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The Influence of Load Growth on Nepal's Distribution Network: Examining the Integration of Electric Cooking Stoves 15

The Influence of Load Growth on Nepal's Distribution Network...

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15th International conference on software, knowledge, Information Management and Applications, SKIMA 2023

作者： Shah, Prashant Kumar Paudel, Sushil Government of Nepal Kathmandu Valley Water Supply Management Board Nepal Kantipur Engineering College Department of Computer and Electronics Engineering Nepal

ISBN: (纸本)9798350316551

In the present context, the government of Nepal is promoting the use of electric cooking stoves (ECS) over liquefied petroleum gas(LPG). With the use of ECS on a large scale, the distribution feeder load will increase significantly, resulting in a reduced voltage level at buses, increased loading on the distribution transformer, and, in fact, increased current carried by the feeder conductor. The study focuses mainly on the loading of the distribution transformer (DT), the voltage level at the buses, and the ampacity of the feeder conductor. The study is carried out considering two feeders: the Jorpati feeder in the Kathmandu district and the Malangwa feeder in the Sarlahi district of Nepal. The load and ZIP Coefficients of the study area are estimated by the polynomial load modeling technique based on a seasonal basis. The results show that the major impact is seen on the Jorpati feeder during the winter season. Considering the winter load and penetration of ECS at each household in the Jorpati feeder, there is overloading on 23 DTs. The existing dog conductor will not be able to handle the increasing demand for load current and the voltage level at buses drops slightly. Similarly, in the Malangwa feeder, the results show that the major impact is seen in the summer season. There is overloading on almost all the DTs except the private one, slightly low voltage levels at a few buses, and the existing feeder conductor will not be able to handle the increasing current requirement. Thus, system upgradation is required before promoting the use of ECS at each household in the Jorpati and the Malangwa area. © 2023 IEEE.

关键词： Feeding

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2nd International conference on Science, engineering Management and Information Technology, SEMIT 2023

2nd International Conference on Science, Engineering Managem...

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2nd International conference on Science, engineering Management and Information Technology, SEMIT 2023

ISBN: (纸本)9783031722868

The proceedings contain 46 papers. The special focus in this conference is on Science, engineering Management and Information Technology. The topics include: Verification and Validation of knowledge engineering Systems: A Life Cycle Framework;The Critical Factors of Success of Gamification in Digital Banking Services: Using Analytic Hierarchy Process (AHP) Approach;e-Shopping Sites Preference Analysis with Multi-criteria Decision-Making Methods;advancing Anemia Diagnosis: Harnessing Machine Learning Methods for Accurate Detection;monkeypox Detection with K-mer Using Machine Learning Algorithms;cloud Computing Model for Handling Medical Big Data: A Mobile Hospital Pervasive Healthcare Application;Harnessing Advanced AI Techniques: An In-Depth Analysis of Machine Learning Models for Improved Diabetes Prediction;image Processing in Toxicology: A Systematic Review;augmented Reality Immersive World with Hologram Special Effect in Early Childhood Education;improving the Visual Ergonomics of Computerised Workplaces Through the Use of Specialised Eye-Rest software;a Diagnosis Model based on Federated Learning for Lung Cancer Classification;Arrhythmia Detection from ECG Traces Images Using Transfer Learning Approach;enhancing Traffic Flow Prediction in Urban Areas Through Deep Learning and Probe Information: A Comparative Study;an Approach to Multi-agent Deep Q-Network Optimization of Signal Control in Multi-intersection Road Environments to Enhance Urban Traffic Flow;blockchain-Driven Smart Contracts: An Overview of Application Areas and Gap Identification in Construction Management Literature;stochastic Optimization Methodology for Production Planning with Uncertain Demand and Lead Time based on the Digital Twin;role of Top Management Commitment and Information Technology Investment in Digital Transformation;antecedents of Mobile Banking Apps Adoption Among Consumers in Ghana.

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Research and Implementation of Financial Management System based on Data Mining Technology

Research and Implementation of Financial Management System B...

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2023 International conference on Power, Electrical engineering, Electronics and Control, PEEEC 2023

作者： Yang, Lingyun Henan University of Engineering Henan Zhengzhou450007 China

ISBN: (纸本)9798350329124

Data Mining (DM) technology is a technique that extracts potential and valuable knowledge from massive amounts of *** present, big data technology has been widely used in all fields in the world. If enterprises want to make great progress, they must keep up with the pace of the times. Therefore, the management mode of enterprises is becoming more and more networked and information-based, and in the management of enterprises, financial management is gradually approaching networking. Therefore, the design of financial software must meet the needs of the network. In order to enhance the core competitiveness of enterprises and make them invincible in the industry, we must start from the inside of enterprises, change the business philosophy, and strengthen enterprise financial management combined with modern information *** financial work of an enterprise requires the accuracy of data collection and accurate information and data management. Especially for the financial management of large-scale enterprises, it has more complex operation difficulties, which brings greater work to the financial staff of the enterprise burden. Therefore, DM algorithms and financial management systems are necessary. This paper briefly expounds the relevant theories, methods and technologies of the visual DM technology and the construction of the financial management information system of DM. © 2023 IEEE.

关键词： Data mining

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COMPUTATIONAL FLUID DYNAMICS SIMULATION OF SLOSHING INSIDE BEVERAGE CANS ON A ROTARY FILLING MACHINE 38

COMPUTATIONAL FLUID DYNAMICS SIMULATION OF SLOSHING INSIDE B...

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38th ECMS International conference on Modelling and Simulation, ECMS 2024

作者： Solari, Federico Lysova, Natalya Scano, Federico Montanari, Roberto Bedogni, Enrico Copelli, Gabriele University of Parma Department of Engineering and Architecture Parco Area delle Scienze 181/A Parma43124 Italy Krones AG Böhmerwaldstraße 5 Neutraubling93073 Germany Gabriele Copelli Engineering Office Via Benedetta 75 Parma43122 Italy

Sloshing is a critical issue in many industrial contexts. In the food industry, it becomes particularly relevant during the filling of beverage cans and bottles with automatic rotary machines, when the uncapped filled containers move to the transfer star wheel, suddenly changing direction of motion and potentially causing the spilling of the product. Deep knowledge of the system behavior and the fluid dynamics in the domain is essential to guarantee the safety and quality of the final products and processing environment. In this study, Computational Fluid Dynamics (CFD) was used to simulate sloshing in beverage cans using two CFD software: commercial ANSYS Fluent and open-source OpenFOAM. Some modeling strategies are explored with the aim of making the simulation more efficient without impacting the results, and an approach for tracking the maximum fluid level in the can is proposed. The modeling methodology was validated by means of an analytical model and by comparing the results calculated by the two software. Finally, operational insights were derived based on the results of a sensitivity analysis carried out by varying the star wheel diameter and the system productivity. ©ECMS Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev (Editors) 2024.

关键词： Open systems

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Cascade Sampling via Dual Uncertainty for Active Entity Alignment 1

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16th International conference on knowledge Science, engineering and Management (KSEM)

作者： Xie, Jiye Li, Jiaxin Tan, Jiawei Wang, Hongxing Chongqing Univ Minist Educ Key Lab Dependable Serv Comp Cyber Phys Soc Chongqing Peoples R China Chongqing Univ Sch Big Data & Software Engn Chongqing Peoples R China

ISBN: (数字)9783031402869

ISBN: (纸本)9783031402852;9783031402869

Entity Alignment (EA) aims to find and unite equivalent entities across different knowledge graphs for knowledge fusion. It requires pre-aligned entity pairs as seed alignments to train an EA model. Recent effort has employed active learning (AL) to query more informative seed alignments for effective EA modeling at a lower cost. However, it still challenges existing AL methods to find and diversify seed alignments since true alignments themselves are sparse and unavailable before getting annotated. To address this issue, we manipulate seed alignment query based on entity selection on a single knowledge graph and deploy active learning on the EA task by querying entities that behave with (i) Matching Uncertainty determined by the EA model in training and (ii) Novelty-oriented Uncertainty estimated through diverse entity identification. To adapt the query set to changes in the EA model and aligned entities during AL iterations, we propose a dynamic cascade sampling strategy by trading-off between matching uncertainty and novelty-oriented uncertainty in a two-stage manner. Experiments on real-world benchmark datasets show the effectiveness of the proposed approach in comparison with state-of-the-art methods.

关键词： Entity Alignment Active Learning Dual Uncertainty Cascade Sampling knowledge Graph

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Color works ranking based on multi-scale texture enhancement and style representation 4

Color works ranking based on multi-scale texture enhancement...

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4th International conference on Neural Networks, Information and Communication engineering, NNICE 2024

作者： Yu, Songsen Wu, Zefeng Liang, Jun Kuang, Xiaoyang South China Normal University School of Software Foshan China

ISBN: (纸本)9798350394375

The ranking of color works is an important task to assist art education. Color works express the image through color coordination and composition, which is significantly different from other visual tasks in terms of visual characteristics, image semantics and aesthetic criteria. Currently, there is little research on the ranking of teaching color works, and the relevant color datasets is not suitable for ranking requirements. To address these issues, we first collect 4068 color works and construct a dataset. Then, we propose a novel network architecture for automatic ranking of color works. This network reuses knowledge from large datasets through transfer learning, and leverages the style and texture of images to improve the performance of CNN in color ranking. The network consists of two branches: the style representation branch and the texture feature branch. The style representation branch incorporates the importance of style information into feature maps through a style-based weight recalibration module, enhancing the style representation of features. The other branch uses a multi-scale feature texture enhancement module to extract multi-scale and global texture information in the deep features. Experimental results on the color works dataset show that our method outperforms other methods. © 2024 IEEE.

关键词： Color

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A Model-based Multi-agent Framework to Enable an Agile Response to Supply Chain Disruptions 18

A Model-based Multi-agent Framework to Enable an Agile Respo...

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IEEE 18th International conference on Automation Science and engineering (IEEE CASE)

作者： Bi, Mingjie Chen, Gongyu Tilbury, Dawn M. Shen, Siqian Barton, Kira Univ Michigan Inst Robot Ann Arbor MI 48109 USA Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Due to the COVID-19 pandemic, the global supply chain is disrupted at an unprecedented scale under uncertain and unknown trends of labor shortage, high material prices, and changing travel or trade regulations. To stay competitive, enterprises desire agile and dynamic response strategies to quickly react to disruptions and recover supply-chain functions. Although both centralized and multi-agent approaches have been studied, their implementation requires prior knowledge of disruptions and agent-rule-based reasoning. In this paper, we introduce a model-based multi-agent framework that enables agent coordination and dynamic agent decision-making to respond to supply chain disruptions in an agile and effective manner. Through a small-scale simulated case study, we showcase the feasibility of the proposed approach under several disruption scenarios that affect a supply chain network differently, and analyze performance trade-offs between the proposed distributed and centralized methods.

关键词： Computer aided software engineering Pandemics Network topology Scalability Supply chains knowledge based systems Decision making

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Teaching Platform of Resonant System based on the Hybrid Programming of MATLAB and C++ 2

Teaching Platform of Resonant System Based on the Hybrid Pro...

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2nd International conference on Applied Statistics, Computational Mathematics, and software engineering, ASCMSE 2023

作者： Qu, Xinyue Zhang, Yongli Wang, Lili Si, Wei School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China School of Information Technology Beijing Institute of Technology Guangdong Zhuhai China

ISBN: (数字)9781510668195

ISBN: (纸本)9781510668188

"Principles of Automatic Control" is a basic course for automation majors, and the laboratory class plays a supporting role in classroom teaching and plays an important role in the autonomy and innovation of students. In order to train students to be proficient in control system analysis and design, a resonant system teaching platform was designed using a mixture of MATLAB and C++ programming. Real-time data transmission is carried out through the upper computer and the resonant system experiment platform, to achieve the interactive teaching and demonstration function. At the same time, it can visually demonstrate the teaching content of control theory from system modeling to time domain and frequency domain response analysis experiments, which can effectively improve students' understanding and comprehensive application of theoretical knowledge. © 2023 SPIE.

关键词： MATLAB

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Construction method of Geographic knowledge Graph based on Micro-Annotation

Construction method of Geographic Knowledge Graph based on M...

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Big Data & Artificial Intelligence & software engineering (ICBASE), International conference on

作者： Xingshu Wang Ying Nie North China Institute of Computing Technology NCI Beijing China

ISBN: (数字)9798331506612

ISBN: (纸本)9798331506629

This paper discusses the construction method of geographic knowledge map based on the combination of geographic information system (GIS) and artificial intelligence. In this paper, a construction method based on micro-annotation is proposed. By optimizing the process of data acquisition and annotation, representative texts are selected for annotation, and iterative training is performed to improve the efficiency and accuracy of entity relation extraction. A structured data collection framework is designed, natural language processing technology is used to automatically extract key information from geographic text, and the geographic knowledge map is constructed for experimental verification. The results show that the proposed method is superior to traditional methods in terms of construction cost, training speed and extraction accuracy. At the end of the paper, the limitation and future direction of the research are discussed, which provides a reference for the further study of geographical knowledge map.

关键词： Training Accuracy Annotations knowledge graphs Data models Natural language processing Data mining Reliability Geographic information systems software engineering

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Integrating the Biological knowledge from Protein Databases Into Spatial RNA Sequencing Analyses 26th

Integrating the Biological Knowledge from Protein Database...

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26th International conference on Information Integration and Web Intelligence, iiWAS 2024

作者： Leśniewska, Anna Dziȩgielewski, Szymon Melnyk, Elena Okoniewski, Michal J. Wrembel, Robert Institute of Computing Sciences Poznan University of Technology Poznan Poland Department of Biosystems Science and Engineering ETH Zurich Basel Switzerland Scientific IT Services ETH Zurich Zurich Switzerland

ISBN: (纸本)9783031780929

Spatial transcriptomics has emerged in recent years as an advanced technique integrating modern microscopy and single-cell RNA sequencing (RNA-seq). The computational aspect of spatial transcriptomics analysis is actively evolving, with software packages like Squidpy at the forefront. A critical challenge in this field is achieving reliable image segmentation based on RNA expression levels within cells, necessitating robust sets of genomic signatures. In this paper, we present our approach to addressing this challenge through data integration and by leveraging proteome signatures from The Human Protein Atlas as a reference standard, applicable to transcriptomic profiles. Our heuristic-based segmentation method provides biological validation for unsupervised techniques and serves as a preliminary proof of concept. Additionally, it establishes a benchmark for the future application of artificial intelligence with the use of transcriptome foundation models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Biotic

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