Computer Sciences Commons^™

Managing Cybersecurity In Local Governments: 2022, Donald F. Norris Phd, Laura K. Mateczun Jd

Journal of Cybersecurity Education, Research and Practice

This paper, based on data from our second nationwide survey of cybersecurity among local or grassroots governments in the U.S., examines how these governments manage this important function. As we have shown elsewhere, cybersecurity among local governments is increasingly important because these governments are under constant or nearly constant cyberattack. Due to the frequency of cyberattacks, as well as the probability that at least some attacks will succeed and cause damage to local government information systems, these governments have great responsibility to protect their information assets. This, in turn, requires these governments to manage cybersecurity effectively, something our data show …

Ai Culture ‘Profiling’ And Anti-Money Laundering: Efficacy Vs Ethics, John W. Goodell, Cal B. Muckley, Parvati Neelakantan, Darragh Ryan

University Research

Using extensive transaction and money laundering detection data, at a globally important financial institution, we investigate the efficacy of including facets of national culture in formulating anti-money laundering predictions. For corporate and individual accounts, Hofstede individualism scores of the country in which a customer is resident, or from which a wire is sent/received, are of first-order importance in the detection of money laundering. When combined with account and transaction data; as well as even a proprietary institutional algorithm, individualism scores continue to determine the models’ predictive performances. The efficacy of cultural profiling in money laundering detection underscores the need for …

Self Supervised Artificial Intelligence Predicts Poor Outcome From Primary Cutaneous Squamous Cell Carcinoma At Diagnosis, Nicolas Coudray, Michelle C. Juarez, Maressa C. Criscito, Adalberto Claudio Quiros, Reason Wilken, Stephanie R. Jackson Cullison, Mary L. Stevenson, Nicole A. Doudican, Ke Yuan, Jamie D. Aquino, Daniel M. Klufas, Jeffrey P. North, Siegrid S. Yu, Fadi Murad, Emily Ruiz, Chrysalyne D. Schmults, Cristian D. Cardona Machado, Javier Cañueto, Anirudh Choudhary, Alysia N. Hughes, Alyssa Stockard, Zachary Leibovit-Reiben, Aaron R. Mangold, Aristotelis Tsirigos, John A. Carucci

Department of Dermatology and Cutaneous Biology Faculty Papers

Primary cutaneous squamous cell carcinoma (cSCC) is responsible for ~10,000 deaths annually in the United States. Stratification of risk of poor outcome at initial biopsy would significantly impact clinical decision-making during the initial post operative period where intervention has been shown to be most effective. Using whole-slide images (WSI) from 163 patients from 3 institutions, we developed a self supervised deep-learning model to predict poor outcomes in cSCC patients from histopathological features at initial diagnosis, and validated it using WSI from 563 patients, collected from two other academic institutions. For disease-free survival prediction, the model attained a concordance index of …

Limitations In Speech Recognition For Young Adults With Down Syndrome, Franceli L. Cibrian, Yingying 'Yuki' Chen, Kayla Anderson, Cecilia Marie Abrahamsson, Vivian Genaro Motti

Engineering Faculty Articles and Research

Speech recognition has the potential to make technology more accessible to users. However, the accuracy of speech recognition remains limited for users with disabilities, including those with Down Syndrome, and the types and frequencies of recognition errors are poorly understood. This paper characterizes these problems, focusing on errors occurring when recognizing Down Syndrome speech. We analyze the transcripts from six speech recognition algorithms (Google, IBM, Otter.ai, Microsoft, AssemblyAI, OpenAI) using the audio content of 15 individuals with Down Syndrome (331 dialogues; 3428 words). Our analysis shows: (1) significant difference in speech recognition accuracy for people with Down Syndrome compared to …

Promoting Digital Agriculture Adoption In Community-Based Agricultural Organizations, Jean Hardy, Abbey Palmer

Journal of Extension

Existing research and practice related to digital agriculture technology adoption is largely focused on large-scale producers. In this paper, we describe a case of adopting an advanced soil monitoring system in a community-based agricultural organization. We provide guidance for Extension professionals seeking to implement or promote digital agriculture technology adoption on: selecting appropriate technology, incorporating new technology into existing practices, harnessing local technology champions, and avoiding data-driven mission creep.

Improved Bidirectional A* Quadratic Path Planning Algorithm For Mobile Robots, Jiongyi Li, Qiang Li, Xinwen Zhang, Myo Htet Zin, Yongbin Cai

Journal of System Simulation

Abstract: Aiming at the problems of the traditional A* algorithm, such as the unhoped intersection between the planned path and the obstacles, the planned path has many inflection points and the search time is long, an improved bidirectional A* quadratic path planning algorithm for the indoor environments is proposed. Through the expansion of the map, the intersection between the planned path and the obstacle is solved. By new heuristic functions and bidirectional expansion methods, the search speed and accuracy of the bidirectional A* algorithm are improved. Turning cost function and adaptive weight are introduced to reduce the number of turning …

Collaborative Optimization Problem Of Dynamic Pre-Maintenance And Green Scheduling, Yuyan Jiang, Ning Ma, Yan Li, Rumeijiang Gan, Fuyu Wang

Journal of System Simulation

Abstract: For the traditional flexible job shop scheduling problem, a joint optimization of machine dynamic pre-maintenance and green scheduling is considered to establish an integrated optimization model with the optimization objectives of minimizing maximum completion time, total carbon emissions, and total cost. An improved NSGA-II algorithm is proposed to solve the model. A three-layer encoding method based on process, machine, and pre maintenance is adopted to design a one-step decoding scheme that considers process allocation, machine selection, and machine pre-maintenance strategies. The algorithm improves the elitist retention strategy, designs an adaptive crossover mutation function with algebraic changes, and a mutation …

Trajectory Optimization Of Robotic Arm Based On Improved Simulated Annealing Genetic Algorithm, Qiang Xu, Jianlei Xu, Yanhai Hu, Haihui Chen, Xing Zhang, Zhaohui Xing

Journal of System Simulation

Abstract: To optimize the working trajectory of the robotic arm, a modified simulated annealing genetic algorithm is proposed. Comprehensively considering the operating requirements and performance characteristics of the robotic arm, the five-order polynomial interpolation method is used to plan a smooth motion trajectory in the joint space. The penalty function method is used to handle the individuals that do not meet the constraint conditions, and the fitness function is recalibrated by the dynamic linear calibration method. An adaptive adjustment mechanism for crossover probability and variation probability is set to modify the genetic algorithm. The cooling idea of the simulated annealing …

An Algorithm For Cloud-Based Web Service Combination Optimization Through Plant Growth Simulation, Qiang Li, Huawei Qin, Bingqin Qiao, Ruifang Wu

Journal of System Simulation

Abstract: In order to improve the efficiency of cloud-based web services, an improved plant growth simulation algorithm scheduling model. This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources. Then, a lightinduced plant growth simulation algorithm was established. The performance of the algorithm was compared through several plant types, and the best plant model was selected as the setting for the system. Experimental results show that when the number of test cloud-based web services reaches 2 048, the model being 2.14 times faster than PSO, 2.8 times faster than the …

Research On Flexible Integrated Scheduling Under Stochastic Processing Times Based On Improved D3qn Algorithm, Xiang Li, Xiaoyu Ren, Yongbing Zhou, Jian Zhang

Journal of System Simulation

Abstract: Aiming at the problem of time uncertainty in discrete manufacturing workshops, we construct an integrated scheduling mathematical model with the optimization objective of minimizing the maximum completion time based on the consideration of equipment and process constraints, and propose an improved dual-competitive deep Q-network algorithm (ID3QN) to solve the flexible integrated scheduling problem under stochastic working hours. The levels of process, machine, and overall scheduling are designed as features. Eight composite scheduling rules are formed as the action space by combining process rules based on processing times, processing sequences, and process structure tree, along with machine rules relevant to …

Research On The Target Allocation Method For Air Defense And Anti-Missile Defense Of Naval Ships, Shuaidi Fei, Changlong Cai, Fei Liu, Minghui Chen, Xiaoming Liu

Journal of System Simulation

Abstract: To solve the problems of multiple types of state information and correlation of time-series state information encountered in the dynamic weapon target assignment problem, a dynamic weapon target assignment method based on an improved deep reinforcement learning algorithm is proposed. A multiinput assignment model of target missile-interceptor unit, interceptor unit, and defense unit under multiwave target and multi-phase is constructed. A multi-input state space is designed, and a Markov decision process is established in conjunction with the problem model. A feature extraction network combining multi-input information processing and gated recurrent network is designed, which improves the ability to extract …

Combat Effectiveness Evaluation Of Air Defense Missile Weapon System Based On Rbf Neural Network, Peng Zhang, Ke Feng, Jiancheng Gong, Xiaoqiang Yang, Jinxing Shen

Journal of System Simulation

Abstract: A combat effectiveness evaluation method based on RBF neural network is proposed to address the problems of high dimensionality, high complexity, and subjective evaluation methods in current air defense missile weapon systems. A combat effectiveness index system for air defense missile weapon systems has been constructed by analyzing the OODA environmental combat theory. The RBF neural network model simulation is implemented using MATLAB, and several methods such as BP, PCABP, and Elman neural network are compared and verified through simulation. The simulation results show that the predicted evaluation results of the RBF neural network model are closer to the …

Dynamic Loading Simulation Method For Large-Scale Spiking Neural Network, Jiawei Shen, Daye Cai, Guoqing Yang, Pan Lü, Hong Li

Journal of System Simulation

Abstract: To address the problem of high GPU memory requirements in large-scale spiking neural network simulation, a dynamic loading simulation method for large-scale spiking neural networks is proposed. This method uses data movement at the sub-network granularity and utilizes the host memory as a larger memory pool to reduce the limitation of GPU memory on the model simulation scale, enabling large-scale spiking neural network simulation on a single GPU computer. The pipeline acceleration technique is adopted to reduce the impact of data movement on simulation speed. The simulation of a million-scale neural network is achieved in a single GPU experimental …

Design And Simulation Analysis Of Guidance Law For Boost Phase Interceptor Missile, Xu Zhang, Peng Zeng, Xu Li, Xuehe Zheng, Jianheng Xue, Chao Wang

Journal of System Simulation

Abstract: The intercept time window in the boost phase is very short, which requires the missile to have high speed and high acceleration capability, at the same time, because the target ballistic missile is still accelerating in the boost phase, the guidance scheme of the interceptor missile needs to have the ability to cope with the characteristics of the booster phase interceptor missile. The trajectory simulation model is established, and the guidance law of the boost phase interceptor missile in the initial guidance, midguidance and final guidance stage are designed in detail according to the performance of the guidance mechanism …

Quadrotor Uav Path Planning Based On Rapidly-Exploration Directional Tree Algorithm, Shijun Hu, Hailiang Liu, Binglei Wang, Wenke Su

Journal of System Simulation

Abstract: Aiming at the problems of low planning success rate, slow convergence speed, and suboptimal paths in the RRT algorithm for quadrotor UAV path planning of in complex environments, a directional exploration tree algorithm is proposed, which uses a directional sampling strategy to improve the directionality of the tree expansion, and by introducing an adaptive target adjustment strategy and a branch expansion strategy, the tree can expand quickly towards the target point while avoiding obstacles. The redundant points in the initial path are removed by the pruning process, and then the trajectory correction and smoothing process are performed on the …

Research On Task Planning Methods For Space Robot Assisted Operation, Guoqiang Fang, Haitao Chang, Xing Liu, Zhengxiong Liu, Panfeng Huang

Journal of System Simulation

Abstract: In view of the difficulties caused by the complicated task process and numerous task constraints during the space robot assisted operation, a task planning method combining fast forward search algorithm and hierarchical network algorithm is proposed, in which the task planning process is divided into task planning and replanning. Based on the fast forward search task planning method of operation cost, the execution sequence of actions with minimum operation cost is obtained. The task adaptive replanning method based on hierarchical network corrects and compensates the problems according to the priority of compensation for the movement, grab and release actions. …

An Empirical Analysis Of New Perspectives For Strategy Solving In Intelligent Game-Theoretic Decision-Making, Jiongming Su, Junren Luo, Shaofei Chen

Journal of System Simulation

Abstract: With the development of artificial intelligence technology, especially the promotion of largescale pre-training model theory, some new perspectives of strategy solving for intelligent game-theoretic decision-making have gradually been widely concerned and discussed. This paper combines the development of artificial intelligence technology and the transformation of strategy solving paradigm for intelligent game-theoretic decision-making, takes Chess (two-player zero-sum perfect information game), diplomacy (multi-player general-sum imperfect information game), and StarCraft Multi-Agent Challenge (multi-agent Markov game) as the research object for empirical analysis on sequential decision-making, the new paradigm and new way of strategy solving are analyzed according to the new perspective of …

Intelligent Service Migration Towards Mec-Based Iov Systems, Sijin Huang, Jia Wen, Zheyi Chen

Journal of System Simulation

Abstract: To address the problem of QoS degradation during the vehicle movement, a novel service migration via convex-optimization-enabled deep reinforcement learning (SeMiR) method is proposed. The optimization problem is decomposed into two sub-problems and solved separately. For the service migration sub-problem, an improved deep reinforcement learning based service migration method is designed to explore the optimal migration policy. For the resource allocation sub-problem, a convex optimization based resource allocation method is developed to derive the optimal resource allocation for each MEC server under the given migration decisions, thereby improving the performance of service migration. Experimental results show that the SeMiR …

Intensity-Based Feature Filtering For Lidar-Based Slam, Weigang Li, Shaofeng Zou, Yongqiang Wang, Chuxiang Yu

Journal of System Simulation

Abstract: In order to solve the problem that an excessive influx of feature points into the point cloud registration phase can potentially lead to diminished algorithmic accuracy and suboptimal mapping outcomes, a novel laser SLAM algorithm predicated on the filtering of feature points through the utilization of intensity information is proposed. The intensity distribution near the feature points in the local map is calculated based on the point cloud intensity information, and each feature point within the local map is attributed an intensity distribution index. Through the application of an intensity threshold, feature points that exhibit substantial variations in intensity …

A Hybrid Heuristic Algorithm For Solving The Green Vrp With Priority Delivery, Huanhuan Cui, Lihe Guan

Journal of System Simulation

Abstract: This paper considers the problem that some customers' goods cannot be mixed in logistics distribution. Based on the traditional green vehicle routing problem with simultaneous pickup and delivery, customers are divided into three types: priority delivery, non-priority only pickup without delivery, and non-priority pickup with delivery. A single objective nonlinear optimization model is established to minimize the total cost. A hybrid heuristic method based on simulated annealing and adaptive large neighborhood search algorithm is designed. An improved saving algorithm is used to construct the initial solution. And 5 kinds of destruction operators and 2 kinds of repair operators are …

Point Cloud Registration Method Based On Improved Grey Wolf Algorithm And Adaptive Splitting Kd-Tree, Yuanhao Du, Xiuli Geng, Chengzhi Xu, Yinhua Liu

Journal of System Simulation

Abstract: Traditional GWO algorithms suffer from limitations such as insufficient search efficiency and susceptibility to local optima. A novel method for the registration of point clouds of complex industrial components is proposed based on an improved GWO algorithm and ICP. To address the problem of uneven population distribution caused by random initialization in GWO, chaotic mapping is employed to initialize the gray wolf population, ensuring a more uniform distribution of individuals within the search space. A non-linear control parameter strategy is introduced to strike a balance between the algorithm's local search and global search capabilities. Elite reverse learning is integrated …

Gaussian Chaotic Fire Hawk Optimization Algorithm For Solving Dynamic Optimization Problems, Yongzhang Chen, Yuanbin Mo

Journal of System Simulation

Abstract: There are many important chemical processes in the chemical industry rely on dynamic optimization with factors such as nonlinearity and discontinuity. In order to find a more efficient solution algorithm, Gaussian Chaotic fire hawk optimization algorithm is proposed based on the fire hawk optimization algorithm, which is used to solve such problems after parameterizing the control variables. The original way of initializing the populations is replaced using tent chaotic mapping in order to make more sense of the initial distribution of the algorithm; a more targeted update method has been proposed in the analysis of fire hawk location updates …

Coordinated And Optimal Dispatching For Wind-Photovoltaic-Storage Systems Based On Multi-Strategy Multi-Objective Differential Evolution Algorithm, Xuyang Ren, Xuhui Bu, Yanling Yin, Jinghua Liu

Journal of System Simulation

Abstract: The introduction of new energy generation units makes the power system structure more and more complex, and the existing economic dispatching methods face many challenges. A coordinated and optimal dispatching for wind-photovoltaic-storage systems is constructed and a constraint handling method is given, a competitive mechanism-based multi-strategy multi-objective differential evolutionary (CMMODE) algorithm is proposed. The CMMODE algorithm utilizes a competitive mechanism to partition the population and constructs multiple differential variance operators based on the partitioning results, thus generating a multi-strategy scheme, employs an elite self-exploration mechanism to make the population have the ability to jump out of the local optimum …

Research On Rule-Based Energy Management Strategy Of Hybrid Mining Dump Truck, Jiangong Liu, Yuanhui Zhang, Fei Wei, Yiying Wang, Xiaoling Li, Peiqing Liu, Fengmiao Si

Journal of System Simulation

Abstract: A distributed hybrid powertrain system structure and a rule-based energy management strategy are proposed to address the problems of insufficient power and poor fuel economy in conventional dieselpowered mining dump trucks. By analyzing the operational characteristics of mining dump trucks, a distributed hybrid powertrain system structure and vehicle driving conditions are established, relevant mode-switching rules are formulated. The results demonstrate that the proposed distributed hybrid powertrain system structure enhances the climbing capability of the vehicle by 27% when using the third gear for uphill driving. In addition, the adoption of the rule-based energy management strategy results in an 19% …

Construction Of A Digital Twin-Based Ship Manufacturing Workshop Monitoring System, Tianxiang Hu, Hui Ye, Xiaofei Yang

Journal of System Simulation

Abstract: In order to address issues of opacity in production information and difficulties in collecting equipment data in shipbuilding workshops, a digital twin ship manufacturing workshop monitoring system is designed based on the Unity physics platform. The essential steps in building a virtual reality platform are outlined, encompassing the creation of a virtual ship workshop, the development of data transmission methods for multi-source heterogeneous data acquisition, implementation of data-driven methods for achieving virtual-real synchronization, and enhancement of data visualization capabilities. By practically designing a real-time monitoring system for the welding assembly line production process in shipbuilding, the 3D scene reproduction …

Improved Target Detection Algorithm For Aerial Images Based On Yolov5, Yecai Guo, Jingdong Sun, Saha Amitave

Journal of System Simulation

Abstract: In order to improve the existing small target detection methods, which suffer from low detection accuracy, high false detection rate and high leakage rate, the FSD-YOLOv5 algorithm is proposed, which has three improvements based on the YOLOv5 algorithm. The Focal EIoU is used instead of the original CIoU to improve the model convergence speed and regression accuracy. To cope with the deficiencies in CNN architecture, we adopt a new CNN building block called SPD-Conv is adopted. To address the problem of the reduced or lost information of small objects in feature maps caused by downsampling in convolutional neural networks, …

Evaluating The New Nd: Yag Laser Method In Phytosynthesizing Silver Nanoparticles And Assessing Their Medical Applications., Arshad Mahdi Hamad, Qanat Mahmood Atiya

Karbala International Journal of Modern Science

Silver nanoparticles (AgNPs) were synthesized via an innovative green synthesis method using amygdalin (Am) as a reducing agent and the Nd: YAG laser as a catalyst. We studied the properties of the nanoparticles using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive X-ray spectroscopy (EDX), atomic force microscopy (AFM), ultraviolet-visible spectroscopy (UV), and Fourier transform infrared spectroscopy (FTIR) techniques. All the results of the examination demonstrate excellent structural and optical properties. In addition, the molecular docking of the complex composed of amygdalin and AgNPs was tested on three proteins concerned with the virulence of Pseudomonas aeruginosa and …

Integrating Neural Networks For Predictive Torque Control And Obstacle Avoidance In Autonomous Robot, Viswanath Kodali, Harsha Vardhan Borra, Kiran P

Northeast Journal of Complex Systems (NEJCS)

In the field of robotics, precise motion control and accurate computation of joint forces are critical for ensuring optimal performance. Traditional methods, such as using the Jacobian matrix for joint angle determination and Euler-Lagrange equations for torque computation, are reliable but computationally intensive, making them less suitable for real-time applications. This paper presents an advanced approach to improving the productivity and efficiency of a 3-Degree of Freedom (DOF) robotic arm by utilizing Artificial Neural Network (ANN). The proposed system dynamically predicts joint angles and torque, enabling faster and more efficient motion control.

To address the challenge of obstacle avoidance in …

The Evolution And Future Of Microservices Architecture With Ai-Driven Enhancements, Jill Willard, James Hutson

Faculty Scholarship

Microservices architecture has revolutionized software development by enabling the decomposition of monolithic applications into smaller, more manageable services. While this shift has reduced risks and enhanced system resiliency, the increasing complexity of managing numerous microservices presents new challenges. As Artificial Intelligence (AI) continues to evolve, there is a growing need to explore how autonomous AI agents can optimize microservices architectures, particularly in terms of communication and workflow orchestration. The purpose of this study is to investigate how AI agents can autonomously interact and manage microservices, reducing human intervention and enhancing system efficiency. The key research question guiding this investigation relates …

Characterization Of 1,8-Cineole (Eucalyptol) From Myrtle And Its Potential Antibacterial And Antioxidant Activities*, Humera Khan

Karbala International Journal of Modern Science

1,8-Cineole is a naturally occurring chemical molecule predominantly found in fragrant plants, particularly Myrtle. Its aroma is distinctive and has been the subject of numerous investigations due to its various biological actions. This study examines the characterization of 1,8-Cineole derived from Myrtle and investigates its antibacterial and antioxidant properties. This study seeks to compare 1,8-Cineole with antibiotics like Amoxicillin and Tetracycline, and moreover, to investigate its antioxidant capabilities against diverse bacterial strains (both Gram-positive and Gram-negative). 1,8-Cineole exhibits the most effective antibacterial properties, demonstrating an inhibition zone of 12.00 mm against Staphylococcus aureus and 10.00 mm against Pseudomonas aeruginosa. …