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International Conference on Computational Engineering, ICCE 2023

作者： Rajan, R. Sundara Kannan, V. Kamala Navaneetan, M. Department of Mathematics Hindustan Institute of Technology and Science Tamil Nadu Chennai India Department of Computer Science and Engineering Hindustan Institute of Technology and Science Tamil Nadu Chennai India

ISBN: (纸本)9783031777639

Embark on a journey into the neural landscape where fires ignite, spread, and reveal the secrets of connectivity. This groundbreaking exploration introduces "NeuroBurning," a novel approach that computes the burning number for Harary graphs, unraveling the minimum activation needed to set the entire neural network ablaze. From controlling disease spread to optimizing brain stimulation, this study delves into the computation of the burning number and its captivating applications in understanding the intricate web of connections within the brain. In this study, we have calculated the burning number for Harary graphs and explored the dynamics of neural connectivity by examining this concept within the framework of Harary graphs. Additionally, we have determined the burning number for pencil graphs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Graph neural networks

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Towards new realities: Implications of personalized online layers in our daily lives

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i-com 2024年第2期23卷 221-229页

作者： Herder, Eelco Stojko, Laura Strecker, Jannis Neumayr, Thomas Yigitbas, Enes Augstein, Mirjam Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Department of Computer Science University of the Bundeswehr Munich Neubiberg Germany Institute of Computer Science University of St. Gallen St. Gallen Switzerland Research Group Personalized Environments and Collaborative Systems University of Applied Sciences Upper Austria Hagenberg Austria Faculty of Electrical Engineering Computer Science and Mathematics Paderborn University Paderborn Germany

We are currently in a period of upheaval, as many new technologies are emerging that open up new possibilities to shape our everyday lives. Particularly, within the field of Personalized Human-computer Interaction we observe high potential, but also challenges. In this article, we explore how an increasing amount of online services and tools not only further facilitates our lives, but also shapes our lives and how we perceive our environments. For this purpose, we adopt the metaphor of personalized 'online layers' and show how these layers are and will be interwoven with the lives that we live in the 'human layer' of the real world. © 2024 the author(s), published by De Gruyter, Berlin/Boston.

关键词： Human computer interaction

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On the Attractive and Repulsive Forces of Generalized Stochastic Neighbor Embedding With Alpha-Divergence

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IEEE Access 2024年 12卷 90380-90394页

作者： Lin, Hsin-Yi Tseng, Huan-Hsin Chien, Jen-Tzung Seton Hall University Department Of Mathematics And Computer Science South OrangeNJ07079 United States Brookhaven National Laboratory Computational Science Initiative UptonNY11973 United States Institute Of Electrical And Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan

Stochastic neighbor embedding (SNE) performs nonlinear transformation from high-dimensional observation space to low-dimensional latent space which preserves neighbor affinities. Data pairs in latent space tend to be crowded due to the dimensionality reduction. To mitigate the crowding problem, certain characteristics are favorable in the design of the SNE setting. This study presents a fundamental analysis of SNE that not only generalizes the previous SNEs but also provides a systematic way to understand the intrinsic properties. From the perspective of theoretical connection, we are able to conceive a new generalized SNE (g-SNE) by introducing a regularized power-law distribution with the α-divergence for manifold learning. The proposed method generalizes and incorporates various favorable features for the clustering process. In addition, the proposed method provides high flexibility, admitting tailored realizations to properly reflect the similarity between original and dimension-reduced samples. Experiments are performed to analyze the proposed method, and its effectiveness is demonstrated with several learning tasks. © 2024 The Authors.

关键词： Data visualization

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Hybrid QKD-based framework for secure enterprise communication system

Hybrid QKD-based framework for secure enterprise communicati...

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2023 International Conference on ENTERprise Information Systems, CENTERIS 2023 - International Conference on Project MANagement, ProjMAN 2023 - International Conference on Health and Social Care Information Systems and Technologies, HCist 2023

作者： Rencis, Edgars Viksna, Juris Kozlovics, Sergejs Celms, Edgars Larins, Davis Janis Petrucena, Krisjanis Institute of Mathematics and Computer Science University of Latvia Raina blvd. 29 RigaLV-1459 Latvia

This research paper proposes a hybrid quantum key distribution (QKD)-based framework for secure enterprise communication using post-quantum cryptography (PQC) and smart cards. The paper discusses the limitations of current PQC implementations and the need for a hybrid approach that combines classical non-PQC algorithms with quantum-resistant PQC algorithms to establish secure communication channels. The proposed framework utilizes point-to-point QKD links between quantum devices to establish a shared secret key, which is then used to encrypt and decrypt data using PQC algorithms. Smart cards are used for authentication and key synchronization to ensure the security of end-user devices. The paper also reviews relevant literature on QKD and PQC and discusses future work. The proposed framework offers a cost-effective and secure way for enterprises to communicate with each other. © 2024 The Author(s).

关键词： Quantum cryptography

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The Role of Syntactic Span Preferences in Post-Hoc Explanation Disagreement 30

The Role of Syntactic Span Preferences in Post-Hoc Explanati...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Kamp, Jonathan Beinborn, Lisa Fokkens, Antske Computational Linguistics and Text Mining Lab Vrije Universiteit Amsterdam Netherlands Institute of Computer Science Campus Institute Data Science University of Göttingen Germany Dept. of Mathematics and Computer Science Eindhoven University of Technology Netherlands

ISBN: (纸本)9782493814104

Post-hoc explanation methods are an important tool for increasing model transparency for users. Unfortunately, the currently used methods for attributing token importance often yield diverging patterns. In this work, we study potential sources of disagreement across methods from a linguistic perspective. We find that different methods systematically select different classes of words and that methods that agree most with other methods and with humans display similar linguistic preferences. Token-level differences between methods are smoothed out if we compare them on the syntactic span level. We also find higher agreement across methods by estimating the most important spans dynamically instead of relying on a fixed subset of size k. We systematically investigate the interaction between k and spans and propose an improved configuration for selecting important tokens. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Syntactics

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Evaluating Open-Source LLMs in Low-Resource Languages: Insights from Latvian High School Exams 4

Evaluating Open-Source LLMs in Low-Resource Languages: Insig...

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4th International Conference on Natural Language Processing for Digital Humanities, NLP4DH 2024

作者： Dargis, Roberts Barzdinš, Guntis Skadina, Inguna Gruzi¯tis, Normunds Sauli¯te, Baiba Institute of Mathematics and Computer Science University of Latvia Raina bulv.29 RigaLV-1459 Latvia

ISBN: (纸本)9798891761810

The latest large language models (LLM) have significantly advanced natural language processing (NLP) capabilities across various ***, their performance in low-resource languages, such as Latvian with 1.5 million native speakers, remains substantially underexplored due to both limited training data and the absence of comprehensive evaluation *** study addresses this gap by conducting a systematic assessment of prominent open-source LLMs on natural language understanding (NLU) and natural language generation (NLG) tasks in *** utilize standardized high school centralized graduation exams as a benchmark dataset, offering relatable and diverse evaluation scenarios that encompass multiple-choice questions and complex text analysis *** experimental setup involves testing models from the leading LLM families, including Llama, Qwen, Gemma, and Mistral, with OpenAI's GPT-4 serving as a performance *** results reveal that certain open-source models demonstrate competitive performance in NLU tasks, narrowing the gap with ***, all models exhibit notable deficiencies in NLG tasks, specifically in generating coherent and contextually appropriate text analyses, highlighting persistent challenges in NLG for low-resource *** findings contribute to efforts to develop robust multilingual benchmarks and to improve LLM performance in diverse linguistic contexts. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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A Novel Algorithm of Priority Selection Strategies for the United Nations Sustainable Development Goals Based on Relationship Network 3

A Novel Algorithm of Priority Selection Strategies for the U...

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3rd International Conference on Advanced Algorithms and Neural Networks, AANN 2023

作者： Luo, Jia'an Shen, Sitian Ma, Zi'ao Wang, Hongzhou School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Computer Mathematics and Statistics Beijing Institute of Technology Beijing China

ISBN: (纸本)9781510668355

The 17 Sustainable Development Goals (SDGs) proposed by the UN are not independent of each other. In this article, we analyze the reciprocal influence of 17 SDGs, on the basis of which we propose Network-based Priority Selection Algorithm (NPSA), in which static and dynamic networks are constructed. The static network is established to describe the fundamental interaction between 17 SDGs by using Cross-impact Matrix for Targets. Fiscal expenditure, main driving force of the development of 17 SDGs, is mainly invested in ten fields. So we set up a Field-Goal Map by counting the number of targets they include in common. Then we establish four priority selection indicators, including centrality, system impact, urgency and development-based modification. According to the various developing level of different countries, we assign personalized weight vectors for them to synthesize the influence of the four indicators using the Entropy Weight Method. Then we get priority score of each goal and its rank for each year. We quantitatively simulate system dynamics to implement scenario analysis on a ten-year horizon. Once a year, we re-rank the priority of 17 SDGs and then use conservative, steady, or aggressive strategies to allocate financial expenditure. Considering the delay effect between investment and reward, we propose Delay-based Breadth-First Search Algorithm (D-BFS) to update our network, broadcasting the influence of one goal to another once a month. Logistic curve in is used to simulate the S-shaped curve change of the degree of mutual influence between goals. We use the dynamic model to give guidance on financial investment for each goal in the next ten years. Moreover, facing global field mutation and crisis, the development strategy calculated by our model has excellent stability. The code is released at https://***/GoodMorningPeter/NPSA. © 2023 SPIE.

关键词： Sustainable development

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Analytical study of atmospheric internal waves model with fractional approach

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Journal of Ocean Engineering and science 2024年第4期9卷 326-337页

作者： Trushit Patel Hardik Patel Ramakanta Meher Computer Science University of the PeoplePasadenaCA 91101United States Department of Mathematics Uka Tarsadia UniversityBardoliGujaratIndia Mathematics and Humanities Department Sardar Vallabhbhai National Institute of TechnologySuratGujaratIndia

This study looks at the mathematical model of internal atmospheric waves,often known as gravity waves,occurring inside a fluid rather than on the *** the shallow-fluid assumption,internal atmospheric waves may be described by a nonlinear partial differential equation *** shallow flow model’s primary concept is that the waves are spread out across a large horizontal area before rising *** Fractional Reduced Differential Transform Method(FRDTM)is applied to provide approximate solutions for any given *** aids in the modelling of the global atmosphere,which has applications in weather and climate *** the integer-order value(α=1),the FRDTM solution is compared to the precise solution,EADM,and HAM to assess the correctness and efficacy of the proposed technique.

关键词： Shallow-fluid equations Atmospheric internal waves Time-fractional partial differential equations Fractional reduced differential transform method(FRDTM) Climate prediction

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Enhancing Urban Air Quality with Smart Vehicle Exhaust Management

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Operations Research Forum 2025年第2期6卷 1-24页

作者： Tyagi, Vaishali Dubey, Roshan Singh, Suraj Ram, Mangey Department of Applied Sciences & Humanities ABES Institute of Technology Uttar Pradesh Ghaziabad India Department of Computer Science & Engineering ABES Institute of Technology Uttar Pradesh Ghaziabad India Department of Mathematics Computer Science and Engineering Graphic Era Deemed to be University Uttarakhand Dehradun India

Air pollution is the contamination of the indoor or outdoor environment by any chemical, physical, or biological agent that modifies the natural characteristics of the atmosphere. Burning gasoline and diesel fuel creates harmful byproducts like nitrogen dioxide, carbon monoxide, hydrocarbons, benzene, and formaldehyde. This study proposes a sensor-based model to control vehicular pollution by monitoring emission levels and preventing vehicles from operating if their pollution exceeds government standards. The proposed model consists of a smoke sensor, particulate sensors, carbon monoxide sensors, along with Arduino based microcontroller, data logger, LCD display, and GPRS modem. Using the block diagram, a mathematical model has been developed and some differential equations by using Markov process have been generated. This Markov-based model gives the information about the failure causes and working of the proposed system. Some reliability matrices like availability, mean time between failure (MTBF), and sensitivity analysis have been evaluated with the help of Laplace transform and illustrated with the help of graphs. Also, the failure cases of the system and its cost analysis have been done along with all the numerical calculations required for the successful operation of the model. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Air pollution Cost analysis Failure cases Markov process Reliability Sensor system

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SSD-MIR: Towards Medical Image Restoration With Structured Visual State Space Duality

SSD-MIR: Towards Medical Image Restoration With Structured V...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Chen, Binghong Zhang, Zhengqian Wang, Haiyu Yu, Tianshuo Wang, Dong Wang, Jialiang Ren, Junjun Liu, Yongzhuang Jiang, Wei Harbin Institute of Technology School of Mathematics School of Computer Science and Technology Harbin China Harbin Institute of Technology Department of Fundamental Education Harbin China University of Glasgow James Watt School of Engineering Glasgow United Kingdom Harbin Institute of Technology School of Computer Science and Technology Harbin China Harbin Institute of Technology School of Computer Science and Technology School of Mathematics Harbin China

ISBN: (纸本)9798350386226

In the field of Medical image processing, Transformers and CNNs bring filter-based local sensing and attention-based global modelling, which strengthened their dominant position. However, the scales required in different applications vary, and improper usage or selection on models can lead to performance decrease, resulting in more serious consequences in downstream tasks. The recent advanced Structured State Space Model has shown its potential as a baseline model, and is further proved to maintaining implicit duality with the attention mechanism, The corresponding model Mamba2 shows its long-range modelling ability with optimized long-term memory and linear computational *** this paper, we propose SSD-MIR, a novel architecture leveraging the advantages of state space duality mechanism. SSD-MIR includes three parts: input projection and feature representation, deep feature transformation, output projection and feature inversion. With the three components sequentially connected to form our model, it is able to model long-range dependencies and learn the mapping between low-quality input and high-quality output simultaneously. In the main deep feature transformation part, depthwise convolution is used for additional feature mapping as an alternative of 1D causal convolution, and an optimized quad-direction scanning mechanism is implemented to form the overall 2D state space dual module. The corresponding wrapper module is built in MetaFormer style with the usage of residual connection and LayerNorm. We perform extensive experiments on multiple medical image restoration tasks, and the results are superior to the state-of-the-arts, demonstrating the strength and efficacy of our model. © 2024 IEEE.

关键词： Mapping

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