Computer Engineering Commons^™

Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Paul Thomas, Eric Webb, Jon Martin, Austin Walden

National Training Aircraft Symposium (NTAS)

An increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time-series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) embedded machine learning framework. Data cleanup and preparation has …

Research On Intelligent Optimization Method Of Combat Sos Based On Gabc Algorithm, Hucheng Zhang, Jingyu Yang

Journal of System Simulation

Abstract: In order to solve the problem that exploratory simulation can not traverse the solution space quickly, and provide the auxiliary decision-making scheme in real time, a genetic algorithm based on classifier is proposed. The framework of simulation optimization method based on the algorithm is established. It can find the optimal solution according to the dynamic changes of key factors and decision targets of the system, which is suitable for such as seeking the best efficiency-cost ratio scheme and the optimization of the optimal power deployment and other systems. Based on the simulation bed system of the National Defense …

Chameleon Swarm Algorithm For Segmental Variation Learning Of Population And S-Type Weight, Damin Zhang, Yi Wang, Linna Zhang

Journal of System Simulation

Abstract: It is the best choice for intelligent algorithms to be applied to specific fields to explore strong searching ability, good reliability and stability.In this paper, aiming at the defects of chameleon swarm algorithm, such as unstable solution, low convergence accuracy and unbalanced search and development, a chameleon swarm algorithm (RMSCSA) based on population diversity segmental mutation learning and S-type weight is proposed. The refraction mirror learning strategy (RML) is introduced to make the chameleon more consistent with the observation in nature and enhance its diversity. The introduction of segmental variation of population diversity can keep the individuals with poor …

Development Opportunities And Application Prospects Of Aero-Engine Simulation Technology Under Digital Transformation, Jianguo Cao

Journal of System Simulation

Abstract: The development of China's social economy and the improvement of its national defense capability in the new era put forward higher requirements for the development of aero-engines. It is urgent to promote the digital transformation of aero-engines in order to achieve coordinated, agile and efficient aero-engine development. Based on the current research and development of aero-engine in China, this paper clarifies the new connotation of "speediness and efficiency, accurate mapping, comprehensive coverage, and dynamic prediction" given by the development of emerging cutting-edge technologies to aero-engine simulation technology, as well as the new technical features of "spatio-temporal ubiquity, data driven, …

Research On Mixed Flow Line Balancing And Scheduling Optimization With Multiple Constraints, Zhenping Li, Ying Shi, Lingyun Wu

Journal of System Simulation

Abstract: Aiming at the phenomena of unbalanced load between stations and product accumulation caused by unreasonable design of mixed flow line in G enterprise, based on the matching relationship between processes and stations, cycle time, process priority and other constraint, with the objectives of reducing the number of stations, balancing the workload between stations, and reducing the products waiting time, a multi-objective mixed integer programming model for mixed flow line balance and product scheduling problem is established. A hierarchical algorithm and a hybrid heuristic algorithm are designed respectively; the accuracy of the hierarchical algorithm is verified by small-scale …

Large-Scale Multi-Objective Natural Computation Based On Dimensionality Reduction And Clustering, Weidong Ji, Yuqi Yue, Xu Wang, Ping Lin

Journal of System Simulation

Abstract: In multi-objective optimization problems, as the number of decision variables increases, the optimization ability decreases significantly. To solve "dimension disaster", a large-scale multi-objective natural computation method based on dimensionality reduction and clustering is proposed. The decision variables are optimized by locally linear embedding(LLE) to obtain the representation of high-dimensional variables in the low-dimensional space, then the individuals are grouped through K-means to select the appropriate guide individuals for the population to strengthen the convergence and diversity. To verify the effectiveness, the method is applied to the multi-objective particle swarm optimization algorithm and the non-dominated sorting genetic algorithm. The convergence …

Research On Vr Experience Comfort Based On Motion Perception, Wei Quan, Chao Wang, Xuena Geng, Cheng Han

Journal of System Simulation

Abstract: A VR video comfort evaluation model based on motion perception is proposed for viewers who will feel discomfort such as vertigo and nausea after a virtual reality (VR) experience. By performing dense optical flow estimation on stereoscopic VR video and calculating the video frame velocity matrix by analyzing the horizontal and vertical motions in the scene, the frame acceleration feature extraction methods based on frame difference method and based on time domain are proposed. Taking the extracted velocity, acceleration and other motions features as input, a model is established using the support vector regression algorithm, and VR video experience …

Drosophila Retina Simulation System And The Emergence Of Orientation Selectivity, Ziyu Liu, Yiran Zhuo, Zhuoyi Song

Journal of System Simulation

Abstract: To investigate the biophysical mechanisms underlying the Drosophila retinal computations, a piece of simulation software is constructed. By constructing the connectivity of the optical structure of the Drosophila compound eye with the neural network and retinal neuronal information encoding processes,, the retinal transformation from the light to the electrical signals is simulated. The photo-transduction model is optimized by a stochastic process. The generating mechanism of orientation selectivity (OS) is explored in the Drosophila retina's output neurons through a simulation system. Experiments show that with comparable simulation accuracy, the simulation speed increases by 40 times. The software can now be …

Research On Modeling And Simulation Of Application Efficiency Of Tactical Medical Equipment, Guowei Lu, Xueqiang Tao, Deguang Duan, Hao Li, Zerui Zhang, En Chen

Journal of System Simulation

Abstract: In view of the lack of effective modeling and simulation means for the current research on the application efficiency of tactical medical treatment equipment in our army, a modeling and simulation research framework for the application effectiveness of equipment through the wounded model, equipment model and evaluation model is constructed. Based on the multi-agent method in Anylogic8.7.0 modeling and simulation platform, the casualty generation and its circulation process among medical treatment equipment are simulated. In the context of a tactical medical exercis, the overall support capability of medical treatment equipment is evaluated scientifically and quantitatively, and the key equipment …

Simulation-Based Adaptive Dynamic Scheduling For Bi-Objective Parallel Multi-Processor Open Shop, Yarong Chen, Shuchen Guan, Chengjun Huang, Lixia Zhu, Fuhder Chou

Journal of System Simulation

Abstract: Aiming at the parallel multi-processor open shop scheduling problem with uncertain job's release time,processing time and urgent jobs, an adaptive dynamic method integrating FlexSim simulation model and NSGA-Ⅱ algorithm is designed to optimize the bi-objectives of TWC(total weighted completion time) and TWT(total weighted tardiness). By using the FlexSim simulation model, this method determines the adaptive scheduling cycle according to the dynamic workload of the open shop, and conducts right-shift rescheduling to the urgent jobs. NSGA-Ⅱ algorithm is used to generate the bi-objective optimization scheduling scheme. Experimental results of a grain sorting shop show that compared with the rule-based real-time …

Scheduling Optimization Of Aluminum Extrusion Production Line Based On Timed Petri Net And Bso Algorithm, Yali Wu, Shuting He, Yanxi Yang, Lianqiang Feng, Fuqiang Wang, Yulu Chen

Journal of System Simulation

Abstract: For the problems of long production period and low efficiency caused by the complicated processes and large scheduling capacity of aluminum extrusion production line in industrial production, a timed Petri net (TdPN) scheduling model of aluminum extrusion production line is proposed and analyzed for reasonableness. The brain storm optimization (BSO) algorithm is introduced into the model, and an optimized scheduling algorithm for aluminum extrusion scheduling problems is proposed based on the individual encoding and decoding methods. The simulated annealing local search mechanism is used to improve the performance of BSO algorithm in the later stage, which can achieve the …

Modulation Recognition Method Of Mixed Signal Based On Intelligent Analysis Of Cyclic Spectrum Section, Yu Du, Xinquan Yang, Jianhua Zhang, Suchun Yuan, Huachao Xiao, Jingjing Yuan

Journal of System Simulation

Abstract: Aiming at the problems of low intelligence and poor adaptability for the existing mixed signal recognition methods, an intelligent recognition method based on cyclic spectral cross section and deep learning is proposed. For common mixed communication signals, the characteristics of zero frequency cross section of cyclic spectrum are theoretically deduced and analyzed. Two new pre-processing methods, nonlinear segmental mapping and directional pseudo-clustering are proposed, which can effectively improve the adaptability and consistency of cross section features. The pre-processed feature graph is combined with the residual network (ResNet), and the deep learning network is used to mine and analyze the …

Research On Intelligent Prediction Method Of Wargaming Air Mission, Dayong Zhang, Jingyu Yang, Xi Wu

Journal of System Simulation

Abstract: The efficient, accurate and automatic judgment of the combat mission or intention of the enemy's air targets in the battlefield is the basis of situation awareness and the key to the allocation of auxiliary combat resources. Combined with the calculation characteristics of feed forward deep neural network and long-term and short-term memory network model, two targeted basic index learners are designed, and then the weighted combination is carried out according to the cross entropy of the basic index, which can be used to further train the evaluation index of the learner. It can not only effectively prevent the model …

Artificial Intelligence For Automated Detection Of Large Mammals Creates Path To Upscale Drone Surveys, Javier Lenzi, Andrew Barnas, Abdelrahman A. Elsaid, Travis Desell, Robert F. Rockwell, Susan N. Ellis-Felege

Biology Faculty Publications

Imagery from drones is becoming common in wildlife research and management, but processing data efficiently remains a challenge. We developed a methodology for training a convolutional neural network model on large-scale mosaic imagery to detect and count caribou (Rangifer tarandus), compare model performance with an experienced observer and a group of naïve observers, and discuss the use of aerial imagery and automated methods for large mammal surveys. Combining images taken at 75 m and 120 m above ground level, a faster region-based convolutional neural network (Faster-RCNN) model was trained in using annotated imagery with the labels: “adult …

Dynamic Risk Assessment Of Vocs Cross Regional Flow Based On Petri Nets, Guangqiu Huang, He Wang

Journal of System Simulation

Abstract: In order to evaluate the interaction between regions due to the cross regional flow of VOCs(volatile organic compounds) under polluted weather, a dynamic risk assessment method of cross regional flow of VOCs is proposed by using Petri net modeling method. The migration paths of VOCs between multiple potential pollution sources and contaminated areas are determined by HYSPLIT model, and the relationship between each migration path is described by Petri net; the dynamic risk assessment method is defined, and the calculation of dynamic risk is integrated into the operation of functional Petri net; through case analysis, the dynamic risk assessment …

Research On System Of Virtual-Reality Fusion And Inquiry-Based Learning, Yongning Zhu, Zeru Lou, Tianxiang Wu, Jianmin Wang

Journal of System Simulation

Abstract: With the increasing interest in personalized and self-motivated education, emphasizing active learning and practical experiences, inquiry-based learning (IBL) is attracting interest in education. Considering the requirement for inquiry-based education, a framework of full process inquiry-based learning environment in the real-virtual worlds is designed. As an example, a mixed-reality chemical experiment system is developed. The metadata including user behavior data, interactive suite status and interactive interface status is collected through physical sensing. By mapping real-world status to the virtual world avatar, virtual experiments are simulated with computational dynamic solvers and real-time rendering. The generated images are sent back to the …

Knn Fault Detection Based On Reconstruction Error And Multi-Block Modeling Strategy, Jing Zheng, Weili Xiong, Xiaodong Wu

Journal of System Simulation

Abstract: For the fault monitoring algorithm based on k-nearest neighbor (kNN), the abnormal information that caused the fault is easy to be overwhelmed by the normal operating condition information, which leads to the problem of untimely fault detection and low alarm rate. A kNN fault monitoring method based on reconstruction error is proposed using auto-encoder and multi-block modeling strategy. The method uses the normal working condition data set to train the auto-encoder model, and extracts the reconstruction error based on the model to solve the problem that abnormal information is easy to be overwhelmed. Further considering the fault characteristics such …

Uniform Experimental Design With Constrained Region Based On Fruit Fly Algorithm, Jiawei Zhou, Xin Du, Youcong Ni, Hu Zhang, Hao Zhang, Haoran Ni, Feng Wang

Journal of System Simulation

Abstract: To solve the problems that existing two-phase differential evolutionary algorithms still have poor diversity of population distribution and weak local search ability in solving uniform designs in constrained experimental region, a new two-phase fruit fly optimization algorithm (ToPFOA) based on uniform experimental design is proposed. In the first stage, fruit fly search strategy combined with differential operator, K-means clustering and external document updating the centers of clusters is used todynamically improve distribution diversity of population in constrained region. In the second stage, a new fruit fly operator is designed to improve local search ability in constrained region. …

Research On Multiple Filter Signal Compensation For Washout Algorithm Optimization Of Flight Simulator, Weichao Liu, Hui Wang

Journal of System Simulation

Abstract: Aiming at the defects of signal loss and poor adaptability of the classical washout algorithm when applied to flight simulator, an optimization scheme of washing algorithm based on multiple filtering signal compensation is proposed. Analyzing the lost signal in classical washout algorithm, intercepting the lost signals to the depth filter with depth filtering strategy, basing on human perception errors and platform movement margin, after multiple filtering signal to certain proportion respectively compensation to the three channel of washout algorithm to achieve the maximum reduction of signal loss, thus reducing human perception error. The classical washing algorithm and the improved …

Short-Time Human Activity Recognition Based On Wavelet Features Matching, Benyue Su, Li Zhang, Qingxuan He, Min Sheng

Journal of System Simulation

Abstract: The selection of features is the key problem in the study of human activity recognition. In order to obtain sufficient and stable behavioral features, long-time behavioral data that exceed one behavior cycle are often processed, while short-time behavioral data with less than one behavioral cycle are usually unstable, making it difficult to achieve accurate and stable identification. This paper proposes a short-time human activity recognition method based on the combination of wavelet transform and template matching. Coefficient features are extracted using wavelet transform method. The features of the short-time test samples are matched with the features in the template …

A Multi-Resolution Simulation Modeling Method, Zhaopeng Liu, Xinhai Xu, Bowen Yuan, Jinlu Zhang

Journal of System Simulation

Abstract: Aiming at the resolution gap between the operation task issued by the high-level commanders and the simulation system model instructions in the human-in-the-loop simulation deduction, a multi-resolution modeling method based on behavior tree is proposed. By improving the behavior tree syntax, the low-resolution combat missions are disaggregated into high-resolution simulation system instructions. By designing a decision model embedded in the behavior tree, the problem of resource uncertainty and execution effect uncertainty faced in the execution of model instructions is solved. A combat scenario for seizing air supremacy is designed to verify the effectiveness of the method.

Data Integration Based Human Activity Recognition Using Deep Learning Models, Basamma Umesh Patil, D V Ashoka, Ajay Prakash B. V

Karbala International Journal of Modern Science

Regular monitoring of physical activities such as walking, jogging, sitting, and standing will help reduce the risk of many diseases like cardiovascular complications, obesity, and diabetes. Recently, much research showed that the effective development of Human Activity Recognition (HAR) will help in monitoring the physical activities of people and aid in human healthcare. In this concern, deep learning models with a novel automated hyperparameter generator are proposed and implemented to predict human activities such as walking, jogging, walking upstairs, walking downstairs, sitting, and standing more precisely and robustly. Conventional HAR systems are unable to manage real-time changes in the surrounding …

The Security And Cyber Defence Realities And Difficulties In Algeria, Kada Aicha

Journal of Police and Legal Sciences

This research paper aims to shed light on the digital challenge faced by Algeria as it enters the world of the knowledge society, which qualifies it to achieve cybersecurity and cyber defense against various forms and types of security threats, including cyber threats. The researcher used an analytical approach to understand the phenomenon under study and trace its causes, in addition to a case study method to study all aspects of the studied phenomenon and identify the characteristics of the case study - Algeria was chosen as the analysis unit. The study concluded several important results, including:

The deficiency of …

Social Networks And Their Impact On Social Values In The United Arab Emirates, Muhammad Al-Naqbi

Journal of Police and Legal Sciences

The aim of the study was to measure the impact of social media networks on societal values in the United Arab Emirates (UAE). To achieve this objective, a questionnaire was used as a data collection tool, and a social survey method was employed within the study's community. A simple random sample of 50 individuals was selected from the employees of the Social Support Center and the Department of Social Care in the Emirate of Sharjah. The study found several results, including that social media networks contribute to learning unethical behaviors and the spread of extremist ideas that affect societal values. …

An Investigation Of Internet Service Provider Selection Criteria: A Systematic Literature Review, Mohammed Naji, Sivadass Thiruchelvam, Mohammed Khudari

Iraqi Journal for Computer Science and Mathematics

In today’s highly competitive business environment, organizations need to collaborate with strategic partners to provide high quality services at lower costtomaintain theireffectiveness and efficiency. Hence,the concept of Supply Chain Management (SCM)emergedto effectively coordinate and manage financial, physical,and information activities within organizations andamong all participating external parties. Qualitative and quantitative factors must be consideredin SCM toensuresustainable development. The research investigatesthe metricsand criteria influencing the process of selecting an Internet service provider (ISP) from 2001 to2022to assessthe extent to which these factors have met the requirements of current decision-makers. It is appropriate to conduct a literature review in light of the changes …

Enhancing Student'sperformance Classification Using Ensemble Modeling, Ahmed Adil Nafea, Muthanna Mishlish, Ali Muwafaq Haban Shaban, Mohammed M. Al-Ani, Khattab M Ali Alheeti, Hussam J. Mohammed

Iraqi Journal for Computer Science and Mathematics

A precise prediction of student performance is an important aspect withineducational institutions to improve results and provide personalized support ofstudents.However, the predication accuracy of student performance considers anopenissue within education field.Therefore, thispaper proposes a developedapproachto identifyperformance of students using a group modeling. This approach combinesthe strengths of multiple algorithms including random forest (RF), decision tree (DT), AdaBoosts, and support vector machine (SVM). Afterward, thelastensemble estimatesas one of the bets logistic regressionmethodswas utilizedto create a robust and reliable predictive modelbecause it considers The experiments were evaluated usingtheOpen University Learning Analytics Dataset (OULAD)benchmark dataset.The OULADdataset considersa comprehensive dataset containingvarious characteristics related to …

A Comprehensive Review Of Software Development Life Cycle Methodologies: Pros, Cons, And Future Directions, Qahtan M. Yas, Abdulbasit Alazzawi, Bahbibi Rahmatullah

Iraqi Journal for Computer Science and Mathematics

The software development process needs specific and studied steps within a reliable plan to achieve the requirements for the success of any project. Software development life cycle (SDLC) methodologies have provided several models that meet the needs of the various proposed projects. These methodologies present various scenarios that can be applied in the process of developing systems to make them more efficient and predictive. The paper aims to illuminate the paramount Software Development Life Cycle (SDLC) methodologies by conducting a comprehensive review of the pros andcons of the various models widely used for software design. Furthermore, the paper discusses fundamental …

State Of The Art In Drivers’ Attention Monitoring – A Systematic Literature Review, Sama Hussein Al-Gburi, Kanar Alaa Al-Sammak, Ion Marghescu, Claudia Cristina Oprea

Karbala International Journal of Modern Science

Recently, driver inattention has become the leading cause of automobile accidents. As a result, the driver's perception and decision-making abilities are diminished, and the driver can lose control of the car. To prevent accidents caused by driver inattention, it’s vital to continuously monitor the driver and his driving behaviour and inform him if he becomes distracted or sleepy. This topic has been the subject of study for decades. Whenever feasible to recognise unsafe driving in advance, accidents could be avoided. This document presents an overview of the existing driver alertness system and the various techniques for detecting driver attentiveness.

An Intelligent Prairie Dog Optimization (Ipdo) And Deep Auto-Neural Network (Dann) Based Ids For Wsn Security, D Hemanand, P Mohankumar, N Manoj Kumar, S Vaitheki, P Saranya

Iraqi Journal for Computer Science and Mathematics

Wireless sensor networks (WSNs) are targets of intrusion, which seeks to make these networks lesscapable of performing their duties or even completely eradicate them. The Intrusion Detection System (IDS) is highly important for WSN, sinceit aids in the identification and detection of harmful attacks that impair the network's regular functionality. In order to strengthen the security of WSN, several machine learning and deep learning approaches are employed in thetraditional works. However, its main drawbacks are computational burden, system complexity, poornetwork performance outcomes, and high falsealarms. Therefore, the goal of this study is to develop an intelligent IDS framework for significantly …

Perspectives On Design Considerations Inspired By Security And Quantum Technology In Cyberphysical Systems For Process Engineering, Helen Durand, Jihan Abou Halloun, Kip Nieman, Keshav Kasturi Rangan

Chemical Engineering and Materials Science Faculty Research Publications

Advances in computer science have been a driving force for change in process systems engineering for decades. Faster computers, expanded computing resources, simulation software, and improved optimization algorithms have all changed chemical engineers’ abilities to predict, control, and optimize process systems. Two newer areas relevant to computer science that are impacting process systems engineering are cybersecurity and quantum computing. This work reviews some of our group’s recent work in control-theoretic approaches to control system cybersecurity and touches upon the use of quantum computers, with perspectives on the relationships between process design and control when cybersecurity and quantum technologies are of …