scenarios. The simulation results show that deep reinforcement learning algorithms can provide a basis for the modeling …

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Research On Usv Navigation Simulation Key Technologies, Jianhai Jin, Zexing Zhou, Zhang Bo, Yihong Chen, Xizhong Wei Jan 2022

Research On Usv Navigation Simulation Key Technologies, Jianhai Jin, Zexing Zhou, Zhang Bo, Yihong Chen, Xizhong Wei

Journal of System Simulation

Abstract: In order to solve the problems of long test time, high cost and high risk, a general framework of simulation system for autonomous navigation test and verification of USV(Unmanned Surface Vessel) has been developed, and some key simulation technologies such as complex scenario simulation, intelligent perception, navigation simulation and environmental effect modeling are researched. the dynamic equation, kinematics equation, wind load modeling, wave surface modeling, wave drift force modeling and ocean current modeling are designed and realized. The simulation system is proved to have high accuracy and fidelity by the real ship test on the lake, which can greatly …

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Kinematics Analysis And Simulation Of Automatically Tracking Dental Surgery Lamp, Zerui Jiang, Lijun Yang, Li Jun, Xiaolong Jiao, Zheng Hang Jan 2022

Kinematics Analysis And Simulation Of Automatically Tracking Dental Surgery Lamp, Zerui Jiang, Lijun Yang, Li Jun, Xiaolong Jiao, Zheng Hang

Journal of System Simulation

Abstract: In order to solve the problem that the oral surgical lamp cannot automatically adjust the irradiation posture of the surgical lamp according to the face direction and oral cavity position, a six-degree-of-freedom automatic tracking visual manipulator solution is proposed. Coordinate conversion is achieved through binocular vision to obtain three-dimensional information of oral cavity position and face normal vector. The geometric method is introduced into the kinematics calculation, and the closed solution of the inverse kinematics is obtained. The correctness is verified by the Maltab programming and the introduction of numerical values. Five-degree polynomial motion planning is performed …

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Research On Digital Twin-Based Modeling And Monitoring Of Five-Axis Grinder, Xiao Tong, Haifan Jiang, Guofu Ding, Jiang Lei, Shuwen Ma Jan 2022

Research On Digital Twin-Based Modeling And Monitoring Of Five-Axis Grinder, Xiao Tong, Haifan Jiang, Guofu Ding, Jiang Lei, Shuwen Ma

Journal of System Simulation

Abstract: Aiming at the poor virtual-real interaction ability, single data presentation mode, and hysteretic abnormality handling in CNC machine tool status monitoring, a visual monitoring method for machine tool process based on digital twin is proposed, Which realizes the mapping of three subsystems of machine tool, machinery, control and electrical to the information space from three dimensions of geometry, logic and data. The verification of instructions and CNC programs, real-time status monitoring and abnormality handling during operation are carried out. A digital twin-based machine tool modeling and monitoring system is designed and developed. Taking a five-axis CNC …

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Hyperspectral Rx Anomaly Detection Method Based On The Fusion Of Spatial And Spectral Feature, Liu Xuan, Xiangyang Li, He Fang, Jianwei Zhao, Fenggan Zhang Jan 2022

Hyperspectral Rx Anomaly Detection Method Based On The Fusion Of Spatial And Spectral Feature, Liu Xuan, Xiangyang Li, He Fang, Jianwei Zhao, Fenggan Zhang

Journal of System Simulation

Abstract: To address the problem that the hyperspectral anomaly detection algorithm does not make full use of the spatial information of the hyperspectral image and the detection accuracy is limited, a FSSRX (Fusing Spatial and Spectral Reed-Xiaol) anomaly detection algorithm that fuses spatial and spectrum information is proposed to improve the accuracy of hyperspectral anomaly detection. In FSSRX algorithm, the spatial feature of hyperspectral images is firstly extracted by the EMAP(Extended Multi-attribute Profile) method and the abnormal score of each pixel in spatial features is then calculated with RX detector. Meanwhile, RX anomaly detection is carried out directly on the …

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Research On Model Reuse Technology Based On Semantic Matching And Composition, Xingyu Tian, Guangxun Zeng, Yunbo Gao, Lili Ye, Guanghong Gong, Li Ni Jan 2022

Research On Model Reuse Technology Based On Semantic Matching And Composition, Xingyu Tian, Guangxun Zeng, Yunbo Gao, Lili Ye, Guanghong Gong, Li Ni

Journal of System Simulation

Abstract: In order to solve the data barriers between the conceptual model and the simulation scenario of the combat system, the intelligent mapping and model reuse technology of the simulation scenario is researched. The conceptual model is analyzed using DOM technology. Based on the ontology theory, the knowledge base of the combat domain is constructed and the web crawler is customized to build the domain thesaurus. Through the SWRL rule library, the reasoning engine is called to realize the relational reasoning at the semantic level. An intelligent matching algorithm is designed to map the semantic relationship to the combination relationship …

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Research On Cloud Tool Integration And Management Methods, Tianying Zhang, Ji Hang, Junhua Zhou, Tao Luan Jan 2022

Research On Cloud Tool Integration And Management Methods, Tianying Zhang, Ji Hang, Junhua Zhou, Tao Luan

Journal of System Simulation

Abstract: In response to the application needs of using professional tools to develop complex products in the fields of aerospace, aviation, weapons, ships, etc., it is urgent to implement centralized management of cloud tools and cross-professional sharing of tools through tool service-oriented methods, so as to solve issues such as inconsistent tool versions, cross-professional resource barriers, and high thresholds for tool mastery during the traditional model development process. By studying the integration and calling methods of cross-professional and different versions of self-developed tools, as well as methods of tool server operation control, authority management, etc., and taking the local …

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Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station, Xiaohe Li, Jianping Wu, Depin Peng Jan 2022

Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station, Xiaohe Li, Jianping Wu, Depin Peng

Journal of System Simulation

Abstract: With the rapid development of subway in China, the urban rail station, especially the transfer station, is prone to generate passenger congestion in the peak period. After analyzing the types of passenger flow in and out of the platform, a predictive control model of passenger flow is established based on the discrete linear quadratic optimal control theory. Taking Fuxingmen Station as an example, the simulation environment of the station is built by using the simulation software of Anylogic. The historical passenger flow data in peak period and the optimal passenger flow control sequence obtained by solving the passenger flow …

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Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections, Zhao Dan, Xuejun Niu, Shuhao Zhang, Jiaxu Wei Jan 2022

Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections, Zhao Dan, Xuejun Niu, Shuhao Zhang, Jiaxu Wei

Journal of System Simulation

Abstract: Contraflow left-turn is one of the traffic organization ways at intersections. By analyzing the setting parameters of the contraflow left-turn, the length and the range of the contraflow left-turn lane, the constrained conditions of the contraflow left-turn are determined, and the applicable conditions are determined from the road, traffic and signal control. VISSIM software is used to analyze a road intersection, simulate and evaluate the indicators related to the intersection entrance, optimize the timing plan of contraflow left-turn lane, and validate the feasibility and advantages of contraflow left-turn lane. The results show that the intersection delays are reduced by …

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Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel, Feng Xiao, Zhang Hui, Zhou Rui, Qiao Lu, Wei Dong, Dandan Li, Yuyao Zhang, Guoqing Zheng Jan 2022

Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel, Feng Xiao, Zhang Hui, Zhou Rui, Qiao Lu, Wei Dong, Dandan Li, Yuyao Zhang, Guoqing Zheng

Journal of System Simulation

Abstract: In order to construct a maize kernel variety recognition model with high recognition accuracy and suitable for mobile phone application, a mobile phone is used to obtain maize kernel double-sided (embryonic and non-embryonic) images. Based on the lightweight convolutional neural network MobileNetV2 and transfer learning, a maize kernel image variety recognition model is constructed. In view of the existing research methods are mainly for single-sided recognition of maize kernel variety, the performance of single-sided and double-sided characteristics modeling and recognition is compared. The results show that the double-sided recognition accuracy of maize kernel double-sided characteristics modeling is 99.83%, which …

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A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran Jan 2022

A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran

Electrical and Computer Engineering Faculty Publications

Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD). Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers around the world to identify CKD as a condition that leads to reduced renal function over time. A person with CKD has a higher chance of dying young. Doctors face a difficult task in diagnosing the different diseases linked to CKD at an early stage in order to prevent the disease. This research presents a novel deep learning model for the early detection and prediction of CKD. This research objectives to create a deep …

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Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora Jan 2022

Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora

Dissertations

Word embeddings have been considered one of the biggest breakthroughs of deep learning for natural language processing. They are learned numerical vector representations of words where similar words have similar representations. Contextual word embeddings are the promising second-generation of word embeddings assigning a representation to a word based on its context. This can result in different representations for the same word depending on the context (e.g. river bank and commercial bank). There is evidence of social bias (human-like implicit biases based on gender, race, and other social constructs) in word embeddings. While detecting bias in static (classical or non-contextual) word …

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Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan Jan 2022

Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan

Electronic Theses and Dissertations

Parkinson’s disease (PD) is a neurodegenerative movement disorder that progresses gradually over time. The onset of symptoms in people who are suffering from PD can vary from case to case, and it depends on the progression of the disease in each patient. The PD symptoms gradually develop and exacerbate the patient’s movements throughout time. An early diagnosis of PD could improve the outcomes of treatments and could potentially delay the progression of this disorder and that makes discovering a new diagnostic method valuable. In this study, I investigate the feasibility of using a machine learning (ML) approach to classify PD …

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Data Analytics And Visualization For Virtual Simulation, Sri Lekha Koppaka Jan 2022

Data Analytics And Visualization For Virtual Simulation, Sri Lekha Koppaka

Browse all Theses and Dissertations

Healthcare organizations attract a diversity of caregivers and patients by providing essential care. While interacting with people of various races, ethnicity, and economical background, caregivers need to be empathetic and compassionate. Proper training and exposure are needed to understand the patient’s background and handle different situations and provide the best care for the patient. With social determinants of health (SDOH) as the basis, the thesis focuses on providing exposure through “Wright LIFE (Lifelike Immersion for Equity) - A simulation-based training tool” to two such scenarios covering patients from the LGBTQIA+ community & autism spectrum disorder (ASD). This interactive tool helps …

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Computer Enabled Interventions To Communication And Behavioral Problems In Collaborative Work Environments, Ashutosh Shivakumar Jan 2022

Computer Enabled Interventions To Communication And Behavioral Problems In Collaborative Work Environments, Ashutosh Shivakumar

Browse all Theses and Dissertations

Task success in co-located and distributed collaborative work settings is characterized by clear and efficient communication between participating members. Communication issues like 1) Unwanted interruptions and 2) Delayed feedback in collaborative work based distributed scenarios have the potential to impede task coordination and significantly decrease the probability of accomplishing task objective. Research shows that 1) Interrupting tasks at random moments can cause users to take up to 30% longer to resume tasks, commit up to twice the errors, and experience up to twice the negative effect than when interrupted at boundaries 2) Skill retention in collaborative learning tasks improves with …

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Topological Hierarchies And Decomposition: From Clustering To Persistence, Kyle A. Brown Jan 2022

Topological Hierarchies And Decomposition: From Clustering To Persistence, Kyle A. Brown

Browse all Theses and Dissertations

Hierarchical clustering is a class of algorithms commonly used in exploratory data analysis (EDA) and supervised learning. However, they suffer from some drawbacks, including the difficulty of interpreting the resulting dendrogram, arbitrariness in the choice of cut to obtain a flat clustering, and the lack of an obvious way of comparing individual clusters. In this dissertation, we develop the notion of a topological hierarchy on recursively-defined subsets of a metric space. We look to the field of topological data analysis (TDA) for the mathematical background to associate topological structures such as simplicial complexes and maps of covers to clusters in …

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Virtual Reality-Based Serious Role-Playing Games As Digital Experiential Learning Tools To Deliver Healthcare Skills Through Mobile Devices, Dixit Bharatkumar Patel Jan 2022

Virtual Reality-Based Serious Role-Playing Games As Digital Experiential Learning Tools To Deliver Healthcare Skills Through Mobile Devices, Dixit Bharatkumar Patel

Browse all Theses and Dissertations

Inadequate professional training and practices related to health care may result in severe complications to care experiences and outcomes. Moreover, healthcare professionals are as susceptible to the possibility of implicit biases as any other group. Importantly, the health care training is critical and challenging as minor prejudicial beliefs have an adverse influence or serious consequences on patients' health outcomes. Thus, facilitating serious role-playing virtual care practices along with raising awareness of healthcare professionals about the enduring impact of implicit/explicit biases and Social Determinants of Health (SDH) on health outcomes assist to advance the patient-provider relation, care experiences (e.g., healthcare experience …

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Automatically Inferring Image Bases Of Arm32 Binaries, Daniel T. Chong Jan 2022

Automatically Inferring Image Bases Of Arm32 Binaries, Daniel T. Chong

Browse all Theses and Dissertations

Reverse engineering tools rely on the critical image base value for tasks such as correctly mapping code into virtual memory for an emulator or accurately determining branch destinations for a disassembler. However, binaries are often stripped and therefore, do not explicitly state this value. Currently available solutions for calculating this essential value generally require user input in the form of parameter configurations or manual binary analysis, thus these methods are limited by the experience and knowledge of the user. In this thesis, we propose a user-independent solution for determining the image base of ARM32 binaries and describe our implementation. Our …

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Ransombuster Iot: A Intrusion Detection And Dataset Creation Tool For Ransomware Attacks Within Iot Networks, Jackson M. Walker Jan 2022

Ransombuster Iot: A Intrusion Detection And Dataset Creation Tool For Ransomware Attacks Within Iot Networks, Jackson M. Walker

Cybersecurity Undergraduate Research Showcase

The proposed research follows the design-science guidelines(Hevner, 2004). This paper uses these design-science methods for developing the guidelines for the implementation of the proposed architecture, understanding previous research contributions, and evaluating of research. This paper proposes a network artifact for studying ransomware IoT intrusion detection techniques and offers a proposed network architecture to serve as a framework for creating a publicly available dataset for IoT research on ransomware.

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Deepfakes: Ai Technology Of The Future, Hosanna Root Jan 2022

Deepfakes: Ai Technology Of The Future, Hosanna Root

Cybersecurity Undergraduate Research Showcase

Deepfakes technology’s danger stems from its ability to create realistic but fake synthesized media that people often identify as something that is real. With this powerful technology in the wrong hands, deepfakes can cause devastating havoc through information warfare, election campaign disruptions, and more, creating distrust in society. Disinformation is already rampant today, even without wide deployments of deepfakes, which is concerning given the fact that deepfakes’ nefarious full potentials are yet to be reached.

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Security Issues With Network Connected Scada Systems, Chad Holm Jan 2022

Security Issues With Network Connected Scada Systems, Chad Holm

Cybersecurity Undergraduate Research Showcase

The use of Supervisory Control and Data Acquisition (SCADA) systems has become common place and are being used in several different industries. These have evolved as the technology has progressed. The use of Internet of Things (IOT) devices makes for less human intervention to run daily operations in these industries. This can also allow hackers to gain access to these devices due to security holes that are overlooked. There have several different ways that have been exploited on SCADA networks and the goal is to recognize and secure them so hackers cannot gain access to them.

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Corporate Cybersecurity In The Context Of M&A Transactions, Cameron Beck Jan 2022

Corporate Cybersecurity In The Context Of M&A Transactions, Cameron Beck

Cybersecurity Undergraduate Research Showcase

The rapid rise of digital devices has unlocked a new dimension of innovation and prosperity in the 21st century. Computers are now an integrated and ubiquitous part of our global culture. You would be hard-pressed to walk into any given room without several computer chips humming inaudibly inside the machines that facilitate our modern world. Even lightbulbs and doorbells are connected to the Internet, capturing information from the world around them and sending that information to the Cloud. The Internet expands access to communication, international marketplaces, entertainment, professional resources, and nearly every book in the world.

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Examining Cooperative System Responses Against Grid Integrity Attacks, Alexander D. Parady Jan 2022

Examining Cooperative System Responses Against Grid Integrity Attacks, Alexander D. Parady

Honors Undergraduate Theses

Smart grid technologies are integral to society’s transition to sustainable energy sources, but they do not come without a cost. As the energy sector shifts away from a century’s reliance on fossil fuels and centralized generation, technology that actively monitors and controls every aspect of the power infrastructure has been widely adopted, resulting in a plethora of new vulnerabilities that have already wreaked havoc on critical infrastructure. Integrity attacks that feedback false data through industrial control systems, which result in possible catastrophic overcorrections and ensuing failures, have plagued grid infrastructure over the past several years. This threat is now at …

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Improving Collaborative Recommendation Based On Item Weight Link Prediction, Sahraoui Kharroubi, Youcef Dahmani, Omar Nouali Jan 2022

Improving Collaborative Recommendation Based On Item Weight Link Prediction, Sahraoui Kharroubi, Youcef Dahmani, Omar Nouali

Turkish Journal of Electrical Engineering and Computer Sciences

There is a continuous information overload on the Web. The problem treated is how to have relevant items (documents, products, services, etc.) at time and without difficulty. Filtering system also called recommender systems are widely used to recommend items to users by similarity process such as Amazon, MovieLens, Cdnow, etc. In the literature, to predict a link in a bipartite network, most methods are based either on a binary history (like, dislike) or on the common neighbourhood of the active user. In this paper, we modelled the recommender system by a weighted bipartite network. The bipartite topology offers a bidirectional …

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A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization, Hesamoddin Tahami, Hengameh Fakhravar Jan 2022

A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization, Hesamoddin Tahami, Hengameh Fakhravar

Engineering Management & Systems Engineering Faculty Publications

There are several approaches for solving hard optimization problems. Mathematical programming techniques such as (integer) linear programming-based methods and metaheuristic approaches are two extremely effective streams for combinatorial problems. Different research streams, more or less in isolation from one another, created these two. Only several years ago, many scholars noticed the advantages and enormous potential of building hybrids of combining mathematical programming methodologies and metaheuristics. In reality, many problems can be solved much better by exploiting synergies between these approaches than by “pure” classical algorithms. The key question is how to integrate mathematical programming methods and metaheuristics to achieve such …

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Validating Software States Using Reverse Execution, Nathaniel Christian Boland Jan 2022

Validating Software States Using Reverse Execution, Nathaniel Christian Boland

Browse all Theses and Dissertations

A key feature of software analysis is determining whether it is possible for a program to reach a certain state. Various methods have been devised to accomplish this including directed fuzzing and dynamic execution. In this thesis we present a reverse execution engine to validate states, the Complex Emulator. The Complex Emulator seeks to validate a program state by emulating it in reverse to discover if a contradiction exists. When unknown variables are found during execution, the emulator is designed to use constraint solving to compute their values. The Complex Emulator has been tested on small assembly programs and is …

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Synthetic Aperture Ladar Automatic Target Recognizer Design And Performance Prediction Via Geometric Properties Of Targets, Jacob W. Ross Jan 2022

Synthetic Aperture Ladar Automatic Target Recognizer Design And Performance Prediction Via Geometric Properties Of Targets, Jacob W. Ross

Browse all Theses and Dissertations

Synthetic Aperture LADAR (SAL) has several phenomenology differences from Synthetic Aperture RADAR (SAR) making it a promising candidate for automatic target recognition (ATR) purposes. The diffuse nature of SAL results in more pixels on target. Optical wavelengths offers centimeter class resolution with an aperture baseline that is 10,000 times smaller than an SAR baseline. While diffuse scattering and optical wavelengths have several advantages, there are also a number of challenges. The diffuse nature of SAL leads to a more pronounced speckle effect than in the SAR case. Optical wavelengths are more susceptible to atmospheric noise, leading to distortions in formed …

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A Progressive Learning Strategy For Large-Scale Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari Jan 2022

A Progressive Learning Strategy For Large-Scale Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, the worldwide temperature increase has resulted in rapid deglaciation and a higher risk of glacier-related natural hazards such as flooding and debris flow. Due to the severity of these hazards, continuous observation and detailed analysis of glacier fluctuations are crucial. Many such analyses require an accurately delineated glacier boundary. However, the complexity and heterogeneity of glaciers, particularly debris-covered glaciers (DCGs), poses a challenge for glacier mapping when using conventional remote sensing or machine-learning techniques. Some examples exist about small-scale automated glacier mapping, but large or regional-scale mapping is challenging. Previously, a deep-learning-based approach named GlacierNet2 had been …

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