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检索条件"任意字段=5th International Conference on the Art, Science, and Engineering of Programming, Programming 2021"

共 1197 条记录，以下是1131-1140 订阅

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Comparative Analysis of Data Mining Techniques for Classification of Student's Learning Styles

Comparative Analysis of Data Mining Techniques for Classific...

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the 6th international conference on Chemical, Agricultural, Biological and Environmental sciences (CAFES-17);the 5th international conference on Studies in Business, Management, Education and Law (SBMEL-17);international conference on Advances in science, engineering and Technology (ICASET-17);international conference on arts, Social sciences, Humanities and Interdisciplinary Studies (ASSHIS-17)

作者： Renato R.Maaliw Ⅲ Melvin A.Ballera Shaneth C.Ambat Menchita F.Dumlao the Computer Engineering Department Southern Luzon State University Southern Luzon State University AMA University in the Philippines School of Graduate Studies of AMA University in the Philippines Research and Development of Philippine Women’s University in the Philippines

this study focused on the comparative performances of different classification algorithms provided in WEKA such as Neural Network,Na?ve Bayes,Part and J48 Decision Tree classifier in classifying students learning *** student's behavior and navigational patterns have been observed while using a learning management system and eleven attributes have been found to be significant in classifying student's learning styles based on the Felder-Silverman learning style model.A total of 60,158 rows of log and interaction data from 565 students of Computer programming 1 Moodle online course have been extracted.A 10-fold cross validation was used to evaluate the selected *** accuracy,training errors and kappa statistics have been observed to measure the performance of each *** experiment showed that the J48 decision tree technique had the highest collective average value of correctly classified instances at 87.56% accuracy and it could be used to classify the learning styles of students in a Learning Management System.

关键词： Learning management system Learning styles Felder-Silverman learning style model Educational data mining

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Modeling and Predicting Cyber Hacking Breaches

Modeling and Predicting Cyber Hacking Breaches

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international conference on ent Computing and Control Systems (ICICCS)

作者： R.Raja Subramanian Rithvik Avula Paramkusam Sree Surya Bellamkonda Pranay Computer Science and Engineering Kalasalingam Academy of Research and Education Virudhunagar India

A data breach is a security event, where sensitive data is accessed without any permission from a website or an organization. An information breach will be considered as the purposeful or accidental gathering of secure or personal data from an organization. A breach can be an accession of a data without any permission, these kinds of regulations should be provided with safe and secured framework but this is not happening in many corporations. So, by analyzing the previous attempts (successful or unsuccessful attacks), the proposed model can be trained to adapt to new scenarios and predict the next breach. Further, this research work has designed a model by using machine learning to defend a website from security breaches. the primary aim of this research work is to create a machine learning model, which trains in Realtime and monitors the website or a system and trains from the state-of-art attacks. the proposed model has created a web application using Django, which takes the data from multiple sources such as Amazon, Flipkart, Snapdeal, and Shop clues, which shows the data that is safe to obtain from the website. then, the data will be sorted on our page and then it will be made secured and illegal for the external people to access the data from our website and the proposed model will monitor the website 24/7. the model is trained daily and it generates predictions from the several of datasets available and from the previous state-of-the-art attacks. this model will be trained from the existing datasets and the history of attacks and breaches on our website.

关键词： Adaptation models Analytical models Statistical analysis Organizations Machine learning Predictive models Data breach

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A Two-stage Optimization Method for Intermodle Transportation

A Two-stage Optimization Method for Intermodle Transportatio...

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IEEE Advanced Information Management,Communicates,Electronic and Automation Control conference (IMCEC)

作者： Fan Chen HaiYan Luo Ping Zhang Qing Zhu Faculty of Geomatics Lanzhou Jiaotong University Lanzhou China School of Economics and Management Lanzhou Jiaotong University Lanzhou China School of Architecture and Urban Planning Lanzhou Jiaotong University Lanzhou China Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Chengdu China

ISBN: (纸本)9781665479691

this study focuses on one of the intermodel operational issues: how to select the best routes and transportation modes for shipments through the international intermodal network. Take into account of the “scale effect” of transportation cost, it is assumed to be a continuous piecewise linear function. the main objective is to find optimal paths so as to minimize the total transportation cost, and satisfying time window constraints and path capacity constraints at the same time. According to the characteristics of the model, established a two-stage solution method, in the first stage, ignore the transfer situation, and look for the first k shortest paths in the network, and the next step sorts the objective function by importance. After that, eliminate the pathes that do not satisfy the constraints according to the constraint condition. Finally, pick up the shortest path that meets all the constraints, and it is also the optimal solution. the case study verified effectiveness of the algorithm, and it also shows the importantance of path capacities, time constraints and transportation cost.

关键词： Costs Automation Transportation Optimization methods Economies of scale Linear programming Cost function

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Analyzing Students’ Learning Engagements Using PLS-SEM: A Case Study in A Small Private Online programming Course 22

Analyzing Students’ Learning Engagements Using PLS-SEM: A C...

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Proceedings of the 2022 6th international conference on Education and E-Learning

作者： Bilegjargal Daramsenge Nien-Lin Hsueh Lien-Chi Lai Department of Information Engineering and Computer Science Feng Chia University Taiwan

ISBN: (纸本)9781450398428

Nowadays, particularly during the epidemic situation, the increasing popularity of online-offline education. In computer science education, a small private online programming course (SPOPC) is an important curriculum course to enhance the students’ problem-solving, creative thinking and teamwork activities. the main purpose of this study is to investigate the influences of students’ composite engagements (learning performances and personal feelings) in a SPOPC. We applied an online engagement framework for higher education and partial least squares structural equation modeling (PLS-SEM) approach. Our analysis was conducted from a Python programming course at Feng Chia University, Taiwan, held in the fall semester of 2021–2022 through OpenEdu platform. Our results show that (1) Strongest mediator performance was ‘Video watching’ affected by four significant relations; (2) Behavioral engagement ‘BE’ and emotional engagement ‘EE’ are positively affected ‘Video watching’ performance and they were inextricably linked factors; (3) Social engagement ‘SE’ significantly affected the ‘Term project’ and ‘Final score’ through ‘Midtest’; (4) Cognitive engagement ‘CE’ did not significantly affect the ‘Term project’; Most important is that (5) Students’ first feelings about the course (the first part of the semester) are important factors in deciding to continue a related course or drop out of the course in the future. these findings have valuable practical implications for course instructors who design and lead the programming course.

关键词： programming course PLS-SEM Distance learning Composite engagements

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Automatic Indexing of Lecture Videos using Syntactic Similarity Measures

Automatic Indexing of Lecture Videos using Syntactic Similar...

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international conference on Signal Processing and Integrated Networks (SPIN)

作者： Shubhangi Jaiswal Manoj Misra Department of Computer Science and Engineering Indian Institute of Technology Roorkee India

In recent years, with increase in the use of internet the multimedia contents on it have rapidly increased. Users may need to go through a video in a top down manner i.e. browsing the videos, or in bottom up manner i.e. retrieving specific information from videos. they may also want to go through the summary or through the highlights of the videos. this has necessitated the need to handle multimedia resources effectively. this paper proposes an automatic method for aligning scripts of lecture videos with captions. Alignment is needed to extract time information from captions and insert it in the scripts, to create index of the videos. No alignment work has been previously done in lecture videos domain. Alignment methods proposed for other type of videos are not applicable for lecture videos because, different similarity techniques behave differently on different types of datasets. the proposed method uses transcripts of lecture videos, SRT file of captions available along with lecture videos and captions generated from auto-caption generation feature of YouTube. the captions and scripts are then aligned using a dynamic programming technique. No such work has been previously done for lecture videos. Most important aspect of alignment is similarity measure. In the proposed work we have used three similarity measures cosine, jaccard, and dice. A comparative analysis of these measures is given in the paper. We also use a large lexical database of English words known as WordNet for word-to-word similarity. the experimental result shows comparison of various similarity techniques and YouTube captions.

关键词： Videos YouTube Silicon Motion pictures Signal processing algorithms Syntactics

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Carbon Trading Based Short-Term Production Simulation of Wind Power Integrated System

Carbon Trading Based Short-Term Production Simulation of Win...

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IEEE conference on Energy Internet and Energy System Integration (EI2)

作者： Yubin He Yongquan Nie Chaoyi Peng Mingtao Liu Xionghua Shi Jun Xie Dispatching and Control Center China Southern Power Grid Guangzhou China College of Energy and Electrical Engineering Hohai University Nanjing China NR Electric Co. Ltd. Nanjing Jiangsu China

ISBN: (纸本)9781665434263

Under the background of low-carbon economy, wind power has become an important force in promoting the low-carbon development of electricity and has received widespread attention. However, the uncertainty of wind power brings new costs such as additional reserve capacity costs, balancing costs to the operation of power system, which weakens the market competitiveness of wind power. this paper redefines the short-term electricity cost composition from the perspective of low-carbon economy, and applies stochastic programming theory to propose a short-term production simulation model for wind power integrated system. the model aims to minimize the expected cost of electricity production in short-term time scale, coordinately optimize the day-ahead power output, real-time power output, power reserve capacity, wind spillage and load shedding. Simulation results of the modified IEEE 30-bus system show that the proposed model can effectively quantify and evaluate the impact of carbon trading mechanism, carbon trading price, and wind power installed capacity on electricity costs, carbon emission reduction and operation risks.

关键词： Costs Uncertainty Simulation Stochastic processes Carbon dioxide Production Low-carbon economy

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Motion Simulation and Optimization of LED Chip Scanning and Positioning Based on NX MCD

Motion Simulation and Optimization of LED Chip Scanning and ...

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Mechatronics Technology and Intelligent Manufacturing (ICMTIM), international conference on

作者： Zhengyu Li Fifi Liu Yikai Huang Jianwen Zhang School of Mechanical and Electrical Engineering Jiangxi University of Science and Technology Ganzhou

ISBN: (数字)9798350363265

ISBN: (纸本)9798350363272

the current LED chip scanning and positioning experiments heavily rely on physical testing equipment, demanding significant time and resources for device calibration. Moreover, the validation tests are prone to damaging the chips and tools, leading to unnecessary resource wastage. As a result, this paper adopts virtual debugging technology by using NX software to establish the LED chip detection machine's model and properties. It involves programming scan and point measurement procedures through TIA Portal software, and incorporates MCD cameras and visual software for template matching and positioning. Within the simulation environment, the paper performs motion simulation of redundant strategies for LED chip scanning and validates optimization methods to improve deduplication accuracy by 0.3%. this approach effectively minimizes the risks and resource consumption in actual experiments, while fostering the development of automation in chip visual positioning.

关键词： Visualization Semiconductor device measurement Solid modeling three-dimensional displays Debugging Inspection Light emitting diodes

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Surrogate-Assisted Hybrid Metaheuristic for Mixed-Variable 3-D Deployment Optimization of Directional Sensor Networks

Surrogate-Assisted Hybrid Metaheuristic for Mixed-Variable 3...

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Data-driven Optimization of Complex Systems (DOCS), international conference on

作者： Yuntian Zhang Chen Chen Tongyu Wu Changhao Miao Shuxin Ding School of Automation Beijing Institute of Technology Beijing China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing China Traffic Management Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit Beijing China

A major concern in designing sensor networks is the deployment problem. However, establishing an efficient algorithm for the real-world deployment problem is challenging due to three issues, which are 1) the realistic mixed-integer nonlinear programming problem (MINLP) with mixed-variable; 2) the combinatorial subset selection problem; and 3) the expensive computational cost for fitness evaluation in the 3-D coverage problem. therefore, this paper addresses these challenges and proposes a surrogate-assisted hybrid metaheuristic for mixed-variable 3-D deployment optimization of directional sensor networks (DSNs). First, an MINLP with flexible coordinate transformation technique and an efficient mixed-variable encoding scheme are introduced to model and represent the problem. We propose hybrid metaheuristic which applies two reproduction methods respectively for discrete and continuous variables. Second, we design sparse population-based incremental learning (s-PBIL) to handle inherent subset selection problem. s-PBIL could accurately learn the required information, and automatically learn a sparse distribution. third, a mixed-variable surrogate with unifying space under Bayesian model management is incorporated to reduce the expensive computational cost. Experiment results on real-world deployment scenarios scaling from small-size to large-size show the effectiveness of the proposed algorithm.

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Attention Mechanism for Fashion Image Captioning 5th

Attention Mechanism for Fashion Image Captioning

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5th international conference on Green Technology and Sustainable Development, GTSD 2020

作者： Nguyen, Bao T. Prakash, Om Vo, Anh H. Faculty of Information Technology Ho Chi Minh City University of Technology and Education Ho Chi Minh City Viet Nam Department of Computer Science and Engineering H.N.B Garhwal University Srinagar India Artificial Intelligence Laboratory Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9783030623234

Image captioning tries to make computer learn to understand the visual content of a given image and produce one or more description sentences. Recently, with the help from rapid development of deep learning, image captioning has become an active research. the encoder-decoder architecture is commonly considered as the baseline method to address image captioning. this model focuses on recognizing objects and the relationship among these objects. However, with fashion images, the generated sentence should not only describe items inside the input image, but also mention item attributes such as texture, fabric, shape, style, etc. this requirement of fashion image captioning is not able to be solved by the image-captioning method based on the traditional encoder-decoder architecture. Our study addresses this issue by proposing an image captioning model based on the attention mechanism for fashion image which is able to cover both items and the relationship among the detailed attributes of items. We introduce an efficient framework for fashion image captioning that incorporates spatial attention inside the traditional encoder-decoder architecture. Our model generates fashion image captions using the spatial attention mechanism, which dynamically modulates the sentence generation context in multi-layer feature maps. Experiments were conducted on Fashion-Gen, one of state-of-the-art fashion image dataset, and achieved CIDEr/ROUGE-L/BLEU-4 scores of 0.913, 0.502, and 0.221, respectively. Based on experiments, it is consistently presented that our proposed model has significantly improved the performance of fashion-image captioning task, and it even surpasses the baseline methods on the same fashion benchmark dataset. © 2021, the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Recurrent neural networks

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API Design and Development for Developer Payroll in Startups Based on Agile Productivity Factors

API Design and Development for Developer Payroll in Startups...

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international conference on science and Technology-Computer (ICST)

作者： Yang Agita Rindri Rudy Hartanto Ridi Ferdiana Departement of Electrical Engineering and Information Technology Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9781728123691

ISBN: (纸本)9781728123707

Software startups are growing rapidly now. One of the important challenges faced by startups is how to formulate and calculate payroll for developers appropriately and easily that can satisfy both developers and startups. To help startups in calculating the developer payroll formulation appropriately and easily, a payroll application is required. However, developing a payroll application is not too easy and takes a lot of effort for startups. Especially for new startups that still do not have more resources in developing a payroll application. In this paper, Application programming Interface (API) for developer payroll is designed and implemented based on agile projects. the API is designed based on the payroll calculation method that considers developer productivity parameters, i.e developer's years of experience, type of roles, bug, and timeliness. API for developer payroll is expected to facilitate and ease the development of developer payroll information system by startups in need. this study designed and developed 7 Payroll REST API resources using *** Web API. the API testing is conducted using POSTMAN with 100% successful test results.

关键词： Productivity Software Organizations Computer bugs Remuneration Indexes Task analysis

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