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检索条件"任意字段=7th International Conference on Functional Programming"

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the Joint Replenishment Problem with Cycle Time Constraints under General-Integer Policy 7

The Joint Replenishment Problem with Cycle Time Constraints ...

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7th international conference on Optimization and Applications, ICOA 2021

作者： Lin, Yu-Liang Yao, Ming-Jong National Chiao Tung University Transportation Logistics Management Hsinchu Taiwan

ISBN: (纸本)9781665441032

the joint replenishment problem (JRP) is to determine the replenishment cycle times of a group of items over an infinite planning horizon. We investigated the JRP with cycle time constraints under general-integer policy that are popular in industries and can be extended to minimum order quantity, delivery frequency, and storage capacity constraints. Based on our theoretical analysis on the optimality solution structures, we categorized the items into four types and developed an efficient algorithm for solving this constrained JRP. Our numerical experiments demonstrated that the proposed algorithm is effective and performs better than the existing approaches in the literature. © 2021 IEEE.

关键词： Nonlinear programming

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Implementing the Hammock-EFL Methodology for Project Management and Parallel programming: (Research in progress) 2021

Implementing the Hammock-EFL Methodology for Project Managem...

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7th conference on the Engineering of Computer Based Systems, ECBS 2021

作者： Goldstein, Moshe Eliezer, Oren Dayan, David Jerusalem College of Technology Israel

ISBN: (纸本)9781450390576

In this paper we present the Python implementation of the Hammock-EFL methodology, whose model is a combination of project schedule design and parallel program design. Actually, it is a useful combination of two paradigms taken from two different disciplines: the intrinsically parallel Hammock Cost Techniques for project management and the Flexible Algorithms' approach to parallel programming and computation, which has been implemented by EFL (Embedded Flexible Language). We show that the underlying hierarchical structure of a project (and its schedule), as well as that of a program, is essentially the same. We argue that this methodology, as a design tool, will allow the project designer, as well as the programmer, to think in a more holistic way, leading to the design of a time-efficient program, or project schedule. Now, that we have a tool based on the Hammock-EFL methodology, we will be able to do an in-depth investigation of the run time performance of programs written using it. © 2021 Association for Computing Machinery. All rights reserved.

关键词： Parallel programming

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Cost Optimisation on Cloud by Adoption of Rust programming

Cost Optimisation on Cloud by Adoption of Rust Programming

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international conference on ent Computing and Control Systems (ICICCS)

作者： Yogesh Parab Samaya Pillai Symbiosis Institute of Digital and Telecom Management Constituent of Symbiosis International (Deemed University) India

“Cloud computing” or “Compute over the cloud” is the on-demand delivery of IT resources like Computational power, networking infrastructure and various types of storage over the internet, which is scalable and elastic on demand. One only pays for the amount he uses. the traditional approach is to invest in on-premise hardware, buying, provisioning, and maintaining the same. Instead of the huge capital expenditure, operational expense on the cloud can be considered. One can save on costs, as maintenance and provisioning cost is transferred to the hyperscalers. Almost every other organization in the industry is adopting cloud computing as the go-to option. the flexibility and convenience are immense. Cloud is agile: Hyperscalers like AWS, Azure & GCP innovate continuously to bring about technological disruptions and support every reinvent in the techno space. this aids the developer communities worldwide not being bound by resource scarcity. Complex apps can be deployed in minutes and can be accessed from every part of the world. Developers gain the freedom to experiment with every possible technology, test new plans, and essentially transform and move towards a better future. With the increased popularity of Cloud Computing, multiple Tech giants have jumped into this space to provide cloud services and hence generate revenue. With the availability of a gamut of services and resources, multiple pricing tiers and a multitude of minuscule decisions at every step of implementation, cost optimization becomes a very crucial aspect to focus on. Every decision affects the cost one pays, from designing, resource provisioning and deployment. Hence this study tries to address various methods of cost optimization on the cloud. the narrative literature review approach has been adopted for the conceptualization of the model. the study provides implications to practitioners and developers for designing and developing cloud solutions at par with their requirements with optimal prici

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Energy Storage System Control Scheme based on Pretrained Adaptive Dynamic programming for PSOs

Energy Storage System Control Scheme based on Pretrained Ada...

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international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： R. Rajkumar Chudamani Ramineni D. Sateesh Kumar S. Kaliappan S Farook Christu Paul Ramaian Department of Electronics and Instrumentation Engineering Kongu Engineering College Erode Tamil Nadu India Department of Mathematics Prasad V. Potluri Siddhartha Institute of Technology Vijayawada Andhra Pradesh India Department of Engineering Mathematics Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Division of Research and Development Lovely Professional University Phagwara Punjab India Department of Electrical and Electronics Engineering School of Engineering Mohan Babu University Tirupathi Andhra Pradesh India Department of Automobile Engineering Hindustan Institute of Technology and Science Chennai Tamil Nadu India

With the increasing requirement of power the storage of energy becomes more and more challenging. To tackle this problem control schemes for energy storage systems are introduced. Over the years, various techniques were implemented in control schemes to improve its performance. In recent years, machine learning is widely used in control schemes for energy storage systems, one of those machine learning techniques is Adaptive Dynamic programming (ADP). ADP is a type of algorithm that allows the subject to improve its behavior in an unknown domain while interacting over a period of time. ADP is an online self-learning algorithm that uses the data collected over a period of time to improve itself. this study proposes an optimal energy control scheme for energy storage systems using ADP. the algorithm will take the parameters such as load demand, power consumed in the time period, and the cost of electricity in the given location as its input and the algorithm’s final objective is to improve the performance index of the energy storage system, the better the performance index the lower the electricity cost. this method will provide an optimum performance index for the energy storage system based on the input parameters presented to the algorithm. To improve the efficiency and to reduce the time consumption for self-learning of ADP algorithm pretraining was required. To retrain the ADP algorithm another algorithm is used i.e. Particle Swarm Optimization (PSO) was used. the PSO algorithm can find the optimum solution in a defined solution space. the pretrained ADP model provides an optimum performance index for the energy storage systems which reduces the cost of electricity.

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7th international conference on Computational Science and Technology, ICCST 2020

7th International Conference on Computational Science and Te...

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7th international conference on Computational Science and Technology, ICCST 2020

ISBN: (纸本)9789813340688

the proceedings contain 47 papers. the special focus in this conference is on Computational Science and Technology. the topics include: the Most Potential Decision Tree Technique to Classify the Large Dataset of Students;attention Models for Sentiment Analysis Using Objectivity and Subjectivity Word Vectors;a Question-Answering System that Can Count;contactless Patient Authentication for Registration Using Face Recognition Technology;drawing and Recognising Simple Shapes with Real-Time Feedback Using Pattern Recognition;information Technology Students’ Preferences on Blended Learning;preface;building a Knowledge Graph of Vietnam Tourism from Text;improved Facial Recognition Algorithms Based on Dragonfly and Grasshopper Optimization;optimization on the Financial Management of Banks with Two-Stage Goal programming Model;evaluating the Performance of Selected Mortality Forecasting Models: A Malaysia Case Study;assessing Python programming through Personalised Learning Styles Model;the programming Learning Assessment Model for Measuring Student Performance;design and functionality of a University Academic Advisor Chatbot as an Early Intervention to Improve Students’ Academic Performance;Multiprocessing Implementation for Building a DNA q-gram Index Hash Table;predicting Chart Difficulty in Rhythm Games through Classification Using Chart Pattern Derived Attributes;nasheed Song Classification by Fuzzy Soft-Set Approach;Hybrid SDN Deployment Using Machine Learning;technology Adoption Models: Users’ Online Social Media Behavior Towards Visual Information;LED Lighting Assessment for High-Performance Stadium Illuminance;split Balancing (sBal)—A Data Preprocessing Sampling Technique for Ensemble Methods for Binary Classification in Imbalanced Datasets;DyslexiAR: Augmented Reality Game Based Learning on Reading, Spelling and Numbers for Dyslexia User’s;applying Transfer Learning in Stock Prediction Based on Financial News.

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Analysis of Neural Network and Statistical Models Used for Forecasting of a Disease Infection Cases 7

Analysis of Neural Network and Statistical Models Used for F...

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7th IEEE international conference on Information Technology and Nanotechnology, ITNT 2021

作者： Abotaleb, Mostafa S.A. Makarovskikh, Tatiana South Ural State University Dept. of System Programming Chelyabinsk Russia

ISBN: (纸本)9781665432177

More than a year has passed since the coronavirus 2 (SARS-CoV2) pandemic began, and no one has been able to forecast the infection cases of the disease with high accuracy. Nowadays, a lot of studies are devoted to finding out the pattern of infection spreading and forecasting cases of infection. But models used in those studies have large errors in forecasts, and this makes it more challenging to discover the pattern of infection spreading. the choice of appropriate models may vary from country to country. the increase of the number of infection cases is one of the global challenges nowadays not only for virusologists and medicians, but also for data analytics. In our paper, we analyze errors in the forecast in the list of the top 10 countries affected by disease on January 1, 2021 using the following the neural network models, linear and non-linear classical statistical models, and also classical epidemiological SIR model. the other part of our computational experiment is devoted to forecasting the dates of the peak values of time series. It is shown on time series for the regions most affected by pandemics that neural network models allow to forecast this date with high accuracy. We also discover the possible field of application of such algorithms in other fields. © 2021 IEEE.

关键词： Forecasting

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Inverse Optimal Control with System Output

Inverse Optimal Control with System Output

引用

Industrial Cyber-Physical Systems (ICPS)

作者： Zihao Liang Shaoshuai Mou School of Aeronautics and Astronautics Purdue University IN USA

ISBN: (数字)9798350363012

ISBN: (纸本)9798350363029

this paper presents an incremental approach for addressing inverse optimal control (IOC) with only system output trajectory available. the unknown objective function is expressed as a weighted combination of features, where the weights are unknown. the proposed approach utilizes the optimality conditions for optimal state trajectory and the system output equation to iteratively solve the IOC problem with the initial optimal state available. In the case when the initial optimal state is unavailable, by utilizing the observed system output segments, we proposed a method to incrementally estimate the optimal initial state. Combining the aforementioned methods, we proposed an incremental algorithm to estimate the unknown weights. the method’s effectiveness is demonstrated through simulations on a 2-link robot arm and a 6-DoF maneuvering quadrotor system. In both cases, only limited system output segments are available.

关键词： Service robots Optimal control Cyber-physical systems Manipulators Linear programming Mathematical models 6-DOF

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Ubiquitous Learning Management Using Collaborative Inquiry-based Approach for programming Course: A Case Study of 3 Universities 23

Ubiquitous Learning Management Using Collaborative Inquiry-b...

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Proceedings of the 2023 7th international conference on Education and E-Learning

作者： Krittawaya thongkoo Kannika Daungcharone Jirapipat thanyaphongphat Patcharin Panjaburee College of Arts Media and Technology Chiang Mai University Thailand Faculty of Education Khon Kaen University Thailand

ISBN: (纸本)9798400708732

Aside from the necessary learning skills of logical thinking, problem-solving, and creativity, undergraduate students in the programming discipline must also be self-motivated because these abilities enable them to overcome obstacles and achieve success. In the digital learning era, a pedagogical approach emphasizing inquiry and collaborative approaches can enhance students' programming skills anywhere and anytime. As a result, this research aims to investigate the effects of collaborative learning on academic achievement and motivation by managing ubiquitous learning in computer courses at three universities in northern thailand using a collaborative inquiry-based approach. the learning environment allowed students to practice independently using the instructor-provided content and exercises. then, as part of group learning, students gave advice and shared knowledge until they found the best solution. Following class, the instructor discussed the merits of each group's responses with all students. Students were then asked to repeat the questions to ensure they completely understood the logical reasoning and problem-solving process. According to the findings, ubiquitous learning management based on collaborative inquiry-based approaches could help them learn more effectively, with higher learning achievement and motivation. the study's findings inspire further research into creating a collaborative digital learning environment in computer education, particularly from the standpoint of ubiquitous learning.

关键词： Collaborative learning Digital learning environment Inquiry-based learning U-learning

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Dynamic programming-Based Optimal Charging Scheduling for Electric Vehicles

Dynamic Programming-Based Optimal Charging Scheduling for El...

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IEEE international conference on Intelligent Transportation Engineering (ICITE)

作者： Kuan Li Ying Zhang Chenglie Du Tao You Lu Bai Jiaming Wu School of Software Northwestern Polytechnical University Xi’an China School of Computer Science Northwestern Polytechnical University Xi’an China Department of Architecture and Civil Engineering Chalmers University of Technology Gothenburg Sweden

the charging scheduling of electric vehicles not only affects the operation of the grid system, but also affects the charging cost of vehicle users. this paper studies the charging scheduling problem of electric vehicles from the user’s perspective by considering the grid’s as well as the user’s needs. On the basis of real-time electricity prices, an electric vehicle charging scheduling system aiming at the lowest charging cost is designed and an optimal charging scheduling method based on dynamic programming is established. In order to reduce the unnecessary computational expenses, this paper optimizes the dynamic programming algorithm, and defines the state transition limit of the dynamic programming search space according to the actual constraints, which reduces the computational complexity. the simulation results show that, on the premise of satisfying the power constraints and user charging demands, the electric vehicles charging scheduling system can effectively reduce the charging cost and time. In addition, the charging process has little impact on the power system from the perspective of grid fluctuation.

关键词： Fuzzy logic Vehicle-to-grid Costs Fluctuations Processor scheduling Simulation Dynamic scheduling

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Exploring the Use of Industrial Robots in CNC Machine Tool programming and Operation Courses

Exploring the Use of Industrial Robots in CNC Machine Tool P...

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IEEE international conference on Mechatronics System and Robots (ICMSR)

作者： Weiwen Ye School of Mechanical and Electrical Engineering Guangdong University of Science and Technology Dongguan City 523083 Guangdong China

CNC machine tools (Note: CNC’s full name is Computer Numerical Control, hereinafter referred to as CNC) is the core equipment of modern manufacturing, in the cutting and processing of moulds and mechanical parts, has an irreplaceable position. For a long time, CNC machine tools have been put into production processing individually or in bulk. In recent years, with the rapid development of new technologies, industrial robots have also been developed rapidly and put into use in various fields, and CNC machine tools and industrial robots are gradually combined into a whole. In CNC machining, the use of industrial robots maximises the inherent potential of CNC machine tools, making them simpler, more stable and more efficient. For the operator, the intervention of industrial robots makes the operation of CNC machine tools increasingly difficult, not only ensuring processing quality, but also improving processing efficiency. Robotics and CNC machining machine tools are a combination of robotics and CNC technology, enabling the machine tool to have a variety of features and functions of the robot at the same time, while the robot can have similar characteristics to the operator. this makes the combination of robotics and CNC machining machine tools more functional and powerful. It also reduces the manual labour intensity and improves the safety of industrial intensity. the use of industrial robots in CNC machining technology allows for better performance in the programming and manufacturing process. Not only can cutting work tasks be completed, but also precise robot operations and much more can be achieved. the use of robots improves the efficiency of industrial production and brings more convenience and profit to companies. In recent years, CNC machining technology has also developed rapidly, which in turn plays a full role in ensuring high product quality and output. For this reason, the authors analyse and explore the application of industrial robots in CNC machining

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