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Cybernetics and Innovations (ICCI), International Conference on

作者： Nutcha Srilachai Pranodnard Viboonsang Somkiat Kosolsombat Data Science and Innovation Program College of Interdisciplinary Studies Thammasat University Pathum Thani Thailand

ISBN: (数字)9798331533267

ISBN: (纸本)9798331533274

Phishing attacks are an emerging cyber threat that makes use of fake URLs to pilfer sensitive information of users, such as their login credentials and other financial details. In line with this, the present study involves the adoption of NLP methods with machine-learning algorithms in effectively detecting phishing URLs. To this end, five different algorithms are considered for effectiveness in the study: LSTM, GRU, Random Forest, Support Vector Machine, and Logistic Regression. Each of them was trained and then tested with a complete dataset, containing phishing and legitimate URLs for correctness in distinguishing malicious URLs from the benign ones. Amongst them, the LSTM model recorded an accuracy as high as 98% due to its capability for handling sequential dependencies in addition to contextual patterns within the URLs. This research underlines the promise of LSTM-based models in fighting phishing threats and further proposes a scalable solution to enable real-time phishing URL detection and enhance cybersecurity defense.

关键词： Uniform resource locators Deep learning Support vector machines Logistic regression Accuracy Phishing Computational modeling Real-time systems Long short term memory Random forests

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Interference-Based Reliability and Capacity Analysis for IEEE 802.11 Broadcast Ad-Hoc Networks on the Highway 11

Interference-Based Reliability and Capacity Analysis for IEE...

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11th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2025

作者： Li, Zhijuan Wu, Xintong Li, Xiaokun Ma, Xiaomin Department of Computer and Big Data Heilongjiang University Harbin150080 China Postdoctoral Program of Heilongjiang Hengxun Technology Co. Ltd. Harbin150090 China School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China College of Science and Engineering Oral Roberts University TulsaOK74171 United States

ISBN: (纸本)9789897587450

Interference is a critical factor that degrades wireless network performance. In IEEE 802.11 wireless broadcast networks, hidden terminals and concurrent transmissions are the primary sources of interference due to the carrier sense multiple access (CSMA) mechanism. Therefore, analyzing the signal-to-interference-plus-noise ratio (SINR) distribution is essential for evaluating network performance, whose derivation relates to the transmission probabilities of hidden terminals and concurrent transmissions. In this study, we utilize the existing semi-markov process (SMP) model to calculate these transmission probabilities. Subsequently, we employ the Laplace transform to analyze the SINR distribution in IEEE 802.11 broadcast ad-hoc networks on highways. Based on the derived SINR distribution, we further evaluate the reliability and capacity. This approach can be readily extended to two-dimensional (2D) or three-dimensional (3D) scenarios by employing d-dimensional (1 ≤ d ≤ 3, dD) point process. Experimental results demonstrate that the proposed model achieves high accuracy under small to medium interference ranges. Additionally, the analysis remains highly accurate for receivers within 70 meters, even in scenarios with large interference ranges. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Markov processes

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Carbon-modified zeolite derivates based filler in mixed matrix membrane adsorbers (MMMAs) for enhancing urea and creatinine removal from hemodialysis spent dialysate

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Journal of Industrial and Engineering Chemistry 2025年 147卷 584-597页

作者： Widiastuti, Nurul Rahman, Reca Ardiyanti Cipta Dharma, Hadi Nugraha Widyanto, Alvin Rahmad Nareswari, Cininta Kayadoe, Victor Raharjo, Yanuardi Saiful Nomura, Mikihiro Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Keputih-Sukolilo Jl. Arif Rahman Hakim Surabaya60111 Indonesia Advanced Nanolithography Lab Department of System Semiconductor Science Dongguk University 30 Pildong-ro 1-gil Jung-gu Seoul04620 Korea Republic of Department of Applied Chemistry Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135-8548 Japan Chemical Education Study Program Faculty of Teaching and Education Sciences University of Pattimura Ambon97233 Indonesia Chemistry Department Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia Chemistry Department Faculty of Mathematics and Natural Science Universitas Syiah Kuala Banda Aceh Indonesia

Conventional dialysate recycling methods struggle to effectively remove creatinine, urea, and other minor contaminants. This study explores mixed matrix membrane adsorbers (MMMAs) as a novel approach to address these challenges. MMMAs, which integrate adsorbents into filtration membranes, function as both filters and impurity scavengers. Zeolite carbon composite (ZCC) and zeolite-templated carbon (ZTC) were incorporated into MMMAs using the non-solvent induced phase separation (NIPS) technique. Characterization by SEM and XRD confirmed the successful synthesis of ZCC and ZTC, retaining the zeolite-Y structure and amorphous nature, with notable differences in particle sizes (680 and 379 nm) and crystallite sizes (0.45 and 0.02 nm). FTIR revealed hydrogen bonding interactions between ZCC and PVP, absent in ZTC. SEM and AFM analyses of the membranes indicated increased hydrophilicity and porosity with ZCC, while ZTC reduced surface roughness. MMMAs significantly outperformed pristine membranes in removing urea and creatinine. The PPK-0.2 membrane achieved superior rejection rates (93.05 % for urea and 98.95 % for creatinine), attributed to microporous entrapment of ZTC and polymer matrix adsorption. In contrast, PPZ-0.2 showed lower rejection rates (84.24 % for urea and 85.79 % for creatinine), relying solely on physical adsorption. These findings highlight MMMAs, especially ZTC-based ones, as promising candidates for enhancing dialysate reuse efficiency. © 2024 The Korean Society of Industrial and Engineering Chemistry

关键词： Hydrogen bonds

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Psoriasis: Perspectives from Irwin M. Braverman, MD

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Clinics in Dermatology 2025年第2期43卷 166-169页

作者： Cohen, Jeffrey M. Bunick, Christopher G. Department of Dermatology Yale School of Medicine New Haven CT United States Department of Biomedical Informatics and Data Science Yale School of Medicine New Haven CT United States Program in Translational Biomedicine Yale University New Haven CT United States

Dr Irwin M. Braverman is recognized as an expert on many skin diseases, including psoriasis, an immune-mediated disorder that presents with scaly erythematous plaques. The most common clinical subtype is plaque psoriasis, with scalp, inverse, guttate, pustular, and nail psoriasis representing additional subtypes. Psoriasis has been associated with several comorbidities, particularly psoriatic arthritis, which affects up to 30% of those with psoriasis. Psoriasis can have an enormous impact on patients, and Dr Braverman reflects that “it is hard to think of another disease that can be so destructive or impactful.” Over the course of his career, Dr Braverman treated many patients with psoriasis and observed several significant therapeutic advances, including the widespread use of psoralens with UV-A phototherapy and the introduction of methotrexate. He also contributed to research on the pathophysiology of psoriasis, studying the hallmark dilated capillary loops. Dr Braverman ultimately believes that “taking care of a patient with psoriasis goes into the making of a dermatologist.” © 2024 Elsevier Inc.

关键词： Goeckerman regimen blood vessels electron microscopy methotrexate phototherapy psoriasis

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AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting

arXiv

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arXiv 2025年

作者： Benechehab, Abdelhakim Feofanov, Vasilii Paolo, Giuseppe Thomas, Albert Filippone, Maurizio Kégl, Balázs Huawei Noah’s Ark Lab Paris France Department of Data Science EURECOM Statistics Program KAUST Saudi Arabia

Pre-trained foundation models (FMs) have shown exceptional performance in univariate time series forecasting tasks. However, several practical challenges persist, including managing intricate dependencies among features and quantifying uncertainty in predictions. This study aims to tackle these critical limitations by introducing adapters—feature-space transformations that facilitate the effective use of pre-trained univariate time series FMs for multivariate tasks. Adapters operate by projecting multivariate inputs into a suitable latent space and applying the FM independently to each dimension. Inspired by the literature on representation learning and partially stochastic Bayesian neural networks, we present a range of adapters and optimization/inference strategies. Experiments conducted on both synthetic and real-world datasets confirm the efficacy of adapters, demonstrating substantial enhancements in forecasting accuracy and uncertainty quantification compared to baseline methods. Our framework, AdaPTS, positions adapters as a modular, scalable, and effective solution for leveraging time series FMs in multivariate contexts, thereby promoting their wider adoption in real-world applications. We release the code at https://***/abenechehab/AdaPTS. © 2025, CC BY.

关键词： Stochastic systems

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Structural study of CaO-based materials with ZrO2 incorporation using in-situ synchrotron radiation X-ray diffraction and X-ray absorption spectroscopy

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Ceramics International 2025年

作者： Munawaroh, Fatimatul Masdya, Yoga Saiyasombat, Chatree Baqiya, Malik A. Triwikantoro Physics Department Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Natural Science Education Study Program Universitas Trunojoyo Madura Bangkalan69162 Indonesia Nakhon Ratchasima30000 Thailand

Pure CaO powder (CZ0) and CaO incorporated with 10 wt% ZrO2 (CZ10) have been successfully synthesized from natural limestone using the sol-gel and wet-mixing methods, respectively. Phase and structural stability were examined using in-situ Synchrotron Radiation-XRD, X-ray Absorption Near Edge Structure (XANES), and Extended X-ray Absorption Fine Structure (EXAFS) analyses. The result indicates that the calcium (Ca) atom is slightly distorted by ZrO2 incorporation, and ZrO2 increases the Ca-O bond distance (2.4014 Å) in the CaO-ZrO2. Carbonation experiments demonstrate that CZ10 achieves a higher formation of CaCO3 (⁓81.63 ± 1.99 wt%) compared to CZ0 (⁓64.50 ± 1.46 wt%). The carbonation process results in Ca-O bond elongation to 2.4142 Å, indicating transition to carbonate phases and an altered calcium electronic environment. No significant reduction in the Ca-O bond length (2.3977 Å) occurs after decarbonization, suggesting that the removal of CaCO3 from the CaO structure can be stabilized by Zr incorporation. Therefore, this material holds great potential for application in CO2 capture. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： X ray absorption near edge structure spectroscopy

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A Sequential Perturbation Framework for Solving Laplacian Systems

A Sequential Perturbation Framework for Solving Laplacian Sy...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Tse-Yu Lin Yen-Lung Tsai Data Science Degree Program National Taiwan University Taipei Taiwan Department of Mathematical Sciences National Chengchi University Taipei Taiwan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

In this paper, we investigate the iterative solution of a sequence of graph Laplacian systems by leveraging the (relative) continuity of the generalized inverse operator. Our primary objective is to extend traditional matrix perturbation techniques specifically to the context of graph Laplacian systems. We achieve this by modeling the evolution of these systems starting from a given initial graph Laplacian and applying a series of systematic updates. We propose a novel framework that formulates an iterative method for solving the targeted graph Laplacian system based on the solutions of simpler, earlier Laplacian systems. By establishing a relationship between the solutions of two Laplacian systems, we derive a recursive formula that enables efficient computation of the updated solutions. This approach not only enhances computational efficiency but also maintains accuracy, as it utilizes the inherent structure of the graph Laplacian, including its positive semi-definiteness and the zero-mean condition of the right-hand side.

关键词： Electric potential Laplace equations Systematics Accuracy Perturbation methods Computational efficiency Iterative methods Consumer electronics

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A machine learning and neural network approach for classifying multidrug-resistant bacterial infections

Healthcare Analytics

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Healthcare Analytics 2025年 7卷 100388-100388页

作者： Mengsiri, Preeda Ungcharoen, Ratchadaporn Gertphol, Sethavidh Biomedical Data Science Program Faculty of Science Kasetsart University Thailand Faculty of Public Health Kasetsart University Chalermphrakiat Sakon Nakhon Province Campus Thailand Department of Computer Science Faculty of Science Kasetsart University Thailand

Antimicrobial resistance (AMR) represents a major public health challenge, significantly complicating infection prevention and treatment. This study employs machine learning and neural network techniques to classify multidrug-resistant Gram-negative bacterial (MDR-GNB) infections using electronic health records from 624 patients at Thatphanom Crown Prince Hospital in Thailand. We compared several algorithms, including Logistic Regression, Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), K-Nearest Neighbors (KNN), Multilayer Perceptron (MLP), and Light Gradient Boosting Machine (LightGBM), with the MLP model exhibiting the highest accuracy and specificity. Performance was further enhanced by integrating feature selection methods such as Sequential Forward Selection (SFS), Recursive Feature Elimination with Cross-Validation (RFE-CV), and SelectKBest with data augmentation techniques, including ADASYN and SMOTE variants. Utilizing SHapley Additive exPlanations (SHAP) provided valuable insights into the most influential predictors for MDR-GNB. Notably, the MLP model achieved an AUC of 0.70, surpassing prior studies and highlighting its potential to advance clinical decision-making in managing MDR-GNB infections. © 2025 The Authors

关键词： Electronic health records Gram-negative bacteria Machine learning Multidrug resistance Neural network

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Mapping the Scientific Landscape of Integrated Scheduling Towards Industry 5.0 with A Bibliometric Analysis

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Procedia Computer science 2025年 253卷 84-93页

作者： Anak Agung Ayu Putri Ardyanti Zhiqiang Xie Andrea Stevens Karnyoto Bens Pardamean Ni Made Estiyanti School of Computer Science and Technology Harbin University of Science and Technology Harbin 150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Doctoral School of Management and Business University of Debrecen Debrecen Hungary

The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously. This bibliometric analysis provides a comprehensive understanding of the diverse research perspectives on the potential challenges of integrated scheduling within the framework. We identified 357 Scopus articles and analysed co-occurrence keyword (CNK) by VOSViewer tools and Global Citation Score (GCS) by Scopus tools. The research data obtained from 1993 to 2023 mainly in the subject areas of Engineering, Computer science, Maths, and others. CNK identified six cluster keywords, and nine most cited articles based on normalised GCS. These results contribute to our understanding of the development of scheduling algorithms, shifting from an emphasis on manufacturing transfers to contemporary demand-centric research directions. Furthermore, this research provides a valuable perspective for policymakers, plant personnel, and manufacturing managers to make informed decisions.

关键词： integrated scheduling assembly job shop scheduling heuristic algorithm genetic algorithm bibliometric analysis

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Lung Cancer Diagnosis Based on Object Detection Technology 14th

Lung Cancer Diagnosis Based on Object Detection Technology

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14th International Conference on Frontier Computing, FC 2024

作者： Xu, Jia-Lang Wang, Pei-Yun Huang, Tzu-Hsuan Hsu, Ying-Lin Huang, Kuo-Yang Chen, Mu-Yen Artificial Intelligence Development Center Changhua Christian Hospital Changhua Taiwan Doctoral Program in Data Science and Industrial Analytics National Chung Hsing University Taichung Taiwan Department of Applied Mathematics and Institute of Statistics National Chung Hsing University Taichung Taiwan Division of Chest Medicine Department of Internal Medicine Changhua Christian Hospital Changhua Taiwan Department of Engineering Science National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9789819623945

With the rise of artificial intelligence, many people nowadays use artificial intelligence to help solve some problems in life, and the medical field is also with the rise of artificial intelligence, many people are slowly applying artificial intelligence to medical images to assist in decision-making, this study proposes a Yolov8 algorithm for object tracking of CT images of lung cancer, which can quickly tell the doctor where the cancer is and what the type of cancer is. The results of this study show that the Box_Loss, Cls_Loss, and Dfl_loss of the Yolov8 algorithm in detecting the location of lung cancer are 1.3689, 0.4552, and 1.5569 in the validation data, respectively, and thus this study suggests that this method can help physicians know the location of the tumor and what kind of tumor it belongs to. Therefore, this study suggests that this method can help physicians know the location of the tumor and the type of tumor. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lung cancer

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