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The Meaning of Independence in Local Institutions from Neutrosophic Perspective

Neutrosophic Sets and Systems 2025年 77卷 463-478页

作者： Mohammed, Alaa A. Abdulrahman, Sabah S. Khalid, Huda E. Smarandache, Florentin Salama, A.A. University of Telafer Legal Affairs Department Telafer University Iraq University of Telafer Telafer University Telafer Iraq Mathematics Physics and Natural Science Division University of New Mexico 705 Gurley Ave GallupNM87301 United States Dept. of Math and Computer Sci. Faculty of Science Port Said University Egypt

It is well known that the term vagueness is spread in all aspects of our lives, this manuscript will clarify the meaning of independence (strict meaning of independence, the illusory meaning of independence, Oscillating between the true meaning of independence, and the fallacy of claiming independence and not applying it), this triplet actually refers to the three components that the Neutrosophic theory standing on which is (truthiness, falsity, indeterminacy), the strategy of applying the notion of independency in the local institutions, enlighten on the allegation of applying the independency notion in some governments’ institutions without a real impact of this term, and studying the meaning of independence from the perspective of a country legal system, all these issues and some comparisons in applying the term (independency) between some countries such as Iraq, France, Algeria, USA, etc. have been enclosed in this article. © 2025, University of New Mexico. All rights reserved.

关键词： Laws and legislation

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From Data to Combinatorial Multivector field Through an Optimization-Based Framework

arXiv

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arXiv 2025年

作者： Côté, Dominic Desjardins Woukeng, Donald Département de Mathématiques Université de Sherbrooke SherbrookeQC Canada Division of Computational Mathematics Faculty of Mathematics and Computer Science Jagiellonian University ul. St. Lojasiewicza 6 Krakow30-348 Poland

This paper extends and generalizes previous works on constructing combinatorial multivector fields from continuous systems (see [10]) and the construction of combinatorial vector fields from data (see [2]) by introducing an optimization based framework for the construction of combinatorial multivector fields from finite vector field data. We address key challenges in convexity, computational complexity and resolution, providing theoretical guarantees and practical methodologies for generating combinatorial representation of the dynamics of our *** Codes 54H30, 37B35, 65P99, 55U10, 06A06 Copyright © 2025, The Authors. All rights reserved.

关键词： Combinatorial optimization

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A Scalable Training-Free Diffusion Model for Uncertainty Quantification 24

A Scalable Training-Free Diffusion Model for Uncertainty Qua...

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Proceedings of the SC '24 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis

作者： Ali Haisam Muhammad Rafid Junqi Yin Yuwei Geng Siming Liang Feng Bao Lili Ju Guannan Zhang Department of Computer Science Virginia Polytechnic Institute and State University Blacksburg VA USA National Center of Computational Science Oak Ridge National Laboratory Oak Ridge TN USA Department of Mathematics University of South Carolina Columbia SC USA Department of Mathematics Florida State University Tallahassee FL USA Computer Science and Math Division Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (纸本)9798350355543

Generative artificial intelligence extends beyond its success in image/text synthesis, proving itself a powerful uncertainty quantification (UQ) technique through its capability to sample from complex high-dimensional probability distributions. However, existing methods often require a complicated training process, which greatly hinders their applications to real-world UQ problems, especially in dynamic UQ tasks where the target probability distribution evolves rapidly with time. To alleviate this challenge, we have developed a scalable, training-free score-based diffusion model for high-dimensional sampling. We incorporate a parallel-in-time method into our diffusion model to use a large number of GPUs to solve the backward stochastic differential equation and generate new samples of the target distribution. Moreover, we also distribute the computation of the large matrix subtraction used by the training-free score estimator onto multiple GPUs available across all nodes. Compared to existing methods, our approach completely avoids training the score function, making it capable of adapting to rapid changes in the target probability distribution. We showcase the remarkable strong and weak scaling capabilities of the proposed method on the Frontier supercomputer, as well as its uncertainty reduction capability in hurricane predictions when coupled with AI-based foundation models.

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GPT-Based Automated Induction: Vulnerability Detection in Medical Software

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Deng, Liangjun Lei, Hang Khan, Fazlullah Srivastava, Gautam Chen, Jingxue Haque, Mainul University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China University of Nottingham Ningbo China School of Computer Science and the Next-Generation Internet of Everything Laboratory Faculty of Science and Engineering Zhejiang Ningbo315104 China Lovely Professional University Division of Research and Development Phagwara India Chandigarh University University Centre of Research and Development Mohali India Brandon University Department of Math and Computer Science BrandonMBR7A 6A9 Canada China Medical University Research Centre for Interneural Computing Taichung40402 Taiwan Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact & Outcome Punjab Rajpura140401 India University of Nottingham Ningbo China Department of Mathematics Faculty of Science and Engineering Zhejiang Ningbo315104 China

Integrating Natural Language Processing (NLP) with Generative Pre-trained Transformer (GPT) models plays a pivotal role in enhancing the accuracy and efficiency of healthcare software, which is essential for patient safety and providing high-quality care. The precision of healthcare software is fundamental to protecting the well-being of the patient. In addition, it can ensure the delivery of superior care, maintain the integrity of healthcare systems, and promote trust and cost-effectiveness. It is necessary to emphasize the importance of software reliability in its development and deployment. Symbolic execution serves as a vital technology in automated vulnerability detection. However, symbolic execution often faces problems such as path explosion, which seriously affects efficiency. Although there have been several studies to reduce the number of computational paths in symbolic execution, this problem remains a major obstacle. Therefore, more efficient solutions are urgently needed to ensure the software security. This paper proposes a large-scale language model(LLM) induction method mitigating path explosion applied to symbolic execution engines. In contrast to traditional symbolic execution engines, which often result in timeout or out-of-memory detection, our approach achieves the task of detecting vulnerabilities in seconds. Furthermore, our proposal improves the scalability of symbolic execution, allowing more extensive and complex programs to be analyzed without significant increases in computational resources or time. This scalability is crucial to tackling modern software systems and improving the efficiency and effectiveness of automated defect verification in healthcare software. © 2025 IEEE. All rights reserved,

关键词： Scalability

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PBNA: An Improved Probabilistic Biological Network Alignment Method

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Tsinghua science and Technology 2014年第6期19卷 658-667页

作者： Muwei Zhao Wei Zhong Jieyue He School of Computer Science and Engineering and also with MOE Key Laboratory of Computer Network and Information IntegrationSoutheast University Division of Math and Computer Science University of South Carolina Upstate Spartanburg SC 29303USA

Biological network alignment is an important research topic in the field of bioinformatics. Nowadays almost every existing alignment method is designed to solve the deterministic biological network alignment ***, it is worth noting that interactions in biological networks, like many other processes in the biological realm,are probabilistic events. Therefore, more accurate and better results can be obtained if biological networks are characterized by probabilistic graphs. This probabilistic information, however, increases difficulties in analyzing networks and only few methods can handle the probabilistic information. Therefore, in this paper, an improved Probabilistic Biological Network Alignment（PBNA） is proposed. Based on Iso Rank, PBNA is able to use the probabilistic information. Furthermore, PBNA takes advantages of Contributor and Probability Generating Function（PGF） to improve the accuracy of node similarity value and reduce the computational complexity of random variables in similarity matrix. Experimental results on dataset of the Protein-Protein Interaction（PPI） networks provided by Todor demonstrate that PBNA can produce some alignment results that ignored by the deterministic methods, and produce more biologically meaningful alignment results than Iso Rank does in most of the cases based on the Gene Ontology Consistency（GOC） measure. Compared with Prob method, which is designed exactly to solve the probabilistic alignment problem, PBNA can obtain more biologically meaningful mappings in less time.

关键词： probabilistic biological network network alignment protein interaction network

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Qudit Dynamical Decoupling on a Superconducting Quantum Processor

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Physical Review Letters 2025年第5期134卷 050601-050601页

作者： Vinay Tripathi Noah Goss Arian Vezvaee Long B. Nguyen Irfan Siddiqi Daniel A. Lidar Department of Physics and Astronomy University of Southern California Los Angeles California 90089 USA Center for Quantum Information Science and Technology University of Southern California Los Angeles California 90089 USA Quantum Nanoelectronics Laboratory Department of Physics University of California at Berkeley Berkeley California 94720 USA Applied Math and Computational Research Division Lawrence Berkeley National Lab Berkeley California 94720 USA Department of Electrical and Computer Engineering University of Southern California Los Angeles California 90089 USA Department of Chemistry University of Southern California Los Angeles California 90089 USA

Multilevel qudit systems are increasingly being explored as alternatives to traditional qubit systems due to their denser information storage and processing potential. However, qudits are more susceptible to decoherence than qubits due to increased loss channels, noise sensitivity, and crosstalk. To address these challenges, we develop protocols for dynamical decoupling (DD) of qudit systems based on the Heisenberg-Weyl group. We implement and experimentally verify these DD protocols on a superconducting transmon processor that supports qudit operation based on qutrits (d=3) and ququarts (d=4). Specifically, we demonstrate single-qudit DD sequences to decouple qutrits and ququarts from system-bath-induced decoherence. We also introduce two-qudit DD sequences designed to suppress the detrimental cross-Kerr couplings between coupled qudits. This allows us to demonstrate a significant improvement in the fidelity of time-evolved qutrit Bell states. Our results highlight the utility of leveraging DD to enable scalable qudit-based quantum computing.

关键词： Qubits

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The Semantics and Collocations Relation in Food Reviews 34th

The Semantics and Collocations Relation in Food Reviews

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34th International Florida Artificial Intelligence Research Society Conference, FLAIRS-34 2021

作者： Shi, Ledong Bukhari, Syed Ahmad Chan Keshtkar, Fazel Division of Computer Science Math & Science St. John’s University

Finding our favorite dishes have became a hard task since restaurants are providing more choices and varieties. On the other hand, comments and reviews of restaurants are a good place to look for the answer. The purpose of this study is to use computational linguistics and natural language processing to categorise and find semantic relation in various dishes based on reviewers’ comments and menus description. Our goal is to implement a state-of-the-art computational linguistics methods such as, word embedding model, word2vec, topic modeling, PCA, classification algorithm. For visualizations, t-Distributed Stochastic Neighbor Embedding (tSNE) was used to explore the relation within dishes and their reviews. We also aim to extract the common patterns between different dishes among restaurants and reviews comment, and in reverse, explore the dishes with a semantics relations. A dataset of articles related to restaurant and located dishes within articles used to find comment patterns. Then we applied t-SNE visualizations to identify the root of each feature of the dishes. As a result, to find a dish our model is able to assist users by several words of description and their interest. Our dataset contains 1,000 articles from food reviews agency on a variety of dishes from different cultures: American, i.e. ’steak’, hamburger;Chinese, i.e. ’stir fry’, ’dumplings’;Japanese, i.e., ’sushi’. © 2021by the authors. All rights reserved.

关键词： Computational linguistics

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Simulation studies of computation and data scheduling algorithms for data grids

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Journal of Grid Computing 2003年第1期1卷 53-62页

作者： Ranganathan, Kavitha Foster, Ian Department of Computer Science University of Chicago Chicago IL 60637 United States Math. and Computer Science Division Argonne National Laboratory Argonne IL 60439 United States

Data Grids seek to harness geographically distributed resources for large-scale data-intensive problems. Such problems, involving loosely coupled jobs and large data-sets, are found in fields like high-energy physics, astronomy and bioinformatics. A variety of factors need to be considered for effective scheduling of resources in such environments: e.g., resource utilization, response time, global and local allocation policies and scalability. We propose a general and extensible scheduling architecture that addresses these issues. Within this architecture we develop a suite of job scheduling and data replication algorithms that we evaluate using simulations for a wide range of parameters. Our results show that it is important to evaluate the combined effectiveness of replication and scheduling strategies, rather than study them *** specifically, we find that scheduling jobs to locations that contain the data they need and asynchronously replicating popular data-sets to remote sites, works rather well. © 2003 Kluwer Academic Publishers.

关键词： Grid computing

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DESIGNS FROM PAIRS OF FINITE-FIELDS .1. A CYCLIC UNITAL U(6) AND OTHER REGULAR STEINER 2-DESIGNS

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JOURNAL OF COMBINATORIAL THEORY SERIES A 1989年第1期52卷 51-61页

作者： BAGCHI, S BAGCHI, B Computer Science Unit Stat-Math. Division Indian Statistical Institute 203 Barrackpore Trunk Road Calcutta 700 035 India

A general construction for Steiner 2-designs with prime power block size (and with a point-regular automorphism group) is presented. Its success depends on number-theoretic restrictions on the parameters—these are completely analysed in case of block sizes k ⩽ 11. The new designs constructed include infinitely many cyclic Steiner 2-designs with block size 7. Among them is a cyclic unital U (6), that is, an S (2, 6 + 1, 6 3 + 1). It is the first example of a unital with non-prime power parameter and the second example of a cyclic unital.

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The globus extensible input/output system (XIO): A protocol independent IO system for the Grid

The globus extensible input/output system (XIO): A protocol ...

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19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005

作者： Allcock, William Bresnahan, John Kettimuthu, Rajkumar Link, Joseph Math. and Computer Science Division Argonne National Laboratory Argonne IL 60439

ISBN: (纸本)0769523129

In distributed heterogeneous Grid environments the protocols used to exchange bits are crucial. As researchers work hard to discover the best new protocol for the Grid, application developers struggle with ways to use these new protocols. A stable, consistent, and intuitive framework is needed to aid in the implementation and use of these protocols. While the application must not be burdened with the protocol details some of it may need to be exposed to take advantage of potential optimizations. In this paper we examine how the Globus XIO API provides this framework. We will explore the performance implications of using this abstraction layer and the benefits gained in application as well as protocol development.

关键词： Distributed computer systems

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