Numerical Analysis and Scientific Computing Commons^™

Review Of System Of Systems Combat Effectiveness Evaluation And Optimization Methods, Ziwei Zhang, Qisheng Guo, Zhiming Dong, Ang Gao, Yifei Wang

Journal of System Simulation

Abstract: The characteristics of system-of-systems combat effectiveness evaluation and optimization are analyzed. In light of the "holism", this paper proposes an idea of dividing system of systems combat effectiveness evaluation and optimization into three stages of comprehensive evaluation, analysis, and optimization. As for the practical problems that need to be solved in the three stages, typical methods suitable for each stage are summarized.The advantages and disadvantages of different methods are then compared. In view of the practical difficulties in implementing system of systems combat effectiveness evaluation and optimization guided by the "holism", this paper puts forward the next research directions …

Simulation And Optimization Of A New Multi-Channel Contact Center System, Junxiang Li, Lichao Li, Kun Ma

Journal of System Simulation

Abstract: In the actual operation of a contact center, it often encounters a large number of calls caused by an emergency. A traditional call center with a simple first-come-first-served queuing rule can hardly handle the rapid increase of calls properly. In this regard, without changing the number of seats, the call-back service channel for evacuating tasks and the special service channel for ensuring the service level are added. Considering customer abandonment, a new multi-channel queuing model for a contact center is built. This model is simulated by FlexSim software, and the results are comparatively analyzed. It is found that …

Modeling And Optimization For Manufacturing Cell Scheduling Based On Improved Wolf Pack Algorithm And Simulation, Zi'an Zhao, Hong Zhou, Yingjian Lei

Journal of System Simulation

Abstract: Aiming at the domestic aircraft stall spin simulation training need, a stall spin simulation training system is developed. The training system consists of the multi-channel dome visual system, the semi-physical simulation cockpit and the maneuvering force control loading system, etc. Distributed simulation technology is used to develop a realistic man-in-the-loop simulation training environment. For the stall spin simulation, the multi-source aerodynamic data is processed comprehensively, and an unsteady aerodynamic model at high angle of attack (AOA) is constructed, and the heavy-load digital electric control loading technology is used to realize the simulation of stall spin alternating force and jitter …

Vehicle Routing Problem With Refined Oil Secondary Distribution Considering Workload Balance, Zhenping Li, Guang Yang, Qianqian Han

Journal of System Simulation

Abstract: The small-signal model of a DC/DC converter is usually built by the analytic method, and its accuracy is verified by the frequency domain method. A new idea is developed to model the small signal of the converter, i.e., directly using the frequency domain method.The design process is as follows: The principle and modeling mechanism of the frequency domain method are analyzed, and the realization flow of Matlab modeling is introduced. A typical phase-shifted full-bridge converter is taken as the design object, and a simulation model is built by Simulink. The transfer function is obtained on the basis of …

Lod Modeling Method For Three-Dimensional Objects With Energy Operator, Yongzhi Wang, Zhenchao Li, Pengyu Liu, Hui Wang

Journal of System Simulation

Abstract: Current level of detail (LOD) modeling methods do not combine simplification and subdivision, which results in models not being rich in detail level. Therefore, the energy operator was used to combine the simplification algorithm of a three-dimensional (3D) object model with the subdivision algorithm, and a LOD modeling method based on an energy operator was proposed for 3D objects. The method involves three major steps: calculation of energy operators for 3D models, model simplification and model subdivision based on an energy operator. Experiments show that this method can generate models with rich levels of detail and has good visualization …

Monocular Semantic Slam Method Based On Object Relation Description, Shiqi Lin, Jikai Wang, Haoyuan Pei, Hao Zhao, Zonghai Chen

Journal of System Simulation

Abstract: Semantic information perception of the external environment and accurate positioning are the keys to autonomous navigation and operation of mobile robots. This paper proposes a method of semantic simultaneous localization and mapping (SLAM) based on a monocular camera. The system completes three-dimensional (3D) object detection while estimating the trajectory. We model the 3D objects with cuboids. Then, the semantic meanings, color distribution, size and neighborhood topology of the objects are extracted as descriptors for the accurate matching of objects between different frames. The camera pose, map points and object landmarks are optimized jointly in the backend of the system. …

Research On Nonlinear Evaluation Method Of Situational Hot Spots, Tengjiao Mao, Dongge Zhang, Xuefeng Liang, Yanjie Niu, Minggang Yu, Ming He

Journal of System Simulation

Abstract: The excessive amount of data and information in the situation map is likely to produce a huge cognitive load that exceeds the physiological limit. This can lead to delays in the perception, judgment, and decision-making of the commander, or even failure of decision-making activities in severe cases. For this reason, situation information needs to be processed to assess and highlight situational hotspots so that cognitive overload can be tackled. Based on the aggregation factors of collaborative targets, this paper takes the effective impact possibility of situational targets and the collaboration as the indicators, derives the attention function, and designs …

Research On Design Method For Transfer Function Of Dc/Dc Converter System Based On Frequency Domain Method, Song Gao, Xue Yin, Jiantao Xu, Yuhao Miao

Journal of System Simulation

Abstract: A robust optimal synchronization control method based on coupling dynamics model of the H-type motion platform is proposed for the problem that the H-type motion platform driven directly by permanent magnet linear synchronous motor has uncertainties such as biaxial coupling, parameter perturbation and external disturbances, which affect the synchronization control accuracy and robustness of the system. A biaxial coupling dynamics model is established based on Euler-Lagrange equation. The cross coupling synchronization controller is designed to effectively combine the single-axis tracking error with the biaxial synchronization error and its rate of change. TheH∞robust optimal synchronous controller …

Research On Collaborative Computing Offloading Model For Base Station Groups Based On Fireworks Algorithm, Bin Xu, Wenqing Yan, Zhuofan Han, Guangshen He, Tao Deng, Yunkai Zhao, Jin Qi

Journal of System Simulation

Abstract: Internet of Vehicles (IoV), AR, AI, and other computing-intensive, time-delay-sensitive applications are developing rapidly. However, due to the relatively insufficient computing capacity of mobile devices, such application tasks face serious latency, which seriously affects user experience and even fails to meet the needs of users. To solve this problem, by comprehensively considering delays and costs, we propose a cooperative computing offloading model based on a multi-user and multi-mobile edge computing (multi-MEC) server for base station groups. In addition, an improved fireworks algorithm based on convex optimization (CVX-FWA) is presented to solve the model and perform reasonable offloading and resource …

Energy Consumption Prediction For Air-Conditioning System Based On Dynamic Temperature Control, Yan Bai, Lulu Wu, Yin'e He, Yuying Wang

Journal of System Simulation

Abstract: To solve the problem of energy consumption prediction for air-conditioning systems implementing dynamic temperature control, we designed a dynamic temperature control strategy and obtained a dataset on the hourly energy consumption of the air-conditioning system through EnergyPlus simulation. An improved particle swarm optimization-back propagation neural network (IPSO-BPNN) prediction model was built on the basis of energy consumption analysis by an integrated method. Clustering, classification, and correlation analysis methods were integrated to mine the energy consumption pattern of the air-conditioning system and determine the input variables for the prediction model. A nonlinear change strategy was designed to adjust the inertia …

Optimal Path Planning For Multi-Stage Automatic Parking And Simulation Analysis, Qiming Wang, Gaoqiang Zong, Jinming Xu

Journal of System Simulation

Abstract: To resolve the path planning for narrow parallel parking spaces and the discontinuous curvature of the parking trajectory, this paper proposes a method of optimal multi-stage parking path planning considering collision avoidance constraints. A trajectory equation for the center of the vehicle rear axle is derived for the case when the steering wheel speed is constant. A function of collision avoidance constraints is developed to ensure the safe parking of the vehicle. With the center of the rear axle of the parking path as the control point, the optimal path is solved according to parking indicators such as the …

Research On Decision-Making Of Closed-Loop Supply Chain For Dual-Channel Recovery Based On Game Theory, Ying Xu, Qinming Liu, Linsen Zhou

Journal of System Simulation

Abstract: To tackle the difficulties and resource depletion in current packaging recycling, this paper constructs a centralized decision-making game model and three Stackelberg game models. Specifically, these Stackelberg game models are developed depending on the differences in the game power of participants in the closed-loop supply chain for dual-channel recovery, respectively corresponding to the cases where the manufacturer, the distributor or the third-party recycler is dominant. The optimal solutions of the four models are compared and analyzed. The benefits of decentralized decision-making do not reach the Pareto optimality as compared with centralized decision-making. An improved revenue sharing contract is …

Component Design And Simulation Of Netted Radar Fusion Processing, Jing Wu, Zhiming Xu, Xiaofeng Ai, Feng Zhao, Shunping Xiao

Journal of System Simulation

Abstract: Data fusion processing technology is the core of netted radars. Taking the air-defense radar network as the reference, this paper builds a component-based and reconfigurable data fusion algorithm library. With the component design method, the process of data fusion is divided into different components, such as data validity check, error match, time-space match, plot association, plot fusion, track initiation, track filtering, track association, track fusion, and track management. Each component involves different algorithms with a unified external interface, and algorithms can be chosen by parameter setting to meet different fusion requirements. Then, the complete processing template forplot fusion and …

Seizure Prediction In Epilepsy Patients, Gary Dean Cravens

NSU REACH and IPE Day

Purpose/Objective: Characterize rigorously the preictal period in epilepsy patients to improve the development of seizure prediction techniques. Background/Rationale: 30% of epilepsy patients are not well-controlled on medications and would benefit immensely from reliable seizure prediction. Methods/Methodology: Computational model consisting of in-silico Hodgkin-Huxley neurons arranged in a small-world topology using the Watts-Strogatz algorithm is used to generate synthetic electrocorticographic (ECoG) signals. ECoG data from 18 epilepsy patients is used to validate the model. Unsupervised machine learning is used with both patient and synthetic data to identify potential electrophysiologic biomarkers of the preictal period. Results/Findings: The model has shown states corresponding to …

Session 5: Equipment Finance Credit Risk Modeling - A Case Study In Creative Model Development & Nimble Data Engineering, Edward Krueger, Landon Thompson, Josh Moore

SDSU Data Science Symposium

This presentation will focus first on providing an overview of Channel and the Risk Analytics team that performed this case study. Given that context, we’ll then dive into our approach for building the modeling development data set, techniques and tools used to develop and implement the model into a production environment, and some of the challenges faced upon launch. Then, the presentation will pivot to the data engineering pipeline. During this portion, we will explore the application process and what happens to the data we collect. This will include how we extract & store the data along with how it …

The Effect Of Using The Gamification Strategy On Academic Achievement And Motivation Towards Learning Problem-Solving Skills In Computer And Information Technology Course Among Tenth Grade Female Students, Mazyunah Almutairi, Prof. Ahmad Almassaad

International Journal for Research in Education

Abstract

This study aimed to identify the effect of using the gamification strategy on academic achievement and motivation towards learning problem-solving skills in computer and information technology course. A quasi-experimental method was adopted. The study population included tenth-grade female students in Al-Badi’ah schools in Riyadh. The sample consisted of 54 students divided into two equal groups: control group and experimental group. The study tools comprised an achievement test and the motivation scale. The results showed that there were statistically significant differences between the two groups in the academic achievement test in favor of the experimental group, with a large effect …

Crowdtc: Crowd-Powered Learning For Text Classification, Keyu Yang, Yunjun Gao, Lei Liang, Song Bian, Lu Chen, Baihua Zheng

Research Collection School Of Computing and Information Systems

Text classification is a fundamental task in content analysis. Nowadays, deep learning has demonstrated promising performance in text classification compared with shallow models. However, almost all the existing models do not take advantage of the wisdom of human beings to help text classification. Human beings are more intelligent and capable than machine learning models in terms of understanding and capturing the implicit semantic information from text. In this article, we try to take guidance from human beings to classify text. We propose Crowd-powered learning for Text Classification (CrowdTC for short). We design and post the questions on a crowdsourcing platform …

Collaborative Curating For Discovery And Expansion Of Visual Clusters, Duy Dung Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

In many visually-oriented applications, users can select and group images that they find interesting into coherent clusters. For instance, we encounter these in the form of hashtags on Instagram, galleries on Flickr, or boards on Pinterest. The selection and coherence of such user-curated visual clusters arise from a user’s preference for a certain type of content as well as her own perception of which images are similar and thus belong to a cluster. We seek to model such curation behaviors towards supporting users in their future activities such as expanding existing clusters or discovering new clusters altogether. This paper proposes …

What Really Matters?: Characterising And Predicting User Engagement Of News Postings Using Multiple Platforms, Sentiments And Topics, Kholoud K. Aldous, Jisun An, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

This research characterises user engagement of approximately 3,000,000 news postings of 53 news outlets and 50,000,000 associated user comments during 8 months on 5 social media platforms (i.e. Facebook, Instagram, Twitter, YouTube, and Reddit). We investigate the effect of sentiments and topics on user engagement across four levels of user engagement expressions (i.e. views, likes, comments, cross-platform posting). We find that sentiments and topics differ by both news outlets and social media platforms, and both sentiments and topics by the four levels of user engagement expression. Finally, we predict a volume of four user engagement levels for given news content, …

Understanding In-App Advertising Issues Based On Large Scale App Review Analysis, Cuiyun Gao, Jichuan Zeng, David Lo, Xin Xia, Irwin King, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Context: In-app advertising closely relates to app revenue. Reckless ad integration could adversely impact app quality and user experience, leading to loss of income. It is very challenging to balance the ad revenue and user experience for app developers. Objective: Towards tackling the challenge, we conduct a study on analyzing user concerns about in-app advertisement. Method: Specifically, we present a large-scale analysis on ad-related user feedback. The large user feedback data from App Store and Google Play allow us to summarize ad-related app issues comprehensively and thus provide practical ad integration strategies for developers. We first define common ad issues …