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Research on the Water Level Optimization of the Great Lakes Based on Ford-Fulkerson Algorithm 24

Research on the Water Level Optimization of the Great Lakes ...

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4th international conference on artificial Intelligence, Big Data and Algorithms, CAIBDA 2024

作者： Hong, Zihan Xi, Dongyang Zhang, Kaixiang Yan, Tingting School of municipal and environmental engineering Shenyang Jianzhu University Liaoning Shenyang China School of Material Science and Engineering Shenyang Jianzhu University Liaoning Shenyang China School of Science Shenyang Jianzhu University Liaoning Shenyang China

ISBN: (纸本)9798400710247

Based on the intrinsic relationship between the data of the Great Lakes region and the geographical data, we developed a water flow network model and a hidden programming model to discuss how to apply the principles of graph theory and natural science to find the shortest path and the maximum flow. this model uses the Ford-Fulkerson algorithm and designs a differential equation model based on the dynamic relationship of water flow in the Great Lakes region. the study used available water level data, combined with detailed information on lakes and rivers, to create a graph-theoretical model. To maintain the ideal water level, the water level is converted into volume, and the result is obtained by whether the fluctuation range is exceeded. In addition, to evaluate the effectiveness and sensitivity of this method, we also designed a value analysis model to solve the optimization problem of the five lakes. this study not only demonstrates the application of graph theory and optimization theory in solving the Great Lakes problem, but also emphasizes the importance of considering environmental factors and conducting sensitivity analysis in model development and evaluation. © 2024 Copyright held by the owner/author(s).

关键词： Analytic hierarchy process

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Multi-stage Robust Optimal Planning of Microgrid Clusters in the Environment of Distribution-side Electricity Market 4

Multi-stage Robust Optimal Planning of Microgrid Clusters in...

引用

4th international conference on Advanced Electrical and Energy Systems, AEES 2023

作者： Chai, Wei Xie, Peikun Li, Zhenkun Zhang, Zhiquan State Grid Shanghai Municipal Electric Power Company Electric Power Research Institute Shanghai China Shanghai University of Electric Power School of Electric Power Engineering Shanghai China

ISBN: (纸本)9798350342659

With the development of the distribution power market, an increasing number of microgrids will appear in the distribution system. In this paper, a multi-stage robust optimal planning method for microgrid clusters is proposed to solve the interest conflict between microgrid clusters and distribution system. Based on the master-slave game theory, this method establishes a two-layer programming mathematical model for the distribution network and the microgrid clusters. In the upper layer, the optimal operation model of the distribution network is established to reduce operating costs and improve the voltage level. In the lower layer, the optimal planning model for the microgrid clusters is constructed to determine the allocation and capacity of each microgrid. In addition, considering the uncertainty of load growth, the robust optimization strategy is added in our methodology to improve the robustness of the planning scheme. Because the above model is a robust optimization bi-level programming problem, the Karush-Kuhn- Tucker(KKT) condition is used to convert the original problem into a single-level equilibrium constraint mathematical programming problem, thus the programming problem can be achieved by the Column-and-Constraint Generation(C&CG) algorithm. Finally, through the analysis of IEEE-33 node, the results show that the method improves the ability of the distribution network to absorb renewable energy and the Operation Index of the distribution network, at the same time, it ensures the economic benefits of investors and effectively realizes the coordinated development of distribution network and micro-grid. © 2023 IEEE.

关键词： Electric power distribution

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the Interaction Interface Design Method of Fresh Food E-Commerce Based on Kansei engineering 4

The Interaction Interface Design Method of Fresh Food E-Comm...

引用

4th international conference on Intelligent Design, ICID 2023

作者： Wu, Kai Yang, Chaoxiang East China University of Science and Technology School of Art Design and Media Shanghai200237 China

ISBN: (纸本)9798350342574

To meet the user's Kansei requirements for the interactive interface of fresh food e-commerce, and address existing issues such as irrational interface layout, visual jumps, and unsatisfactory interactive feedback, this dissertation proposes an interface design program that adheres to the user experience based on Kansei engineering (KE) theory. Firstly, perceptual imagery word pairs collected are subjected to factor analysis to obtain five significant perceptual imagery factors. Subsequently, the interface elements are divided, and a quantitative analysis method is proposed, referred to as Quantitative theory I (QT-I). this approach establishes a correlation model between Kansei appeals and homepage interface factors, enabling the transformation of Kansei appeals into design variables to derive important attributes of the original homepage interface design elements. Finally, through the analysis of model results feasibility, key interface design elements that impact users' perceived demands are identified, guiding interface design decisions. this research methodology holds practical significance not only for fresh food e-commerce interface design but also for other mobile interface designs. © 2023 IEEE.

关键词： Design

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Natural Language programming towards Solving Addition-Subtraction Word Problems for assessing AI-based offensive code generators

Natural Language Programming towards Solving Addition-Subtra...

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Data engineering and Communication Systems (ICDECS), international conference on

作者： Arepelly Shylesh Chirra Dhanush Reddy Bokka Sai Yashwanth Reddy Shruti Kansal Department of Computer Science and Engineering Vardhaman College of Engineering Hyderabad India

programming remains a dark art for beginners. the gap between how people speak and how computer programs are made has always made it hard for people to become programmers. Learning all the complex rules of programming languages can be really tough and often stops people from trying coding. But here, we have an idea to make things much easier. We’re working on a special tool that lets you tell the computer what you want to do in regular human language, whether you write it or say it out loud. It will then create the actual computer code for you, like magic! this will make programming easy, efficient, and user-friendly. By combining NLP and automatic code generation, our project wants to help people express their programming ideas in a way that feels natural and easy. this will bring in a new era of coding that’s friendly to everyone, making it possible for people of all kinds to bring their computer ideas to life without worrying about confusing coding rules.

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Efficient & Sustainable Intrusion Detection System Using Machine Learning & Deep Learning for IoT 4

Efficient & Sustainable Intrusion Detection System Using Mac...

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4th international conference on Computing, Mathematics and engineering Technologies, iCoMET 2023

作者： Amir, Muhammad Sarim Bhatti, Gufran Anwer, Misbah Iftikhar, Yumna Karachi Institute of Economics and Technology Dept. of Computer Science Karachi Pakistan

ISBN: (纸本)9798350335316

Everything is evolving toward IoT (Internet of things) and online-based in our technological environment. the number of IoT devices and ubiquitous computing systems are growing exponentially. this also increases the risk of network breach. To cater this issue many researchers proposed different techniques and get great results but it can be better since everything in online and it's a matter of security and privacy. this paper presents an efficient and sustainable intrusion detection system by the concatenation of two well-known state of the art 'kitsune' datasets (ARP MITM and SSDP Flood). Random Forest, decision tree, and Bi-LSTM (Bi-Directional Long Short Term Memory) were implemented in different training and testing ratios and different numbers of layers. Performance measures show that all the models achieved over 99% accuracy but random forest outperforms both models on the concatenated dataset. Both attacks are determined by the given model hence increasing the performance and the system will notify in case of any malicious activity. © 2023 IEEE.

关键词： Internet of things

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MPI4All: Universal Binding Generation for MPI Parallel programming 24th

MPI4All: Universal Binding Generation for MPI Parallel Progr...

引用

24th international conference on Computational science (ICCS)

作者： Pineiro, Cesar Vazquez, Alvaro Pichel, Juan C. Univ A Coruna CITIC La Coruna Spain Univ Santiago de Compostela Elect & Comp Sci Dept Santiago De Compostela Spain Univ Santiago de Compostela CITIUS Santiago De Compostela Spain

ISBN: (纸本)9783031637483;9783031637490

Message Passing Interface (MPI) is the predominant and most extensively utilized programming model in the High Performance Computing (HPC) area. the standard only provides bindings for the low-level programming languages C, C++, and Fortran. While efforts are being made to offer MPI bindings for other programming languages, the support provided may be limited, potentially resulting in functionality gaps, performance overhead, and compatibility problems. To deal with those issues, we introduce MPI4All, a novel tool aimed at simplifying the process of creating efficient MPI bindings for any programming language. MPI4All is not dependent on the MPI implementation, and adding support for new languages does not require significant effort. the current version of MPI4All includes binding generators for Java and Go programming languages. We demonstrate their good performance with respect to other state-of-the-art approaches.

关键词： Parallel computing MPI Bindings Java Go

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A Two-Phase Submission Algorithm Using Dynamic programming for Kafka Consumer Committing Offset 4

A Two-Phase Submission Algorithm Using Dynamic Programming f...

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4th international conference on Signal Processing and Computer science, SPCS 2023

作者： Lv, Ruiguang Wu, Gang Li, Zhi Li, Runlin Zhang, Mimi State Grid Information & Telecommunication Group Co. Ltd. Beijing China

ISBN: (纸本)9781510672505

As an important middleware of distributed computing, message queue enables us to address issues like decoupling applications, asynchronous communication, fluctuating data traffic, and others. Kafka is a popular open-source message queue for collecting, processing, storing, and analyzing messages at scale, which is famous for its excellent performance, low latency, fault tolerance, and high throughput. In some scenarios like electronic trading, reliable consumption is the utmost concern. However, the native consumer client provided by Kafka cannot guarantee that messages are consumed successfully at least once. this paper proposes a two-phase submission algorithm using dynamic programming which can improve reliability of message consuming. this algorithm utilizes a two-phase submission to ensure that every message is consumed successfully at least once, and uses dynamic programming to improve submission efficiency. We conduct experiments to demonstrate that this algorithm is more efficient in contrast with the original submission strategy. In experiments, this algorithm must make sure that every message is consumed successfully at least once while various consuming failure rates are mocked. © 2023 SPIE.

关键词： Dynamic programming

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Research on MRI Image Super-Resolution Reconstruction Algorithm Based on Information Distillation 4

Research on MRI Image Super-Resolution Reconstruction Algori...

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4th IEEE international conference on Data science and Computer Application, ICDSCA 2024

作者： Zhu, Huazheng Tang, Ling Jia, Yuanyuan Liu, Yaping Zhang, Jun Jiang, Aiping Nie, Zicheng School of Computer Science and Engineering Chongqing University of Science & Technology Chongqing China School of Digital Economy Chongqing Vocational College of Art and Engineering Chongqing China College of Medical Informatics Chongqing Medical University Chongqing China

ISBN: (纸本)9798350368239

In recent years, deep learning has demonstrated powerful capabilities in computer vision tasks and injected new energy into MRI image super-resolution reconstruction algorithms. However, existing MRI super-resolution methods based on 2D and 3D CNNs require interpolation to upsample low-resolution images, which increases the computational burden. To address this, this paper proposes an MRI image super-resolution algorithm based on information distillation, called DASID-SR. the algorithm uses information distillation to reduce network parameters and computational complexity while extracting deep features, and applies sub-pixel convolution for direct reconstruction and upsampling, thereby reducing the model's complexity. the core innovations include constructing a Mixed Information Distillation Module (M-IMDB), introducing a differentiable architecture search algorithm in the deep feature extraction module, and implementing dense connections between modules to enhance feature utilization efficiency. Experimental results show that on the Kirby21 and ALVIN-adult datasets, with a reconstruction factor of 3, the proposed method achieves peak signal-to-noise ratios (PSNR) of 40.21dB and 37.56dB, respectively, outperforming other networks by 0.02dB to 2.68dB and 0.02dB to 1.41dB. Moreover, the model's parameter size is only 0.45MB, demonstrating that the proposed algorithm can generate high-quality MRI images while maintaining a low parameter count. ©2024 IEEE.

关键词： Signal to noise ratio

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Data augmentation for schizophrenia diagnosis via vision transformer-based latent diffusion model 4

Data augmentation for schizophrenia diagnosis via vision tra...

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4th international conference on Biomedicine and Bioinformatics engineering, ICBBE 2024

作者： Yang, Yuxuan Ma, Shidong Cao, Shengjie Jia, Sihan Bi, Yuda Calhoun, Vince D. Shandong University of Science and Technology Shandong Qingdao China Tri-institutional Center for Translational Research in Neuroimaging and Data Science GSU GATech Emory AtlantaGA30303 United States

ISBN: (纸本)9781510682443

Schizophrenia (SZ) is a complex and heterogeneous disorder. Characterizing functional magnetic resonance imaging (fMRI) imaging patterns specific to SZ is challenging and can benefit greatly from advanced artificial intelligence techniques. Prior research has shown that fMRI data can be summarized in functional network connectivity matrices (FNCs) using group independent component analysis (ICA), significantly reducing computational burden for tasks such as classification which also maintaining relevant information. Recent advances in the development of state-of-the-art latent diffusion models (LDMs) have shown promise for various generative tasks, such as image generation and data augmentation. this study leverages a lightweight vision transformer (ViT) encoder-decoder architecture instead of the traditional U-net as an effective denoising function in LDMs for FNC generation. this approach addresses the challenge of small datasets that often lead to lower accuracy such as in the use of neuroimaging data to diagnose schizophrenia. © 2024 SPIE.

关键词： Magnetic resonance imaging

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QPCC: a quantum programming course for inhomogeneous cohorts of professional learners 4

QPCC: a quantum programming course for inhomogeneous cohorts...

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4th IEEE international conference on Quantum Computing and engineering (QCE) / IEEE Quantum Week / 2nd IEEE Quantum science and engineering Education conference (QSEEC)

作者： Dimitrov, Emil Dunne, Conor Kannan, Venkatesh Krishnakumar, Karthik de Rituerto, Pablo Lauret Martinez Vieites, Pablo Suarez Tiwari, Rajarshi Wolf, Richard A. Univ Galway Irish Ctr High End Comp ICHEC Galway Ireland

ISBN: (纸本)9798350343236

the ongoing accelerated development and exploration of Quantum Computing (QC) - systems, software, algorithms and applications - has generated a huge amount of interest and need among a wide range of organisations and user communities to better understand the technology paradigm, its maturity, limitations and opportunities, and positioning alongside classical high-performance computing (HPC) methods and tools. this interest and need to learn about QC has been accentuated by the rapidness and breadth of developments in QC that is being disseminated in both mainstream and specialist scientific/technical media as well as the accessibility to early quantum computing systems and tools. It has become a challenge for the (potential) user community to sift through the material catering to developing bottom-up fundamental scientific/mathematical skills as well as top-down exploitation oriented knowledge. As the National and one among the European Competence Centres in HPC, the Irish Centre for High-End Computing (ICHEC) has worked with an international advisory board composed of quantum computing technology developers, the user community and the Irish State Agency's network that is responsible for national enterprise skills development in ICT to create and deliver a blended course which is customisable, modular and stackable, thereby offering different learning pathways to professional learners from the academic, enterprise and public sector communities with inhomogeneous backgrounds. Particular emphasis is laid on the stakes of engaging learners and organisations with different knowledge basis, skills and learning objectives, as well as making the content suitably-positioned and approachable to all (e.g. varied levels of mathematical knowledge required for basic understanding of quantum computing versus developing quantum algorithms). In this paper, we discuss the Quantum programming Certification Course (QPCC) by summarising the 4-year design process with the advisory boar

关键词： high-performance quantum computing HPC-QC inhomogenous cohorts professional learners blended modular stackable course

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