Computer Sciences Commons^™

Some Legal And Practical Challenges In The Investigation Of Cybercrime, Ritz Carr

Cybersecurity Undergraduate Research Showcase

According to the Internet Crime Complaint Center (IC3), in 2021, the United States lost around $6.9 billion to cybercrime. In 2022, that number grew to over $10.2 billion (IC3, 2022). In one of many efforts to combat cybercrimes, at least 40 states “introduced or considered more than 250 bills or resolutions that deal significantly with cybersecurity” with 24 states officially enacting a total of 41 bills (National Conference on State Legislatures, 2022).

The world of cybercrime evolves each day. Nevertheless, challenges arise when we investigate and prosecute cybercrime, which will be examined in the following collection of essays that highlight …

The Linkage Between The Climate Change And The Cybercrimes, Min Kim

Cybersecurity Undergraduate Research Showcase

At the beginning of the new era, the rise of the Fourth Industrial Revolution has been rapidly transforming society into a new form that has never been experienced before. While previous industrial revolutions have also contributed to societal growth through phenomenal inventions and discoveries, the Fourth Industrial Revolution has the potential to break the most conventional rule, and one that has dominated social and economic activities: physical interaction. In the near future, sitting at the office, having an in-person meeting, or going on a business trip may no longer be needed as physical barriers are destroyed by cyberspace. However, two …

A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee

Computer Science and Engineering Faculty Publications

Engagement is enhanced by the ability to access the state of flow during a task, which is described as a full immersion experience. We report two studies on the efficacy of using physiological data collected from a wearable sensor for the automated prediction of flow. Study 1 took a two-level block design where activities were nested within its participants. A total of five participants were asked to complete 12 tasks that aligned with their interests while wearing the Empatica E4 sensor. This yielded 60 total tasks across the five participants. In a second study representing daily use of the device, …

Rethinking Integrated Computer Science Instruction: A Cross-Context And Expansive Approach In Elementary Classrooms, Umar Shehzad, Jody E. Clarke-Midura, Kimberly Beck, Jessica F. Shumway, Mimi M. Recker

Publications

This study examines how a rural-serving school district aimed to provide elementary level computer science (CS) by offering instruction during students’ computer lab, a class taught by paraprofessional educators with limited background in computing. As part of a research practice partnership, cross-context mathematics and CS lessons were co-designed to expansively frame and highlight connections across – as opposed to integration within – the two subjects. Findings indicate that the paraprofessionals teaching the lessons generally reported positive experiences and understanding of content; however, those less comfortable with the content reported lower student interest. Further, most students who engaged with the lessons …

A Unified Approach That Makes Online Taxi Service More Effective, Jiyao Li

Student Research Symposium

We propose a unified approach for scheduling taxis across a city. Balancing the supplies and demands on a city scale is a challenging problem in the field of online taxi services. To tackle the problem, we design a unified approach considering two important processes: Taxi-Rider Matching and Taxi Guidance. In the Taxi-Rider Matching, with the help of Lottery Selection (LS) and smoothed popularity score, the approach can balance supplies and demands well, both in the local neighborhood areas and hot places across the city. Regarding Taxi Guidance, we propose Q-learning Idle Movement (QIM) to direct vacant taxis to the most …

Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes, Tuo Zhao, Hanqiang Deng, Jialong Gao, Jian Huang

Journal of System Simulation

Abstract: In order to solve the problem that the distributed multi-UAV target assignment algorithm is prone to communication redundancy, which leads to the large communication scale of formation, a multi-UAV dynamic target assignment algorithm (CU-CBBA) based on node clustering in communication network is proposed.The algorithm introduces the communication network node grouping clustering strategy. According to the node's degree centrality, feature vector centrality, intermediate centrality and other attributes, the network node importance ranking model is established. A group of key nodes in the network topology structure are selected and the network topology node clustering is completed according to the shortest …

Trajectory Control Of Crawler Robot Based On Lstm And Smc, Dongyang Liu, Wenwen Zha, Liang Tao, Cheng Zhu, Lichuan Gu, Jun Jiao

Journal of System Simulation

Abstract: Trajectory tracking is an important part of mobile robot control technology and possesses prospect. Highly nonlinear dynamic characteristics are the main obstacles of controller design. A SMC method based on LSTM and quasi-sliding mode is proposed. The kinematics model and dynamics model of the tracked vehicle are given, and the sliding mode control system is established based on the dynamics model. LSTM network based on deep learning method is designed to control and compensate the unknown interference items, reduce the influence of external interference, and reduce the tremor phenomenon by combining the advantages of LSTM network and quasi-sliding …

Research On Modeling And Scheduling Of Virtual Power Plant With Dual Demand Response, Qiang Chen, Yi Wang, Kangshun Li

Journal of System Simulation

Abstract: Virtual power plant technology provides an effective means to aggregate distributed power and user side resources to participate in power scheduling. Most of the existing research focus on the scheduling optimization of distributed energy instead of the demand response of user side. The user side resources are divided into contracted reliable response load and non-contracted random response load, and the load response is regulated through price adjustment mechanism to adapt to the change of distributed. A virtual power plant optimal scheduling model with dual demands response is constructed, in which the maximizing overall profit of the power grid is …

Voltage And Reactive Power Combinational Evaluation Of Regional Power Grid Based On Ewm-Ahp-Bp Neural Network, Yuqi Ji, Huan Xie, Shaoyu Shi, Ping He, Nan Jin, Huili Wang

Journal of System Simulation

Abstract: In order to quantitatively evaluate the influence of renewable energy access on voltage and reactive power operation, a combinational evaluation method of voltage and reactive power based on EWM-AHP-BP neural network is proposed to carry out the multi-objective evaluation weight calculation. Considering voltage qualified rate, voltage fluctuation, power factor qualified rate and reactive power reserve, the comprehensive evaluation model is established. The operation data of renewable energy and power load are clustered to divide the typical scenarios and the evaluation model under multiple scenarios is scored by the combination method of entropy weight method and analytic hierarchy process. The …

Research On Modeling And Solution Method Of Operational Tasks Assignment, Yue Ma, Lin Wu, Shengming Guo

Journal of System Simulation

Abstract: Aiming at the prewar operational tasks assignment in operation task planning, a multi constraint model of operational tasks assignment is constructed to describe the dynamic mapping relationship between operational tasks and operational units. The solution strategy of decision space pruning and constraint condition judgment is proposed, and the methods of decision variable coding, assignment scheme decoding and phased fitness calculation are described. Differential evolution algorithm is used to work out the solution. The experimental results show that the multi constraint assignment model and solution algorithm can effectively reduce the scale of decision space, and can improve the rationality …

Cyber Security In Cyber Space, James D. Lee Jr.

Cybersecurity Undergraduate Research Showcase

For almost twenty years, the Internet has been a driving force in global communication and an integral part of people's everyday lives. As a result of technical developments and declining prices, over 3 billion people worldwide now utilize the Internet. The Internet has created a global infrastructure, and it is worth billions of dollars annually to the global economy (Judge et al.). Today's economic, commercial, cultural, social, and governmental activities and exchanges occur in Cyberspace, involving individuals, enterprises, non-profit organizations, and government and governmental agencies (Aghajani and Ghadimi 220). Cyberspace is the birthplace of much of the world's most essential …

Knowledge Graph-Based Process Knowledge Reasoning Method For Intelligent Production System, Weikai Yang, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the disadvantages of high redundancy and weakness between knowledge and data in intelligent production system, and the difficulty to perform knowledge reasoning, a process knowledge reasoning method for knowledge maps is proposed. The input information is semantically labeled and classified, the characteristics of the information match are extracted, the extracted local feature and global feature are associated through graph convolution method, and the feature of the difference value information is integrated and mapped with the constructed knowledge graph. Different reasoning rules are used according to different reasoning types, and the association and topology information between instances are …

Adaptive Correction Tracking Algorithm Based On Detector And Locator Fusion, Yecai Guo, Cheng Liu

Journal of System Simulation

Abstract: In order to avoid tracking failure caused by occlusion, rotation and other factors in complex dynamic scenes, an adaptive correction tracking algorithm based on detector and locator fusion is proposed. The locator trains a convolutional neural network (CNN) filter for location estimation by extracting the deep features of target. The CNN filter adds two layers of shallow features to the three layers of the convolution features of original CF2 algorithm, which enhances the extraction of target texture information. The detector calculates the confidence score by extracting histogram of oriented gradient(HOG) feature of target and combining the context information. …

Cross-Domain Text Sentiment Classification Based On Auxiliary Classification Networks, Na Ma, Tingxin Wen, Xu Jia, Xiaohui Li

Journal of System Simulation

Abstract: To align exactly the texts with same sentiment polarities of source and target domains, and to enlarge the feature difference of different sentiment texts as much as possible, a domain adaptation model with weighted adversarial networks is proposed. A new structured classification network consisting of a main classification network and an auxiliary classification network is proposed, in which the main classification network is used to perform supervised learning on the labeled texts of the source domain, and the auxiliary classification network is used to improve the distinguishability of the text features. A calculation method of multiple adversarial network weights …

Dual Resource Constrained Flexible Job Shop Energy-Saving Scheduling Considering Delivery Time, Hongliang Zhang, Jingru Xu, Bo Tan, Gongjie Xu

Journal of System Simulation

Abstract: To handle the flexible job shop energy-saving scheduling with machines and workers constraints, on the considering of delivery time, the optimization model of dual resource constrained flexible job shop energy-saving scheduling is established with the goal of minimizing the total earliness and tardiness penalties, and total energy consumption. An improved non-dominated sorting genetic algorithm II(INSGA-II) is proposed. Aiming at the optimized objectives, a three-stage decoding method is designed to gain more feasible solutions. The dynamic adaptive crossover and mutation operators are applied to get more excellent individuals. The crowding distance is improved to obtain a population with better …

Shared Subnet Synthesis And Application Of Object-Oriented Pres Net, Chuanliang Xia, Maibo Guo, Zhuangzhuang Wang, Yan Sun

Journal of System Simulation

Abstract: Focus on embedded system modeling, a solution to obtain a synthesized net via the shared subnet of an extended Petri net is proposed. Object-oriented technology and Petri net-based representation for embedded system (PRES net) are merged to obtain an object-oriented PRES net (OOPRES net). A method of synthesized operation of the shared subnet of OOPRES net is proposed, and the preservation of the liveness and boundedness of synthesized net system is studied. Taking the modeling analysis of intelligent transportation system as an example, the effectiveness of the synthesized method is verified. The method can provide an effective way for …

Research On Improvement Of Social Force Model Based On Non-Motor Vehicle Active Overtaking Behavior, Minghui Yang, Rui Zhang, Qiaobing Yan, Jiahe Wang

Journal of System Simulation

Abstract: Aiming at the social force model not to illustrate the active overtaking behavior of the rear non-motor vehicle to the front vehicle, an improved social force model is proposed. The traffic behavior characteristics of non-motorized vehicles mixed flow during the active overtaking is analyzed. Considering the compressible characteristics of non-motorized vehicle distancing in different density environments, the model is improved by presenting the concept of dynamic perception space and introducing the overtaking force into the social force model. The model is verified by analyzing the active overtaking behavior, active overtaking distance and speed-density basic graphs. The results indicate that …

Multi-Agent Cooperative Combat Simulation In Naval Battlefield With Reinforcement Learning, Ding Shi, Xuefeng Yan, Lina Gong, Jingxuan Zhang, Donghai Guan, Mingqiang Wei

Journal of System Simulation

Abstract: Due to the rapidly-changed situations of future naval battlefields, it is urgent to realize the high-quality combat simulation in naval battlefields based on artificial intelligence to comprehensively optimize and improve the combat effectiveness of our army and defeat the enemy. The collaboration of combat units is the key point and how to realize the balanced decision-making among multiple agents is the first task. Based on decoupling priority experience replay mechanism and attention mechanism, a multi-agent reinforcement learning-based cooperative combat simulation (MARL-CCSA) network is proposed. Based on the expert experience, a multi-scale reward function is designed, on which a naval …

Research Progress Of Opponent Modeling Based On Deep Reinforcement Learning, Haotian Xu, Long Qin, Junjie Zeng, Yue Hu, Qi Zhang

Journal of System Simulation

Abstract: Deep reinforcement learning is an agent modeling method with both deep learning feature extraction ability and reinforcement learning sequence decision-making ability, which can make up for the depleted non-stationary adaptation, complex feature selection and insufficient state-space representation ability of traditional opponent modeling. The deep reinforcement learning-based opponent modeling methods are divided into two categories, explicit modeling and implicit modeling, and the corresponding theories, models, algorithms and applicable scenarios are sorted out according to the categories. The applications of deep reinforcement learning-based opponent modeling techniques on different fields are introduced. The key problems and future development are summarized to provide …

Research On Workshop Logic Modeling And Simulation Based On Finite State Machine, Mingyuan Liu, Jiaxiang Xie, Hao Wu, Jianlin Fu, Guofu Ding

Journal of System Simulation

Abstract: Discrete manufacturing is common in aircraft, ships, electronic equipment, automobile and other manufacturing industries. To ensure the correctness and flexibility of the modeling and simulation process of discrete manufacturing workshops, a logical modeling and simulation method for the production process of discrete manufacturing workshop is proposed. Based on the theory of discrete event dynamic systems and finite-state machines, the attributes and behaviors of the key elements of the discrete manufacturing workshop are abstracted into a unified logic model, and the function of various elements are realized through inheritance. A production process simulation algorithm is designed for the unified model …

Research On Unmanned Swarm Combat System Adaptive Evolution Model Simulation, Zhiqiang Li, Yuanlong Li, Laixiang Yin, Xiangping Ma

Journal of System Simulation

Abstract: Aiming at the fact that the intelligent unmanned swarm combat system is mainly composed of large-scale combat individuals with limited behavioral capabilities and has limited ability to adapt to the changes of battlefield environment and combat opponents, a learning evolution method combining genetic algorithm and reinforcement learning is proposed to construct an individual-based unmanned bee colony combat system evolution model. To improve the adaptive evolution efficiency of bee colony combat system, an improved genetic algorithm is proposed to improve the learning and evolution speed of bee colony individuals by using individual-specific mutation optimization strategy. Simulation experiment on …

I-Nicemo Enhanced Algorithm Based On Intersection Angel Geometry, Yifan He, Yulin He, Yongda Cai, Zhexue Huang

Journal of System Simulation

Abstract: To exactly determine the number of cluster centers and correctly identify the candidate cluster centers, an I-niceMO enhanced(I-niceMOEn) algorithm based on intersection angel geometry is proposed. As many distributions of intersection angles and distances as possible between observation points and data points are utilized to recognize the candidate cluster centers to avoid the neglection of cluster centers. The spectral clustering algorithm is used to automatically merge the candidate cluster centers according to the eigenvalues of Laplacian matrices. The number of final cluster centers is determined by the number of merged candidate cluster centers. The number of clusters can be …

Dynamics Modeling And Online Prediction Of Energy Consumption Of Discrete Manufacturing System, Wei Chen, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the traditional energy consumption modeling methods of discrete manufacturing system being difficult to adapt to the complexity and variability of working conditions, an online dynamic energy consumption modeling method based on real-time data is proposed. The energy consumption affecting factors are determined by analyzing the operation mechanism of the discrete manufacturing system and equipment. An online sequential extreme learning machine algorithm that can dynamically adjust the number of hidden layer nodes is proposed to construct the energy consumption model. The real-time data can update the model quickly. Bernstein's inequality is introduced to improve the model data screening …

Construction Technology Of Hand Posture Dataset Based On Virtual Simulation Method, Jiaxin Chen, Guohui Zhou, Jianbai Yang

Journal of System Simulation

Abstract: Hand posture is an important carrier of human-computer interaction, and the acquisition and recognition of posture information largely depends on the hand posture dataset. Existing datasets can be divided into two categories, real datasets and synthetic datasets. As real data is limited by equipment, environment, and other factors, the classification of hand posture is insufficient and the annotation is mixed with a lot of manual errors. The existing synthetic data can solve the data scale problem of real data, but the synthetic hand posture volume is limited and with some unreasonable kinematic postures of which the data form are …

Bottleneck Drift Fluctuation Analysis Of Discrete Remanufacturing System Under Disturbance, Yongzhang Zhou, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Considering comprehensively the influence of each production process on the bottleneck degree of discrete remanufacturing system, the interval bottleneck index matrix is established by collecting data repeatedly in the observation stage to obtain the comprehensive bottleneck index of equipment, which is used as the identification basis. Aiming at the volatility of bottleneck drift in the uncertain environment of discrete remanufacturing system, based on the interval bottleneck index matrix and comprehensive bottleneck index, a theoretical method of visual dynamic analysis including system sensitivity coefficient, machine sensitivity coefficient and bottleneck drift judgment model is established. The discrete event simulation case is …

Atmospheric Corrosion Simulation Of Air Conditioning Heat Exchanger In Service Under Marine Environment, Huang Peng, Jun Wang, Li Qi, Zhidong Wu

Journal of System Simulation

Abstract: Aiming at the performance degradation of airconditioner heat exchanger caused by serious corrosion under marine environment, an atmospheric corrosion simulation method is studied to analyze and predict the influence on corrosion conditions of marine environment and working condition of air conditioner heat exchanger. From the acquisition of material parameters, the construction the model and the setting of boundary conditions, the atmospheric corrosion simulation process of air conditioner heat exchanger in service under marine environment is systematically introduced, and a method to verify the accuracy of the simulation model by using an artificially accelerated environmental test chamber is provided. From …

Introduction To Ensemble Watershed Segmentation, Scout Jarman

Student Research Symposium

Compared to color images, hyperspectral images are high dimensional, containing hundreds of channels of information. To distill this information, and capture spatial information, image segmentation is used to group similar pixels together. A popular image segmentation algorithm is the marker-based Watershed Transform. One difficulty with this algorithm is choosing the markers, or locations, that seed the algorithm. There are various approaches for automatic marker placement depending on the application, with little consensus on the most general method for hyperspectral images. We propose using an ensemble of random segmentations. Specifically, we investigate a simple, unbiased random marker placement strategy to generate …

Neutrosophic Marcos In Decision Making On Smart Manufacturing System, Nivetha Martin, Said Broumi, S. Sudha, R. Priya

Neutrosophic Systems with Applications

Business firms prefer software-based smart manufacturing systems to monitor and supervise all production activities in a decentralized manner. The choice of software decides the degree of manufacturing robustness. This paper proposes a neutrosophic-based MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method of MCDM with single-valued triangular neutrosophic numbers to solve the software selection problem. The proposed neutrosophic method is applied to hypothetical data to test the efficacy of the method. The results obtained using the proposed method are compared with crisp, fuzzy, and intuitionistic data representations, and suitable inferences are acquired. The proposed method has several industrial …

Neutrosophic Marcos In Decision Making On Smart Manufacturing System, Nivetha Martin, Said Broumi, S. Sudha, R. Priya

Neutrosophic Systems with Applications

Business firms prefer software-based smart manufacturing systems to monitor and supervise all production activities in a decentralized manner. The choice of software decides the degree of manufacturing robustness. This paper proposes a neutrosophic-based MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method of MCDM with single-valued triangular neutrosophic numbers to solve the software selection problem. The proposed neutrosophic method is applied to hypothetical data to test the efficacy of the method. The results obtained using the proposed method are compared with crisp, fuzzy, and intuitionistic data representations, and suitable inferences are acquired. The proposed method has several industrial …

Multi-Modal Knowledge Graph Inference Via Media Convergence And Logic Rule, Feng Lin, Dongmei Li, Wenbin Zhang, Dongsheng Shi, Yuanzhou Jiao, Qianzhong Chen, Yiying Lin, Wentao Zhu

Michigan Tech Publications, Part 1

Media convergence works by processing information from different modalities and applying them to different domains. It is difficult for the conventional knowledge graph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledge graph inference less effective. To address the issue, an inference method based on Media Convergence and Rule-guided Joint Inference model (MCRJI) has been proposed. The authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link prediction. First, a multi-headed self-attention approach …