Computer Engineering Commons^™

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 …

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 …

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 …

Special Vehicle Driving Training Simulation System Based On Integration Of Virtuality And Reality, Xiangyang Li, Wang Xiao, Zhili Zhang, Yihao Li, Long Yong

Journal of System Simulation

Abstract: Aiming at the actual demands of special vehicle driving training, special vehicle driving training simulation system is designed and developed based on the integration of virtuality and reality mode. Through building all kinds of mathematical models, functional modules, workflows and control software, and applying the cab that same as actual equipment with manipulating device, central control instrument and driving seat, immersive driving training environment with integration of virtuality and reality is established based on 6-DoF motion platform and its control system as well as multi-channel visual display device. It can provide the integrated support platform with “educating, training and …

Research On Semi-Physical Simulation Model Of Special Vehicle Cockpit With Force Feedback, Liang Feng, Zhili Zhang, Xiangyang Li, Yihao Li, Wang Bei, Long Yong

Journal of System Simulation

Abstract: To improve the interaction and immersion of cockpit simulation training system, a semi-physical model of special vehicle cockpit with force feedback is studied. The important force feedback parts of the semi-physical simulation model are designed to provide more real operation experience for operators. The simulation training method of special vehicle cockpit based on dynamic model is studied to match the action input of operators with scene changes and provide a high fidelity visual experience. The driving simulation operation process of special vehicle is analyzed and verified. Simulation experiments show that the model has the characteristics of high precision, fast …

Simulation Research On U-Automated Container Terminal, Ding Yi, Tiantian Li

Journal of System Simulation

Abstract: To analyze the new U-layout effect on the handling operation efficiency in automated container terminal, the U-automated container terminal simulation model is established by FlexTerm software to visualize the handling operation process. The traditional automated terminal simulation model is established to compare the working efficiency under different working modes. The working ability of terminal handling equipment such as AGV（Automated Guided Vehicle）, yard cranes and rail-mounted gantry cranes are compared by simulation tests. Simulation results show that due to the creation of yard layout and handling technology, the superiority of U-layout is proved when the working efficiency of each handling …

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 …

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 …

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 …

Track Deception Modeling Method Based On Multi-Jammer Cooperation, Wang Rui, Xiangyang Li, Zhili Zhang, Hongguang Ma

Journal of System Simulation

Abstract: The false track generated by the jammer formation is an effective interference measure against networked radars. This paper starts from the basic principle of false track generation and presents the model of the measurement error of the radar for the false track and the control error of the jammer formation. It also presents an analysis of the effects of these errors on the false track. The effectiveness of the false track is further analyzed through the confrontation scenario between the rectangular front formation of a certain type of equipment and networked radars. The simulation results show that the false …

Low Power Visual Odometry Technology Based On Monocular Depth Estimation, Ma Rong, Qiurui Chen, Zhang Han, Mei Zheng, Wang Rui, Wei Wei

Journal of System Simulation

Abstract: With the development of artificial intelligence, precision machinery and computing technology, micro-unmanned system will play an important role in the future battlefield. To solve the lack of monocular visual odometry scale, micro robot power consumption and load limits, the monocular depth estimation technology is introduced and a low view dataset is collected. A convolutional neural network to predict depth information from a single image is built, and the structure of neural network model is optimized. The depth estimation with monocular visual odometry are combined and deployed on JetsonNano. Experiments show that the combined monocular visual odometry can recover scale …

Research On Supply Chain Recovery Strategy Under Disruption Risks, Yang Yi, Peng Chen, Yujiu Yang, Yulong Wang

Journal of System Simulation

Abstract: Aiming at supply chain disruptions, two effective supply chain recovery strategies are proposed, namely, a supplier’s preset emergency inventory strategy and a manufacturer’s product change strategy, meanwhile, emergency inventory storage cost and products return rate after change are also taken into consideration. In order to maximize the manufacturer’s profit and customer satisfaction, a single-objective model and a bi-objective model are established, respectively. The optimization problems in the two models are transformed into mixed integer programming problems, moreover, corresponding solution algorithms are presented based on ILOG CPLEX. The simulation results show that the disruption recovery strategies proposed can not only …

Radar Emitter Signal Identification Via Distance Features, Yingkun Huang, Weidong Jin, Yan Kang, Jiehao Zhu

Journal of System Simulation

Abstract: Aiming at the problem that traditional recognition methods of radar emitter signal have low accuracy in low signal to noise ratio (SNR) environment, and are usually suitable for only several specific radar signals, an identification approach of radar signal based on distance features is proposed. Several cluster centers are extracted via the k-means algorithm, and the Dynamic Time Warping (DTW) values between the radar signal and the cluster center are calculated respectively, which are combined as the input features of k-Nearest Neighbor (k-NN) algorithm. The simulation results show that when the SNR is 3 dB, the identification rate …

Study On Prediction Of Crystal Properties Based On Deep Learning, Buwei Wang, Wang Min, Fan Qian, Ya'nan Wang, Hanwen Zhang, Yunliang Yue

Journal of System Simulation

Abstract: Predicting crystal properties using traditional machine learning methods requires complex feature engineering. In order to bypass time-consuming feature engineering, element network (ElemNet), representation learning from stoichiometry (Roost), compositionally-restricted attention-based network (CrabNet) and crystal graph convolution neural network (CGCNN) based on deep learning technology are used to simulate the formation energy, total energy per atom, band gap, and Fermi energy of crystal. The residual learning is introduced into CGCNN, and a crystal graph convolution residual neural network (CGCRN) is proposed. In the CGCRN, the number of hidden layers and the number of nodes in the hidden layers are increased, …

Improved Ant Colony Optimization Algorithm For Jamming Resource Allocation, Qingyun Wang, Dezhong Jiao, Shi Shuo, Genyan Peng, Junhua Sun, Yuxin Duan

Journal of System Simulation

Abstract: Ant Colony Optimization (ACO) is a new intelligence optimization algorithm. When applied to jamming resource allocation, the velocity of convergence in optimization process is slow and the probability of obtaining the global optimal solution is low. In order to raise the efficiency of jamming resource allocation and the probability of getting global optimal solution, the attenuation factor is improved to a variable that changes according to the exponential function in optimization process. The attenuation factor is taken as a relatively small value in the initial search phase, and increases monotonically and exponentially as the number of iterations increases. Simulation …

Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen

Journal of System Simulation

Abstract: Reinforcement Learning (RL) achieves lower time response and better model generalization in Job Shop Scheduling Problem (JSSP). To explain the current overall research status of JSSP based on RL, summarize the current scheduling framework based on RL, and lay the foundation for follow-up research, the backgrounds of JSSP and RL are introduced. Two simulation techniques commonly used in JSSP are analyzed and two commonly used frameworks for RL to solve JSSP are given. In addition, some existing challenges are pointed out, and related research progress is introduced from three aspects: direct scheduling, feature representation-based scheduling, and parameter search-based scheduling.

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 …

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 …

Physiological Signal Analysis For Emotion Estimation Of Children With Autism Spectrum Disorder, Janet Pulgares Soriano, Karla Conn Welch Phd

Posters-at-the-Capitol

The diagnosis of Autism Spectrum Disorder (ASD) in children is based on human observations by a clinician. The medical evaluation assesses deficits in social communication, social interaction, and restricted, repetitive behaviors. Robotic technology can assist in quantitatively measuring the observations to be used as a future tool for autism diagnosis and intervention. The project explores this technology to produce robotic partners that can adapt to the needs of the ASD population. This way, such robots could serve as instructors or learning peers. A friendly, partner robot, specifically designed for children with ASD could be used to investigate the effect of …

On The Involutive Matrices Of The Kth Degree, Hasan Kele ̧S

Iraqi Journal for Computer Science and Mathematics

In this study, the gradation of involutive matrices, whose definitions were given before, is conducted.The solutions of the equationx2=1 in real numbers are1. Meanwhile, in the solution of the equationxk=1in real numbers, there is always the number1 that is independent of the power ofk2Z+. This feature, which isrevealed by this equation in real numbers, is the subject of the research. In particular, the kind of situation in whichthe equation would display in the matrices is determined. Initially, the second-order square matrices are studied byobtaining some of their properties. Then, new cases arising from the known addition, subtraction, multiplication,scalar multiplication, and …

Towards A New Curvature Produced By The Tangent Of A Circle Andan Ellipse: The Nada’S Curve, Laith H. M. Al-Ossmi

Iraqi Journal for Computer Science and Mathematics

A new curve is produced and graphically studied. The name of my daughter, Nada, has been givento this curve; in other words, Nada is used to describe this curve whenever it is used in this paper. “Nada’s curve”is a form of closed curve that is constructed when the circle’s diameter and the ellipse’s minor axis share the samelength, and they are tangent by a point from a drawn line passing through the circumstances of the circle and ellipse.Then, from these two intersection points, the point of intersection of the vertical and horizontal lines is selectedto determine a point of Nada’s …

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 …

Identification Method Of Power Internet Attack Information Based On Machine Learning, Yitong Niu, Korneev Andrei

Iraqi Journal for Computer Science and Mathematics

To solve the problem of large recognition errors in traditional attack information identificationmethods, we propose a machine learning (ML)-based identification method for electric power Internet attackinformation. Based on the Internet attack information, an Internet attack information model is constructed, theidentification principle of the power Internet attack information is analysed based on ML, hash fixing is conducted toensure that the same attack information will be assigned to the same thread and that the deviation generated by noisecan be avoided so that the real-time lossless processing of the power Internet attack information can be ensured. Thevulnerability adjacency matrix is constructed, and the …

Chaotic Dynamics In The 2d System Of Nonsmooth Ordinarydifferential Equations, Zain-Aldeen S. A. Rahman, Basil H. Jasim, Yasir I. A. Al-Yasir

Iraqi Journal for Computer Science and Mathematics

Over the last decade, the chaotic behaviors of dynamical systems have been extensively explored.Recently, discovering or developing a 2D system of ordinary differential equations (ODEs) capable of exhibitingchaotic dynamical behaviors is an attractive research topic. In this study, a chaotic system with a 2D system ofnonsmooth ODEs has been developed. This system is can exhibit chaotic dynamical behaviors. Its main dynamicalbehaviors, including time-series trajectories, phase portraits of attractors, and equilibria and their stability, have beeninvestigated. The developed system has been verified by an excessive variety of fascinating chaotic behaviors, such aschaotic attractor, symmetry, sensitivity to initial conditions (ICs), fractal dimension, …

Icu Liberation: Early Mobility And Exercise, Leann Volkers, Holly Kockler, Kristi Patterson

Nursing Posters

The aim of this project was to streamline and standardize the delivery of the follow up Important Message from Medicare (IMM) for IP admissions across CC and Carris-RWF in compliance with regulatory standards of care.

Key drivers identified:

• Site specific variation
• Underutilization of Epic functionality
• Use of data to understand performance

A Half- Yearly E-Newsletter Of The Department Of Computer Science And Engineering, Manipal Institute Of Technology - Jan 2022, Ashalatha Nayak Dr.

Faculty work

No abstract provided.

Exploring The Concept Of The Digital Educator During Covid-19, Fernando Jimenez, Gracia Sanchez, Jose Palma, Luis Miralles-Pechuán, Juan A. Botia

Articles

T In many machine learning classification problems, datasets are usually of high dimensionality and therefore require efficient and effective methods for identifying the relative importance of their attributes, eliminating the redundant and irrelevant ones. Due to the huge size of the search space of the possible solutions, the attribute subset evaluation feature selection methods are not very suitable, so in these scenarios feature ranking methods are used. Most of the feature ranking methods described in the literature are univariate methods, which do not detect interactions between factors. In this paper, we propose two new multivariate feature ranking methods based on …

Assisting End-Users In Creating Chatbots By Improving Training Data, Aparna Roy, Chris Egersdoerfer

Summer REU Program

No abstract provided.

Choosing Wearable Internet Of Things Devices For Managing Safety In Construction Using Fuzzy Analytic Hierarchy Process As A Decision Support System, Sharique Khalid

Theses, Dissertations and Capstones

Many safety and health risks are faced daily by workers in the field of construction. There is unpredictability and risk embedded in the job and work environment. When compared with other industries, the construction industry has one of the highest numbers of worker injuries, illnesses, fatalities, and near-misses. To eliminate these risky events and make worker performance more predictable, new safety technologies such as the Internet of Things (IoT) and Wearable Sensing Devices (WSD) have been highlighted as effective safety systems. Some of these Wearable Internet of Things (WIoT) and sensory devices are already being used in other industries to …

A Trusted Platform For Unmanned Aerial Vehicle-Based Bridge Inspection Management System, Hwapyeong Song

Theses, Dissertations and Capstones

Bridge inspection has a pivotal role in assuring the safety of critical structures constituting society. However, high cost, worker safety, and low objectivity of quality are classic problems in traditional visual inspection. Recent trends in bridge inspection have led to a proliferation of research utilizing Unmanned Aerial Vehicles (UAVs). This thesis proposes a Trusted Platform for Bridge Inspection Management System (Trusted-BIMS) for safe and efficient bridge inspection by proving the UAV-based inspection process and improving the prototype of the previous study. Designed based on a Zero-Trust (ZT) strategy, Trusted-BIMS consist of (1) a database-driven web framework with security features for …