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检索条件"任意字段=Conference on Mathematical Methods in Computer Science"

共 8068 条记录，以下是61-70 订阅

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Analytical Review of Orchestration methods for Distributed Computing Systems Under Conditions of Dynamic Scaling

Analytical Review of Orchestration Methods for Distributed C...

引用

International conference on Current Problems of Applied Mathematics and computer Systems, CPAMCS 2023

作者： Egor, Shiriaev Ekaterina, Bezuglova Georgiy, Valuev Natalya, Gladkova North-Caucasus Federal University Stavropol Russia North-Caucasus Center for Mathematical Research North-Caucasus Federal University Stavropol Russia

ISBN: (纸本)9783031640094

In this paper, a study of orchestration methods is carried out in order to find the most optimal method for managing distributed computing systems. To solve this problem, a study was made of methods for analyzing distributed computing systems, as well as methods of orchestration. In the course of the study, it was found that for building distributed computing systems with dynamic scaling, it is most optimal to use hybrid orchestration based on mathematical modeling of the system. As a solution, the use of hybrid orchestration based on OASIS TOSCA templates and Kubernets containers is proposed. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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Optimization of Double Wishbone Suspension: Evaluating the Performance of Classes of Algorithms

Optimization of Double Wishbone Suspension: Evaluating the P...

引用

2024 International conference on Applied Mathematics and computer science, ICAMCS 2024

作者： Arshad, Muhammad Waqas Lodi, Stefano University of Bologna Dept of Computer Science and Engineering Bologna Italy

ISBN: (纸本)9798350363807

Double wishbone suspension systems are employed in high-performance vehicles owing to their superior control over wheel motion. The design of a double-wishbone suspension is a challenging multi-objective problem due to the many inter- related quantities that are key in determining its performance and vary during its motion. The design activity is thus a time-consuming and complex iterative process that aims to tune their variation and minimize deviations from the desired performance characteristics while requiring the satisfaction of mechanical constraints. Computational optimization methods can be integrated into the design activity only after an assessment of their capability to support efficiently and effectively an iterative workflow. In this work, we start with the mathematical modeling of the camber angle of the double wishbone suspension. Then, we use the multi-model optimization approach that includes metaheuristic algorithms (Genetic Algorithms, Particle Swarm Optimization, Gradient Descent, and Ant Colony Optimization) and classical methods (Nelder-Mead, Interior Point, Simulated Annealing, and Random Search). These methods are assessed in terms of objective value, computational time, and memory usage in an effort to minimize the variation of camber angles from the specified constraints. The results prove that the Interior Point method is more accurate and efficient in optimizing the suspension's camber angle across its operational range, followed by other classical methods. © 2024 IEEE.

关键词： Cambers

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Interdisciplinary TPACK: A Case Study Using Variables, I/O, and Loops with Graduate Teacher Candidates in a methods Course 54

Interdisciplinary TPACK: A Case Study Using Variables, I/O, ...

引用

54th IEEE Frontiers in Education conference, FIE 2024

作者： Kalathas, Paris Parham-Mocello, Jennifer Oregon State University CorvallisOR United States

ISBN: (纸本)9798350351507

This research paper describes the mathematics teacher knowledge transformation when computer science concepts are integrated with mathematics. During the last decade, schools and educators made a significant effort to introduce computer science (CS) and Computational Thinking (CT) in K-12. While this effort produced some positive results in schools where resources and specialized educators are available, there are school districts where creating new classes and/or hiring specialized teachers is not a sustainable option. This creates a need for teachers that are specialized in one subject area to expand their knowledge into CS and CT, and teach these concepts in their classes. This knowledge expansion and integration should result in creating integrated curricula using their subject matter knowledge and the newly acquired CS knowledge. This implies that the teacher should be able to identify the intersection of concepts between the two fields, and leverage their difference and similarities to promote deep learning for their students. The current study explores how the teacher candidates' technological, pedagogical content knowledge (TPACK) in mathematics is affected when mathematical concepts are integrated with CS and CT. This study is a three-day intervention in a graduate level secondary mathematics education methods course, where utilizing Math + CS integrated modules we infuse CS concepts into mathematics. The already known mathematics context reduced the cognitive load for familiarizing the teacher candidates with CS, and the integration of the CS concepts provided a different perspective for thinking about mathematics and teaching. After having the teacher candidates reflecting on the concepts of Variable and Equal Sign (=), our results showed that they started noticing the differences and nuances between the two fields, developing this way their interdisciplinary Math + CS TPACK (I-TPACK) knowledge. Furthermore, the study showed that representing multiplicati

关键词： mathematical transformations

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Krylov Solvers for Interior Point methods with Applications in Radiation Therapy and Support Vector Machines 24th

Krylov Solvers for Interior Point Methods with Applications ...

引用

24th International conference on Computational science (ICCS)

作者： Liu, Felix Fredriksson, Albin Markidis, Stefano KTH Royal Inst Technol Stockholm Sweden RaySearch Labs Stockholm Sweden

ISBN: (纸本)9783031637483;9783031637490

Interior point methods are widely used for different types of mathematical optimization problems. Many implementations of interior point methods in use today rely on direct linear solvers to solve systems of equations in each iteration. The need to solve ever larger optimization problems more efficiently and the rise of hardware accelerators for general purpose computing has led to a large interest in using iterative linear solvers instead, with the major issue being inevitable ill-conditioning of the linear systems arising as the optimization progresses. We investigate the use of Krylov solvers for interior point methods in solving optimization problems from radiation therapy and support vector machines. We implement a prototype interior point method using a so called doubly augmented formulation of the Karush-Kuhn-Tucker linear system of equations, originally proposed by Forsgren and Gill, and evaluate its performance on real optimization problems from radiation therapy and support vector machines. Crucially, our implementation uses a preconditioned conjugate gradient method with Jacobi preconditioning internally. Our measurements of the conditioning of the linear systems indicate that the Jacobi preconditioner improves the conditioning of the systems to a degree that they can be solved iteratively, but there is room for further improvement in that regard. Furthermore, profiling of our prototype code shows that it is suitable for GPU acceleration, which may further improve its performance in practice. Overall, our results indicate that our method can find solutions of acceptable accuracy in reasonable time, even with a simple Jacobi preconditioner.

关键词： Interior point method Krylov solver Radiation therapy Support Vector Machines

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Applications of Fuzzy Set Models in Optimizing Agricultural Production Structures in Smart Farms 1

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23rd International conference on Next Generation Wired/Wireless Networks and Systems (NEW2AN) / 16th conference on Internet of Things and Smart Spaces (RuSMART)

作者： Ishnazarov, Akram Mamasoliyev, Sarvar Tashkent State Univ Econ Dept Math Methods Econ Tashkent Uzbekistan

ISBN: (数字)9783031609978

ISBN: (纸本)9783031609961;9783031609978

This article emphasizes the application of fuzzy logic in the field of agriculture. The use of fuzzy logic is not restricted to specific agricultural domains, but rather extends from soil analysis to the entire process of plant production, encompassing various areas within agriculture. To gain a better understanding of fuzzy logic in agriculture, a concise and comprehensive literature review has been conducted. Crop yield estimation fuzzy logic involves the incorporation of input parameters such as productivity, area, and labor expenses. Through the application of fuzzy arithmetic to these parameters, a precise crop yield value is obtained. The fuzzy modeling employs optimal membership functions. The accuracy of the results is verified by comparing them with existing open-source literature.

关键词： fuzzy logic fuzzy inference system membership functions fuzzy mathematical programming problems graded membership

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methods of Analyzing Random Point Structures in Solving Some Applied Engineering Problems

Methods of Analyzing Random Point Structures in Solving Some...

引用

2024 International conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

作者： Reznik, Alexander Soloviev, Alexander Institute Of Automation And Electrometry Of The Siberian Branch Of The Russian Academy Of Sciences Novosibirsk Russia

ISBN: (纸本)9798350395013

The article describes a method to solving a practical engineering problem related to the process of reading of random structures using an integrator that can capture only a certain number of point objects. methods to solving this problem are described, based on creating of efficient software tools that use branched analytical manipulations on a computer in their work. One of the ways to solve this problem is the creation and use of a specialized system that performs an analytical calculation of the volume of polyhedra in n-dimensional space. The second way is integration method using calculations with two free parameters. A number of exact analytical formulas have been found that can be directly used in various fields related to probability theory, mathematical statistics, queuing theory and others. The work demonstrates it is necessary to use a large set of software and mathematical tools in solving many engineering problems. © 2024 IEEE.

关键词： Statistics

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Mixed Integer Linear Programming-Based methods for the Optimal Time-Constrained Cost-Sensitive Decision Tree 12th

Mixed Integer Linear Programming-Based Methods for the Opt...

引用

12th International conference on Computational Data and Social Networks, CSoNet 2023

作者： Pham, Hoang Giang Quang, Toan Tran ORLab Faculty of Computer Science Phenikaa University Hanoi Viet Nam Faculty of Computer Science Phenikaa University Hanoi Viet Nam

ISBN: (纸本)9789819706686

Cost management and completion timelines are common classification problem requirements. For instance, a blood test requires human and equipment resources, costs money, and must be done quickly. To avoid major patient risks, medical diagnosis should minimize positive-to-negative misclassification. There has been extensive research on how to build a decision tree from training data that minimizes misclassification and test costs, but not on how to design an optimal decision tree with time constraints. A mixed-integer programming is implemented to create an optimal time-constrained cost-sensitive decision tree in this study. We adapt several existing approaches in the literature with time constraints, misclassification cost, and feature selection cost, and introduce new mathematical models designed for these problems. Our experiments compare all methods and examine how time and cost constraints affect optimal solution identification and demonstration. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Decision trees

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A Method to Classify Emotions Based on BERT 4

A Method to Classify Emotions Based on BERT

引用

4th International Signal Processing, Communications and Engineering Management conference, ISPCEM 2024

作者： Chen, Zeli Lin, Jian Jiang, Jie Jing, Di Department of Computer Science Lafayette College EastonPA United States School of Information Technology and Artificial Intelligence Zhejiang University of Finance and Economics Zhejiang Hangzhou China Department of Mathematical and Statistical Sciences University of Alberta EdmontonABT6G 2G1 Canada School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China

ISBN: (纸本)9798331528676

Nowadays, as science and technology continue to advance, addressing people's emotional issues is of particular significance, and how to accurately and efficiently recognize emotions has become increasingly prominent. We explores sentiment recognition and classification methods, including rule-based approaches, traditional machine learning models, deep learning models, and multi-modal sentiment analysis. Through comparative analysis, we will evaluate the effectiveness of these methods in handling social media texts. Additionally, we has developed a BERT-based two-stage model that first determines sentiment polarity (positive or negative) and then performs detailed classification of negative emotions. This two-stage model significantly improves accuracy and detail recognition compared to traditional one-stage models and other baseline methods. The results show that our approach not only enhances sentiment analysis accuracy but also provides deeper insights into the emotional subtleties of social media texts. This advancement holds significant practical implications for real-time sentiment monitoring and more effective crisis management strategies. ©2024 IEEE.

关键词： Contrastive Learning

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Exploring the Compositional Deficiency of Large Language Models in mathematical Reasoning Through Trap Problems

Exploring the Compositional Deficiency of Large Language Mod...

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2024 conference on Empirical methods in Natural Language Processing, EMNLP 2024

作者： Zhao, Jun Tong, Jingqi Mou, Yurong Zhang, Ming Zhang, Qi Huang, Xuanjing School of Computer Science Fudan University China Shanghai Key Laboratory of Intelligent Information Processing Fudan University China

ISBN: (纸本)9798891761643

Human cognition exhibits systematic compositionality, the algebraic ability to generate infinite novel combinations from finite learned components, which is the key to understanding and reasoning about complex logic. In this work, we investigate the compositionality of large language models (LLMs) in mathematical reasoning. Specifically, we construct a new dataset MATHTRAP‡ by introducing carefully designed logical traps into the problem descriptions of MATH and GSM8K. Since problems with logical flaws are quite rare in the real world, these represent "unseen" cases to LLMs. Solving these requires the models to systematically compose (1) the mathematical knowledge involved in the original problems with (2) knowledge related to the introduced traps. Our experiments show that while LLMs possess both components of requisite knowledge, they do not spontaneously combine them to handle these novel cases. We explore several methods to mitigate this deficiency, such as natural language prompts, few-shot demonstrations, and fine-tuning. Additionally, we test the recently released OpenAI o1 model and find that human-like 'slow thinking' helps improve the compositionality of LLMs. Overall, systematic compositionality remains an open challenge for large language models. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Model for Handwritten mathematical Expression Recognition Based on ResNet and Attention 6

Model for Handwritten Mathematical Expression Recognition Ba...

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6th International conference on Artificial Intelligence and Big Data, ICAIBD 2023

作者： Mu, Haofei Xu, Luqiang Southwest University of Science and Technology School of Computer Science and Technology Mianyang China

ISBN: (纸本)9781665491259

Handwritten mathematical expression recognition is still a challenging problem due to its two-dimensional structure and the complexity of handwriting. Handwritten mathematical Expression Recognition (HMER) methods based on encoder-decoder has achieved good results, but there are still some problems in the existing model, such as feature loss caused by multiple pooling of convolution neural network in coding operation and low efficiency of parsing feature caused by inaccurate attention in decoding operation. In view of the above problems, this paper focuses on offline handwritten mathematical expression recognition, and adopts the encoder-decoder model, It is proposed to use the residual network (ResNet) as the encoder for position coding, combine the gated recurrent unit (GRU) of attention mechanism as the decoder for effective decoding analysis, accurately carry out structure analysis and character recognition, and finally realize the end-to-end operation of input pictures and output LaTex strings. The proposed model was tested on the Competition on Recognition of Online Handwritten mathematical Expressions (CROHME) dataset, the experimental results show that this method can achieve relatively good recognition effect. © 2023 IEEE.

关键词： Character recognition

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