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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Chen, Siyang Wu, Lianlian Xu, Yong Liu, Kunhong He, Song Bo, Xiaochen Xiamen University School of Informatics Xiamen China Tianjin University Academy of Medical Engineering and Translational Medicine Tianjin China Fujian University of Technology School of Computer Science and Mathematics Fuzhou China Xiamen University School of Film Department of Digital Media Technology Xiamen China Institute of Health Service and Transfusion Medicine Department of Bioinformatics Beijing China

ISBN: (纸本)9798350337488

The interpretable machine learning method is important in drug discovery. Unlike traditional ensemble learning methods, this paper proposes an interpretable algorithm based on Bayesian rule extraction to obtain reliable and explainable results for hepatotoxicity prediction. To extract information from different types of omics data, our algorithm employs a multi-view learning strategy to enhance performance. Specifically, a random forest is trained in each view, and then the Bayesian rule extraction algorithm is designed to select an optimal rule subset, controlling the size and accuracy of the ruleset through probabilities. These rule sets are integrated through multi-view voting to get the final decisions. The performance of our algorithm is tested on the hepatotoxicity dataset, demonstrating that compared to traditional machine learning algorithms and rule-based algorithms, our approach maintains excellent performance while achieving high interpretability in most cases. Our python source code and the related Supplementary Materials are available at: ***/MLDMXM2017/MV-BRS. © 2023 IEEE.

关键词： Bayesian Ruleset Hepatotoxicity Prediction Interpretable Machine Learning Multi-view Learning

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Mining Intelligence Hierarchical Feature for Malware Detection 15th

Mining Intelligence Hierarchical Feature for Malware Detecti...

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15th International Conference on Intelligent Computing and Networking, IC-ICN 2024

作者： Davuluri, Sandeep Kumar Soni, Mukesh ALMahadin, Ghayth Rivera, Richard Upadhyay, Jinal Patel, Pavan Department of Information Technology University of the Cumberlands Williamsburg United States Dr. D. Y. Patil Vidyapeeth Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Faculty of Information Technology Al Ahliyya Amman University Amman Jordan Department of Informatics and Computer Science Escuela Politécnica Nacional Quito Ecuador HasmukhGoswami College of Engineering Gujarat Vahelal India Ahmedabad Institute of Technology Gujarat Ahmedabad India

ISBN: (纸本)9789819786305

In recent years, a new strain of malware, known as mining malware, has emerged, resulting in significant losses for its victims due to its encryption techniques. This research proposes an innovative approach to detect mining malware by integrating hierarchical threat intelligence features, focusing on the static attributes of mining malware. From the perspective of mining malware threat intelligence, we train classifiers using distinct layers of features, including byte-level features, Portable Executable (PE) structure features, and mining operation execution features. By leveraging diverse malicious software attributes for detection preferences, we develop a comprehensive mining malware detector based on a hierarchical feature integration methodology. To evaluate our approach, we conducted experiments in both controlled lab settings and real-world datasets. The results indicate that our hierarchical feature-integrated mining malware detection method achieves an impressive accuracy rate of 97.01% on the simulated real-world dataset, demonstrating a substantial 6.13% accuracy improvement compared to the baseline mining malware detection method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Instrument-tissue Interaction Detection Framework for Surgical Video Understanding

arXiv

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arXiv 2024年

作者： Lin, Wenjun Hu, Yan Fu, Huazhu Yang, Mingming Chng, Chin-Boon Kawasaki, Ryo Chui, Cheekong Liu, Jiang The Department of Mechanical Engineering National University of Singapore Singapore The Research Institute of Trustworthy Autonomous Systems The Department of Computer Science and Engineering Southern University of Science and Technology China The Agency for Science Technology and Research Singapore The Department of Informatics Osaka University Graduate School of Medicine Japan The Department of Ophthalmology Shenzhen Peoples Hospital China

Instrument-tissue interaction detection task, which helps understand surgical activities, is vital for constructing computer-assisted surgery systems but with many challenges. Firstly, most models represent instrument-tissue interaction in a coarse-grained way which only focuses on classification and lacks the ability to automatically detect instruments and tissues. Secondly, existing works do not fully consider relations between intra- and inter-frame of instruments and tissues. In the paper, we propose to represent instrument-tissue interaction as 〈instrument class, instrument bounding box, tissue class, tissue bounding box, action class〉 quintuple and present an Instrument-Tissue Interaction Detection Network (ITIDNet) to detect the quintuple for surgery videos understanding. Specifically, we propose a Snippet Consecutive Feature (SCF) Layer to enhance features by modeling relationships of proposals in the current frame using global context information in the video snippet. We also propose a Spatial Corresponding Attention (SCA) Layer to incorporate features of proposals between adjacent frames through spatial encoding. To reason relationships between instruments and tissues, a Temporal Graph (TG) Layer is proposed with intra-frame connections to exploit relationships between instruments and tissues in the same frame and inter-frame connections to model the temporal information for the same instance. For evaluation, we build a cataract surgery video (PhacoQ) dataset and a cholecystectomy surgery video (CholecQ) dataset. Experimental results demonstrate the promising performance of our model, which outperforms other state-of-the-art models on both datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Tissue

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AlGaAs soliton microcombs at room temperature

AlGaAs soliton microcombs at room temperature

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Wu, Lue Xie, Weiqiang Xiang, Chao Chang, Lin Yu, Yan Chen, Hao-Jing Yamamoto, Yoshihisa Bowers, John E. Vahala, Kerry J. Suh, Myoung-Gyun T. J. Watson Laboratory of Applied Physics California Institute of Technology PasadenaCA91125 United States Department of Electrical and Computer Engineering University of California Santa Barbara Santa BarbaraCA93106 United States Physics & Informatics Laboratories NTT Research Inc. SunnyvaleCA94085 United States

Soliton generation in AlGaAs microresonators at room temperation is reported for the first time. The destabilizing thermo-optic effect is shown to instead provide stability for high soliton repetition rates. The optic... 详细信息

ISBN: (纸本)9781957171258

关键词： Aluminum gallium arsenide

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Analysis of a Data Set to Determine the Dependence of Airline Passenger Satisfaction 7th

Analysis of a Data Set to Determine the Dependence of Airlin...

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7th Computational Methods in Systems and Software, CoMeSySo 2023

作者： Tynchenko, V.S. Borodulin Kleshko, I.I. Nelyub, V.A. Rukosueva Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow105005 Russia Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russia Department of Information Economic System Institute of Engineering and Economics Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Systems Analysis and Operations Research Institute of Informatics and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Information-Control Systems Department Institute of Computer Science and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Technological Machines and Equipment of Oil and Gas Complex School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk660041 Russia

ISBN: (纸本)9783031535512

This paper presents an analysis of a data set to determine the factors influencing airline passenger satisfaction. The study examines various criteria such as gender, customer type, age, travel type, class, and range to assess their impact on passenger satisfaction. The dataset consists of 25 columns, including attributes like Wi-Fi availability, convenience of online booking, seat comfort, in-flight entertainment, baggage handling, and overall satisfaction. The sample is relatively balanced, with equal representation of men and women, predominantly repeat customers, and a majority flying for business purposes. Key findings include a strong correlation between departure and arrival delays, higher satisfaction among passengers in business class, and positive ratings for Wi-Fi service correlating with overall satisfaction. Correlation analysis reveals interdependencies between different attributes, such as the influence of cleanliness on seat comfort and food and beverage ratings. In addition, a neural network forecasting model is used to estimate the average ratings of passengers, although with low accuracy, which was later excluded. Finally, a decision tree algorithm is utilized to identify the most significant attributes affecting passenger satisfaction words. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Baggage handling

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Correlation Analysis and Predictive Factors for Building a Mathematical Model 1

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7th Computational Methods in Systems and Software, CoMeSySo 2023

作者： Nelyub, V.A. Tynchenko, V.S. Gantimurov, A.P. Degtyareva, K.V. Kukartseva, O.I. Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow105005 Russia Peter the Great St. Petersburg Polytechnic University Saint Petersburg Russia Information-Control Systems Department Institute of Computer Science and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Technological Machines and Equipment of Oil and Gas Complex School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk660041 Russia Department of Information Economic System Institute of Engineering and Economics Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia Department of Systems Analysis and Operations Research Institute of Informatics and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk660037 Russia

ISBN: (数字)9783031535499

ISBN: (纸本)9783031535482

The study, published in the journal Nature Medicine, looked at data on 1,000 people from China who were tracked over an average period of six years. The participants were divided into two groups: those who lived in areas with high levels of air pollution and those who lived in areas with low levels of air pollution. The study analyzed data on patients with lung cancer, including their age, gender, exposure to air pollution, alcohol consumption, dust allergy, occupational hazards, genetic risk, chronic lung disease, balanced diet, obesity, smoking, passive smoking, chest pain, cough, hemoptysis, fatigue, weight loss, shortness of breath, wheezing, difficulty swallowing, nail thickening and snoring. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Air pollution

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Monolithically-Integrated Quarter-Spherical Bandstop Filters

Monolithically-Integrated Quarter-Spherical Bandstop Filters

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European Conference on Microwave

作者： Dimitra Psychogiou Christian Elmiger Symeon Nikolaou Photos Vryonides School of Engineering University College Cork Ireland Tyndall National Institute Ireland Stryker Ireland Frederick Research Center Cyprus Department of Electrical Computer Engineering and Informatics Frederick University Cyprus

ISBN: (数字)9782874870774

ISBN: (纸本)9798350385892

This paper discusses a unique design and integration concept for high-quality factor (Q) monolithically-integrated 3D bandstop filters (BSFs) using quarter-spherical resonators. Monolithic integration is facilitated by: i) stereolithography apparatus (SLA) 3D printing and ii) EM design methodologies focused on the realization of a self-supported geometry. A coaxial excitation scheme is proposed to facilitate utilization in connectorized RF systems. For proof-of-concept validation purposes, two BSF prototypes were designed, manufactured, and tested. They include a two-resonator BSF configuration with center frequency (f cen ): 11.9 GHz, 3-dB rejection fractional bandwidth (BW): 4.5%, maximum stopband rejection: 61 dB and a four-resonator BSF with f cen : 11.8 GHz, 3-dB rejection bandwidth (BW): 4%, maximum stopband rejection: 85 dB.

关键词： Radio frequency Three-dimensional displays Resonator filters Prototypes Monolithic integrated circuits Bandwidth Three-dimensional printing Stereolithography Microwave filters Resonators

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Artificial Intelligence Oriented User Sentiment Evaluation System on Social Networks using Modified Deep Learning Principles 5

Artificial Intelligence Oriented User Sentiment Evaluation S...

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5th International Conference on Mobile Computing and Sustainable informatics, ICMCSI 2024

作者： Thangamayan, S. Jagdale, Sandip Nivrutti Lakshmi, T. R. Kalai Gopal Thatipudi, Jayendra Penyameen, K. Khan, Bhola Saveetha Institute of Medical and Technical Sciences Saveetha School of Law Department of Research and Development Chennai77 India Yashwantrao Mohite Institute of Management Karad India Sathyabama Institute Of Science And Technology School Of Management Studies Chennai India University of North Texas Dept. of Computer Science United States Velammal College Of Engineering And Technology Madurai India MJP Rohilkhand University Department of Regional Economics Bareilly India

ISBN: (纸本)9798350395235

Sentiment analysis, a pivotal aspect of natural language processing, is vital for deciphering the emotional nuances embedded in textual data. This project introduces an innovative workflow that amalgamates various techniques to elevate sentiment analysis performance. The workflow encompasses Fuzzy C-means (FCM) clustering for pattern identification, Differential Multi-layer Whale Optimization (DWO) for feature extraction, and a classification phase utilizing diverse deep learning models, including Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN). Additionally, Ant Lion Optimization (ALO) ensures system optimization, fostering robustness and adaptability. The proposed system is evaluated against eight distinct deep learning models, each offering unique architectures or configurations. Remarkably, the proposed workflow achieves an impressive accuracy of 96%, underscoring its efficacy in discerning complex sentiments. This high level of accuracy positions the system as a powerful tool for real-world applications where nuanced understanding of human sentiment is paramount. The project contributes to the evolving landscape of sentiment analysis, providing a comprehensive framework for extracting valuable insights from diverse textual datasets. © 2024 IEEE.

关键词： Long short-term memory

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An In-Depth Examination of Cybersecurity: Unveiling Contemporary Trends and Recent Advancements in the World of Cyber Threats

An In-Depth Examination of Cybersecurity: Unveiling Contempo...

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Cyber Resilience (ICCR), International Conference on

作者： Waseem Alhasan Muhammad Wannous Abedallah Abualkishik Mohammad Rustom Al Nasar Liaqat Ali Hani Al-Zoubi School of Computer Science and Informatics De Montfort University Dubai Dubai United Arab Emirates Higher Colleges of Technology Al Ain United Arab Emirates American University in the Emirates Dubai United Arab Emirates College of Computer Information Technology American University in the Emirates (AUE) Academic City - Dubai UAE College of Engineering and Technology University of Science and Technology of Fujairah Fujairah UAE Department of Computer Engineering College of Engineering Mutah University Jordan

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

The virtual realm now serves as the primary stage for a wide variety of global interactions spanning economic, industrial, cultural, social and governmental exchanges, between people, non-governmental agencies and government institutions. Given our increasing dependence on the electronic age, protecting statistics from cyber threats has become an impressive mission. Cyberattacks often target groups with the goal of causing economic damage and, at times, have military or political motivations. These attacks occur on various documents, including computer viruses, data breaches, and other attack methods. Exclusive companies hire numerous solutions to mitigate the damage caused by cyberattacks, with cybersecurity structures that track cutting-edge IT logs in real time.

关键词： Economics Target tracking Military computing Law enforcement Government Market research Real-time systems

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Personalizing text summarization based on sentence weighting

Personalizing text summarization based on sentence weighting

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2007 IADIS European Conference on Data Mining, DM 2007, part of the 1st IADIS Multi Conference on computer Science and Information Systems, MCCSIS 2007

作者： Bouras, Christos Poulopoulos, Vassilis Tsogkas, Vassilis Research Academic Computer Technology Institute Computer Engineering and Informatics Department University of Patras N. Kazantzaki Str. Rion26500 Greece

ISBN: (纸本)9789728924409

The amount of data that exists on the Internet is enormous enough to distract users when trying to find useful information. In addition, the expansive use of small screen devices for browsing the World Wide Web generates huge problems when trying to find and read information. A solution to these problems is to personalize the web and try to reduce algorithmically the amount of text. Many text summarizers have been presented in order to reduce the valueless information that is presented to the users and many web sites, especially news portals, introduce personalization features for the users, though, still these techniques are not often used in combination in order to create more effective results. In this paper a mechanism for creating personalized summaries for the members of a news portal that reproduces articles collected from major portals is presented, together with evaluation both of the summarizer and the personalized summaries. The evaluators of the personalized summaries are members of the news portal. The personalized summary mechanism can also be utilized by users of small screen devices, for easier reading of less but inclusive information. © 2007 IADIS

关键词： Text processing

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