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A bound on uniquely decodable code pair for two-user binary adder channel

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND computer scienceS 1996年第5期E79A卷 687-693页

作者： Shi, JJ Watanabe, Y Department of Knowledge Engineering and Computer Science Doshisha University Tanabe Kyoto-fu 610-03 Japan

A uniquely decodable code pair (C, S) is considered for the two-user binary adder channel. When the first code C is linear, a lower bound of \S\ is formulated and a uniquely decodable code pair (C, S) is presented. Wh... 详细信息

关键词： coding of multiple access channel uniquely decodable independence number simple graph linear code

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SoAy: A Solution-based LLM API-using Methodology for Academic Information Seeking 25

SoAy: A Solution-based LLM API-using Methodology for Academi...

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Proceedings of the 31st ACM SIGKDD Conference on knowledge Discovery and Data Mining V.1

作者： Yuanchun Wang Jifan Yu Zijun Yao Jing Zhang Yuyang Xie Shangqing Tu Yiyang Fu Youhe Feng Jinkai Zhang Jingyao Zhang Bowen Huang Yuanyao Li Huihui Yuan Lei Hou Juanzi Li Jie Tang School of Information Renmin University of China Beijing China & Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing China Institute of Education Tsinghua University Beijing China Department of Computer Science and Technology Tsinghua University Beijing China School of Information Renmin University of China Beijing China & Engineering Research Center of Database and Business Intelligence MOE Beijing China School of Information Renmin University of China Beijing China Zhipu AI Beijing China

ISBN: (纸本)9798400712456

Applying large language models (LLMs) to academic API usage shows promise in reducing researchers' efforts to seek academic information. However, current LLM methods for using APIs struggle with the complex API coupling commonly encountered in academic queries. To address this, we introduce SoAy, a solution-based LLM methodology for academic information seeking. SoAy enables LLMs to generate code for invoking APIs, guided by a pre-constructed API calling sequence referred to as a solution. This solution simplifies the model's understanding of complex API relationships, while the generated code enhances reasoning efficiency. LLMs are aligned with this solution-oriented, code-based reasoning method by automatically enumerating valid API coupling sequences and transforming them into queries and executable *** evaluate SoAy, we introduce SoAyBench, an evaluation benchmark accompanied by SoAyEval, built upon a cloned environment of APIs from AMiner. Experimental results demonstrate a 34.58-75.99% performance improvement compared to state-of-the-art LLM API-based baselines. All datasets, codes, tuned models, and deployed online services are publicly accessible at https://***/RUCKBReasoning/SoAy.

关键词： academic information seeking

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Classification with ensembles and case study on functional magnetic resonance imaging

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Digital Communications and Networks 2022年第1期8卷 80-86页

作者： Adnan OM.Abuassba Zhang Dezheng Hazrat Ali Fan Zhang Khan Ali Department of Computer Science Arab Open University-PalestineRamallahPalestine Department of Computer Science and Communication Engineering University of Science and Technology BeijingChina and Beijing Key Laboratory of Knowledge Engineering for Materials ScienceBeijing100083China Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabadPakistan

The ensemble is a technique that strategically combines basic models to achieve better accuracy ***,combination methods,and selection topology are the main factors determining ensemble ***,it is a challenging task to design an efficient ensemble *** though numerous paradigms have been proposed to classify ensemble schemes,there is still much room for *** paper proposes a general framework for creating ensembles in the context of ***,the ensemble framework consists of four stages:objectives,data preparing,model training,and model *** is comprehensive to design diverse *** proposed ensemble approach can be used for a wide variety of machine learning *** validate our approach on real-world *** experimental results show the efficiency of the proposed approach.

关键词： Classification Ensemble learning Extreme learning machine

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Optimizing novel thermal energy storage systems: Enhancing melting efficiency with tubes, stands, and advanced machine learning techniques

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Journal of Energy Storage 2025年 124卷

作者： Almadhor, Ahmad Basem, Ali Singh, Pradeep Kumar Othman, Nashwan Adnan Samad, Sarminah Alhomayani, Fahad M. Abduvalieva, Dilsora Ali, H. Elhosiny Akram, Muhammad Afzal, Abdul Rahman Department of Computer Engineering and Networks College of Computer and Information Sciences Jouf University Saudi Arabia Faculty of Engineering Warith Al-Anbiyaa University Karbala56001 Iraq Department of Mechanical Engineering Institute of Engineering & Technology GLA University U.P. Mathura281406 India Department of Computer Engineering College of Engineering Knowledge University Erbil44001 Iraq Department of Computer Engineering Al-Kitab University Altun Kupri Iraq Department of Management College of Business Administration Princess Nourah bint Abdulrahman University Riyadh11671 Saudi Arabia College of Computers and Information Technology Taif University Saudi Arabia Applied College Taif University Saudi Arabia Department of Mathematics and Information Technologies Tashkent State Pedagogical University Bunyodkor avenue 27 Tashkent100070 Uzbekistan Physics Department Faculty of Science King Khalid University P.O. Box 9004 Abha Saudi Arabia Faculty of Design Informatics and Business University of Abertay Scotland Dundee United Kingdom Department of Industrial Engineering College of Engineering University of Business and Technology Jeddah21361 Saudi Arabia

The transition to renewable energy is crucial to meet growing global energy demands while minimizing environmental impact. Solar energy, a leading renewable source, faces limitations due to its intermittent nature, making energy storage systems essential for continuous supply. Thermal energy storage systems (TESSs) provide a compelling solution, especially by utilizing latent heat storage with phase change materials (PCMs), which efficiently store large amounts of energy. However, PCM-based systems suffer from low thermal conductivity and weak heat transfer performance. Numerous techniques to amend the thermal conductivity of PCMs, whether applied individually or together, show promise for improving the efficiency of TESSs. However, challenges like increased viscosity, decreased latent heat capacity, high costs, and complex manufacturing often limit their practical use. Thus, it is crucial to investigate more straightforward and more cost-effective solutions, like incorporating extended surfaces into the PCM container. In this study, a novel approach is taken to ameliorate the heat transfer surface area in TESSs by incorporating tubes and stands inside the PCM container rather than relying on conventional fins. A new compact TESS design was introduced, featuring fixed tubes supported by aluminum-made stands. Two artificial neural networks (ANN) models were trained with input parameters, including the length of the vertical stands, horizontal stands, and tilted stands, to anticipate the half-melting time and complete melting time of the PCM. In the end, two optimal designs of O-TESS1 and O-TESS2 were proposed by a single-objective optimization, focusing on minimizing the half and complete melting times of the PCM, respectively. A multi-objective optimization was also performed to balance the mentioned objectives. Using the generated data, a Pareto front and TOPSIS-selected designs were developed to visualize the trade-offs between these competing objectives. It took

关键词： Solar heating

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Dialectic operator fuzzy logic

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science China(Technological sciences) 1996年第1期39卷 1-10页

作者：程晓春姜云飞刘叙华 Open Lab for Symbolic Computation and Knowledge Engineering Department of Computer ScienceJilin UniversityChangchun 130023China

Dialectic operator fuzzy logic (DOFL) is presented which is relevant,paraconsistent and *** can vividly describe the belief revision in the cognitive process and can infer reasonably well while the knowledge is incons... 详细信息

关键词： operator fuzzy logic relevant logic nonmonotonic logic paraconsistent logic.

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INTEGRATING knowledge-BASED SYSTEMS AND DATABASES

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CLINICA CHIMICA ACTA 1993年第1-2期222卷 101-115页

作者： GRIMSON, JB Knowledge and Data Engineering Group Department of Computer Science Trinity College Dublin 2 Ireland

In recent years, there has been an explosion of interest among the computing community in the field of artificial intelligence, particularly in the areas of natural language processing and knowledge-based systems (KBS). The medical domain has seen the development of hundreds of KBSs and there is substantial evidence to show that the application of a knowledge-based approach to decision support can go a long way towards overcoming the information overload experienced by many clinicians today. Yet many of these medical KBSs are still at the prototype stage and are mainly confined to research laboratories. There are many reasons for this apparently slow take-up of the technology, but one of the most significant is the lack of integration into the regular routine information processing of the organisation, in particular the database processing. This paper discusses the benefits of such integration and methods for achieving it in the context of general trends in information systems. Database technology provides efficient and secure management of large amounts of data in a multi-user, multiapplication environment. knowledge-based technology, on the other hand, provides mechanisms for building intelligent systems. Thus, for example, given a set of facts about a domain (symptoms, laboratory test results, etc.) together with a set of rules which apply to that domain (e.g.'if TT4 > 150 nmol/l then suspect hyperthyroidism'), a KBS can deduce new information about that domain automatically. The effective integration of these two technologies is seen as a means of achieving the intelligent information systems of the future. There are three basic approaches to integrating KBSs and databases. The first is to start with the KBS and incorporate data management functions. Alternatively, intelligence from the KBS can be incorporated into the database. Finally, the two systems can be allowed to coexist as independent systems which can talk to each other by means of standard interfaces.

关键词： DATABASE MANAGEMENT knowledge-BASED SYSTEMS EXPERT SYSTEMS

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Performance analysis of machine learning techniques for glaucoma detection based on textural and intensity features

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International Journal of Innovative Computing and Applications 2020年第4期11卷 216-230页

作者： Singh, Law Kumar Garg, Hitendra Pooja Khanna, Munish Department of Computer Science and Engineering School of Engineering and Technology Sharda University Knowledge Park III Greater Noida India Department of Computer Science and Engineering Hindustan College of Science and Technology Mathura India Department of Computer Engineering and Applications GLA University Mathura India

Glaucoma is one of the significant causes of blindness, which covers about 15% to 20% of the total population, so early-stage detection is essential. The proposed methods apply fast fuzzy C-means approach to determine optics-cup-to-disc ratio (CDR) followed by textural based and intensity-based features of the eye. Textural features include local binary pattern, grey-level co-occurrence matrix, and Harlick features, whereas intensity-based features include colour moment and skewness. Machine learning techniques are applied to extract entropy, horizontal, vertical diameter of optics disc/cup, textural based and intensity-based features that classify the image as glaucoma or healthy image and obtained ophthalmologists verify results. Own dataset of 298 retinal images consisting of both healthy and glaucomatous images is used for experimental analysis. In the proposed method, various machine learning techniques like support vector machine (SVM), K-nearest neighbour, and naive Bayes, report 95.5%, 93.3%, and 94.35% accuracy, respectively. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Support vector machines

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Towards the Technology Neutral Modeling of Management Components

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Journal of Network and Systems Management 2003年第1期11卷 39-56页

作者： Lewis, David Wade, Vincent Cullen, Brian Knowledge and Data Engineering Group Department of Computer Science Trinity College Dublin Dublin 2 Ireland

This paper outlines an Architectural Model and accompanying modeling notation that addresses on the need to model management component interfaces and their business contexts in a technology neutral manner in order to promote convergence on stable, reusable solutions. The approach combines existing modeling concepts related to component-based and model-driven software development from TINA-C, OMG, DMTF and TM Forum in order to provide guidance on the development of models that need to be exchanged between organizations involved in the development of software components and the management systems in which they are used. The Architectural Model is assessed through application to the management a specific set of e-business support services.

关键词： Electronic commerce

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Integrating the policy dialectic into dynamic spectrum management

Integrating the policy dialectic into dynamic spectrum manag...

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2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks

作者： Lewis, David Feeney, Kevin O'Sullivan, Declan Knowledge and Data Engineering Group Department of Computer Science and Statistics Ireland CTVR Ireland Knowledge and Data Engineering Group (KDEG) Department of Computer Science and Statistics TCD Ireland

ISBN: (纸本)9781424406623

In this paper we propose a holistic approach to modeling the management of dynamic spectrum access (DSA). We argue that the range to issues involved requires not just a management scheme, but also a meta-management scheme whereby management processes are monitored, analyzed and improved. In this way different proposals for management can be refined through interaction in a dialectic that reacts to the problems and conflicts of a given management scheme as well as the changes in the technological, social, economic and political environment. We examine Stafford Beer's Viable Systems Model as a possible basis for a framework that encompasses a variety of feedback loops involved in addressing operations, management and meta-management together. We also propose how this model could be mapped onto a concrete policy meta-management system and sketch out issues worthy of further investigation in developing a holistic DSA management framework.

关键词： Metadata

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A review of neuro-symbolic AI integrating reasoning and learning for advanced cognitive systems

Intelligent Systems with Applications

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Intelligent Systems with Applications 2025年 26卷

作者： Uzma Nawaz Mufti Anees-ur-Rahaman Zubair Saeed Knowledge and Data Science Research Centre Department of Computer and Software Engineering College of Electrical and Mechanical Engineering National University of Science and Technology Islamabad Pakistan Military College of Signals National University of Science and Technology Islamabad Pakistan Department of Electrical & Computer Engineering Texas A&M University College Station TX USA Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar

Neuro-symbolic AI represents the convergence of two principal paradigms in artificial intelligence: neural networks, which are efficient in data-driven learning, and symbolic reasoning, which offers explainability and logical inference. This hybrid methodology combines the adaptability of neural networks with symbolic AI's interpretability and formal reasoning abilities, which provide a practical framework for advanced cognitive systems. This paper analyzes the present condition of neuro-symbolic AI, emphasizing essential techniques that combine reasoning and learning. We explore models such as Logic Tensor Networks, Differentiable Logic Programs, and Neural Theorem Provers. The study analyzes their impact on the advancement of cognitive systems in natural language processing, robotics, and decision-making. The paper examines the challenges faced by neuro-symbolic AI, such as scalability, integration with multimodal data, and maintaining interpretability without compromising efficiency. By evaluating the strengths and weaknesses of many methodologies, we comprehensively understand the field's development and its potential to revolutionize intelligent systems. In addition, we identify emerging research areas, including the incorporation of ethical frameworks and the development of adaptive dynamic neuro-symbolic systems that respond in real-time. This review aims to guide future research by providing insights into the potential of neuro-symbolic AI to influence the development of the next generation of intelligent, explainable, and adaptive systems.

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