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17th international conference on Intelligent Tutoring Systems, ITS 2021

17th International Conference on Intelligent Tutoring System...

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17th international conference on Intelligent Tutoring Systems, ITS 2021

ISBN: (纸本)9783030804206

The proceedings contain 58 papers. The special focus in this conference is on Intelligent Tutoring Systems. The topics include: Difficulties and Disparities to Distance Learning During Covid-19 Period for Deaf Students –A Proposed Method to Eradicate Inequalities;Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums;creating and Visualising Cognitive Maps of Knowledge Diagnosis During the Processing of Learning Digital Footprint;integrating Knowledge in Collaborative Concept Mapping: Cases in an Online Class Setting;an Evaluation of a Meaningful Discovery Learning Support System for Supporting E-book User in Pair Learning;towards Semantic Comparison of Concept Maps for Structuring Learning Activities;MOOC Next Week Dropout Prediction: Weekly Assessing Time and Learning Patterns;internet of Things (IoT) Based Support System for Diabetic Learners in Saudi Arabian High Schools;Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification;Urgency Analysis of Learners’ Comments: An Automated Intervention Priority Model for MOOC;early Predictor for Student Success Based on Behavioural and Demographical Indicators;Wide-Scale Automatic Analysis of 20 Years of ITS Research;Predicting Certification in MOOCs Based on Students’ Weekly Activities;recognizing Novice Learner’s modeling Behaviors;expert, Novice, and Intermediate Performance: Exploring the Relationship Between Clinical Reasoning Behaviors and Diagnostic Performance;agent-Based simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students;Investigating Clues for Estimating ICAP States Based on Learners’ Behavioural Data During Collaborative Learning;behaviour Analytics - A Moodle Plug-in to Visualize Students’ Learning Patterns;exploring the Barriers of Educational Innovation.

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Evolutionary Analysis of the Servitization of Manufacturing Enterprises Based on Evolutionary Game Theory

Evolutionary Analysis of the Servitization of Manufacturing ...

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computer Science and Management Technology (ICCSMT), international conference on

作者： Jin Liu Yifang Zhan Jinchao Guo Jian Weng School of Transportation and Economic Management Guangdong Communication Polytechnic Guangzhou China School of Management Guangzhou Xinhua University Guangzhou China

ISBN: (纸本)9781665420648

The service-oriented upgrading of traditional manufacturing industry is a dynamic process in which enterprises in the industry interact and play with each other. This study utilized evolutionary game theory to establish an evolutionary game model for the servitization of enterprises in the traditional manufacturing industry from the perspective of the game behavior of manufacturing enterprises. Through computer simulation, some of the factors affecting the servitization of manufacturing enterprises were analyzed. The results show that government subsidies have a positive effect on the servitization of manufacturing enterprises; the allocation ratio of the total benefits of servitization within the industry must be set in a reasonable interval to promote the servitization of enterprises; the smaller the speculative income, the higher the possibility of enterprises implementing servitization. Finally, suggestions are given to promote the servitization of enterprises.

关键词： Manufacturing industries computer science computer simulation Computational modeling Government Games Manufacturing

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13th international conference on Computational Collective Intelligence, ICCCI 2021

13th International Conference on Computational Collective In...

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13th international conference on Computational Collective Intelligence, ICCCI 2021

ISBN: (纸本)9783030881122

The proceedings contain 58 papers. The special focus in this conference is on Computational Collective Intelligence. The topics include: Morphological Analysis of Histopathological Images Using Deep Learning;developing a Three Dimensional Registration Method for Optical Coherence Tomography Data;which Gameplay Aspects Impact the Immersion in Virtual Reality Games?;is Wikipedia Easy to Understand?: A Study Beyond Conventional Readability Metrics;compatibility Checking of Business Rules Expressed in Natural Language Against Domain Specification;agent-Based modeling and simulation of Citizens Sheltering During a Tsunami: Application to Da Nang City in Vietnam;effect of Dialogue Structure and Memory on Language Emergence in a Multi-task Game;towards Smart Customer Knowledge Management Systems;the Proposition of Balanced and Explainable Surrogate Method for Network Intrusion Detection in Streamed Real Difficult Data;social Recommendation for Social Networks Using Deep Learning Approach: A Systematic Review;behavioral Anomaly Model for Detecting Compromised Accounts on a Social Network;adversarial Attacks on Face Detection Algorithms Using Anti-facial Recognition T-Shirts;security and Scalability in Private Permissionless Blockchain: Problems and Solutions Leading to Creating Consent-as-a-Service (CaaS) Deployment;EMaxPPE: Epoch’s Maximum Prediction Probability Ensemble Method for Deep Learning Classification Models;convolutional Neural Networks with Dynamic Convolution for Time Series Classification;enhancing Speech Signal Features with Linear Envelope Subtraction;entropy Role on Patch-Based Binary Classification for Skin Melanoma;reinforcement Learning for Optimizing Wi-Fi Access Channel Selection;emotiv Insight with Convolutional Neural Network: Visual Attention Test Classification;Machine Learning in the Context of COVID-19 Pandemic Data Analysis;session Based Recommendations Using Char-Level Recurrent Neural Networks.

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Multi-Agent simulation modeling of Corona Virus Disease 2019 transmission based on various age groups

Multi-Agent simulation modeling of Corona Virus Disease 2019...

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international conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)

作者： Li-Hu Pan Ya Su Hui-Min Yan Bin-Hone Xie Fen-vu Yang School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665417914

Multi-Agent System (MAS) is an important branch of artificial intelligence research. This study uses the bottom-up characteristics of multi-agents to construct multi-agent simulation models for Corona Virus Disease 2019 (COVID-19) virus prevention and control based on different age groups. The development of the epidemic and the infection of residents of all ages under different prevention and control measures issued by the government were studied. The simulation results proved that the multi-agent modeling method could effectively capture the emergence of complex systems. Its experimental conclusions provided a basis for predicting the development of the epidemic and provide scientific support for government decision-making.

关键词： COVID-19 Epidemics Adaptation models Hospitals simulation Government Predictive models

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A 3D Smooth Mobility Model Based on Semi-random Circular Movement for FANETs

A 3D Smooth Mobility Model Based on Semi-random Circular Mov...

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international conference on computer and Communications (ICCC)

作者： Jize Mi Zhitao Dai School of Computer Science Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665409513

In recent years, the number of applications based on multiple unmanned aerial vehicles (UAVs) for cooperative mission execution has increased. In a search and rescue mission (SAR) scenario, the network solution based on Flying Ad Hoc Networks (FANETs) can meet the special requirements of this mission. However, due to the high cost of establishing a real experimental environment, network simulation is considered to be the most practical research method in most cases. For FANETs, modeling and simulation based on the mobility of a UAV in a specific scene have an important impact on the performance of routing protocols. Therefore, to develop an excellent FANETs routing protocol for SAR task scenarios, it is necessary to design a three-dimensional (3D) mobility model suitable for this scenario. This paper first analyzes the design requirements of FANETs 3D mobility model under the SAR task scene. According to these requirements, we proposed a 3DSRCM mobility model based on semi-random Circular Movement (SRCM). Based on the helix and pheromone, we design the track with its selection and switching mechanism for the model. Subsequently, we tested the relevant performance of the model according to the design requirements, and the test results proved that the model could truly simulate the movement behavior of UAV in the SAR scene, with excellent coverage and smooth three-dimensional trajectory, as well as relatively good spatial node distribution and network connectivity.

关键词： Solid modeling Three-dimensional displays Costs Tracking Computational modeling Switches Autonomous aerial vehicles

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Double Closed Loop Control of DC-DC Boost Converter

Double Closed Loop Control of DC-DC Boost Converter

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Power Electronics, computer Applications (ICPECA), IEEE international conference on

作者： Lin Yun Gao Qianqian Zhang Xiang College of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9781728190044

ISBN: (纸本)9781728190051

In this paper, An average switch model of a boost converter with double closed loop control is presented by using the method of average state space. A detailed design procedure of both voltage and current feedback loops are given in a boost converter. The proposed circuit shows the characteristics of the fast dynamic response. Besides, the output voltage ripple is reduced significantly. Finally, this method is verified practically and superiority by using MATLAB.

关键词： Computational modeling simulation Switches Pulse width modulation Power electronics Mathematical model Integrated circuit modeling

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DeltaFace: Fully Automatic 3D Facial Cosmetic Surgery simulation

DeltaFace: Fully Automatic 3D Facial Cosmetic Surgery Simula...

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international computer Science and Engineering conference (ICSEC)

作者： Adawat Chanchua Nuttapong Chentanez Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781665411981

Before cosmetic surgery procedures, the patients are commonly involved in the consultation process using interviews and reference images. The reference images typically consist of pre-post surgery images of other patients, leading to misunderstandings between patients and the surgeon. We present fully automatic pipeline to simulate the whole face of post-surgery results. We first establish a 3D face registration and alignment based on the face surgery procedures of the current day then generate the delta image. We proposed the delta image to solve the lack of dataset dilemma of the pre-post surgery face images. We also propose a convolutional autoencoder model to select the most similar face. Furthermore, we simulate the post-surgery results using surgery procedures retargeting. In the last section, we validate the results using a subjective survey.

关键词： computer science Solid modeling Three-dimensional displays Computational modeling Pipelines Surgery Rendering (computer graphics)

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Sasirangan Cloth Recognition and Shopping Experience simulation Based on Virtual Reality Game with Non-Player Character Integration

Sasirangan Cloth Recognition and Shopping Experience Simulat...

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HCI and UX conference in Indonesia (CHIuXiD), international

作者： Subandi Subandi Aulia Akhrian Syahidi Siti Zakiah Kiyoshi Kiyokawa Ahmad Riyadi M. Helmy Noor Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin Indonesia Informatics Engineering Undergraduate Program Faculty of Computer Science Universitas Brawijaya Malang Indonesia Cybernetics and Reality Engineering Laboratory Nara Institute of Science and Technology Ikoma Japan Informatics Engineering Diploma Program Politeknik Negeri Banjarmasin Banjarmasin Indonesia

ISBN: (纸本)9781665476652

Sasirangan cloth is one of the traditional cloths owned by Indonesia and is a typical cloth originating from the province of South Kalimantan. This Sasirangan cloth has many motifs and is unique. Sasirangan cloth is also one of the potentials that can attract local and foreign tourists to visit South Kalimantan. However, in recent years, tourist visits to South Kalimantan have decreased due to the impact of the COVID-19 pandemic. Then it also has an impact on the delay in the implementation of the Banjarmasin Sasirangan Festival which is usually held annually. The next impact is a decrease in turnover and interest in shopping for Sasirangan cloth, so that employees who work for Sasirangan cloth craftsmen are dismissed and reduce people's income. So the purpose of this study is to report the results of the development of a Virtual Reality Game application called VR-SasiranganKu by integrating the interaction of Non-Player Character (NPC) behavior with the type of narrative in the simulation genre game. VR-SasiranganKu is recommended to introduce and at the same time promote Sasirangan cloth to users, then justify the reaction to knowledge and shopping experience, and evaluate user experience using the UX Honeycomb method. Respondents involved as many as 100 people who are local and national tourists. The results show that the interaction of NPC behavior can provide good direction to users regarding the introduction of Sasirangan cloth by presenting an appropriate interaction design based on the narrative and the theme of the NPC that has been adopted, the results of justification using VR-SasiranganKu can provide knowledge reaction and very good shopping experience, and based on user experience evaluation that VR-SasiranganKu has adopted a very good UX with an average score of 4.91.

关键词： Human computer interaction COVID-19 Solid modeling Pandemics Games Virtual reality User experience

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Sentiment Analysis Model using Text and Emoticons for Pharmaceutical & Healthcare Industries

Sentiment Analysis Model using Text and Emoticons for Pharma...

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international conference on Innovative Sustainable Computational Technologies (CISCT)

作者： Bhaskaran S Veeramanickam M.R.M S. Hariharan N. Bharathiraja Pradeepa K Raja Marappan School of Computing SASTRA Deemed University Thanjavur India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science and Engineering Vardhaman College of Engineering Hyderabad India Department of Computer Science and Engineering St. Michael College of Engineering and Technology India

ISBN: (纸本)9781665474177

Background: Nowadays, pharmaceutical and healthcare industries apply sentiment analysis (SA) to analyze customers' feedback on pharmaceutical products. SA uses natural language processing (NLP) to recognize, assess and analyze the pharmaceutical data to extract valuable insights about the sentiment it conveys. Over the past two decades, in addition to text, emoticons have become a conventional way of expressing one's sentiments. The researchers utilizing textual data for SA have largely ignored emoticons due to their complexity and insufficient resources. Aim of the study: Necessary to include emoticons in SA to capture the emotion expressed by pharmaceutical data. However, this research develops an algorithm that performs SA on text and emoticons. Methods: To highlight the significance of emoticons, the analysis has been conducted on text-only and text-and-emoticon data, using deep learning (DL) and machine learning (ML) methods on multiple datasets. The features – term frequency-inverse document frequency (TF–IDF), emoticon lexicons, and a bag of words (BoW) are taken for simulation. Results: simulation of text features using BiLSTM provides better accuracy, between 85% and 90%, compared to other methods. The precision lies between 70% and 90%. The recall is lowered to 64%. The sentiment the emoticon conveys outweighs that of the text associated with it. In addition, the DL algorithms outperform the ML methods. The overall results indicate that considering emoticons along with text positively impacts ***, it is noted that the DL model marginally outperforms all of the ML algorithms used. Conclusions: This research analyzed the augmentations to the implementation, including multiple enhancements during the pre-processing stage, the inclusion of emojis, and the usage of a bi-long short-term memory network (BiLSTM) in the DL model. The experimental results conclude that better measures are obtained using the DL method.

关键词： Industries Deep learning Sentiment analysis Analytical models Machine learning algorithms Computational modeling Medical services

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Intelligent Task Offloading for Smart Devices in Mobile Edge Computing

Intelligent Task Offloading for Smart Devices in Mobile Edge...

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international Wireless Communications and Mobile Computing conference, IWCMC

作者： Osama Saleem Suleman Munawar Shanshan Tu Zaiwar Ali Muhammad Waqas Ghulam Abbas Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and Technology Topi Pakistan Faculty of Information Technology Beijing University of Technology Beijing China Faculty of Electrical Engineering GIK Institute of Engineering Sciences and Technology Topi Pakistan Department of Computer Engineering College of Information Technology University of Bahrain Bahrain School of Engineering Edith Cowan University Perth WA Australia

Mobile edge computing (MEC) is used for compu-tationally complex applications by offloading it to the nearby edge server either partially or entirely. The problem arises of selecting whether the component is to be offloaded to the mobile edge server (MES) for execution, or it needs to be executed locally. Therefore, we propose a time-efficient decision offloading scheme (TEDOS) to derive a data set and train an artificial neural network (ANN) on the derived data set. TEDOS provide the smart decision on the optimal permutation of the divided components based on delay. We developed a mathematical model for delays in communication, execution and component queuing. We obtained a final delay for all possible permutations of component offloading policies. Our model obtained 91 % accurate results as compared to the existing schemes. The simulation result shows that our proposed model outperforms the state-of-the-art.

关键词： Training Multi-access edge computing Computational modeling Artificial neural networks Mathematical models Delays Numerical models

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