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29th International Computing and Combinatorics Conference, COCOON 2023

作者： Bailey, Lora Blake, Heather Smith Cochran, Garner Fox, Nathan Levet, Michael Mahmoud, Reem Matson, Elizabeth Bailey Singgih, Inne Stadnyk, Grace Wang, Xinyi Wiedemann, Alexander Department of Mathematics Grand Valley State University AllendaleMI United States Department of Mathematics and Computer Science Davidson College DavidsonNC United States Department of Mathematics and Computer Science Berry College Mount BerryGA United States Department of Quantitative Sciences Canisius University BuffaloNY United States Department of Computer Science College of Charleston CharlestonSC United States Department of Computer Science Virginia Commonwealth University RichmondVA United States The Division of Mathematics and Computer Science Alfred University AlfredNY United States Department of Mathematical Sciences University of Cincinnati CincinnatiOH United States Department of Mathematics Furman University GreenvilleSC United States Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI United States Department of Mathematics Randolph–Macon College AshlandVA United States

ISBN: (纸本)9783031491894

In this paper, we examine the computational complexity of enumeration in certain genome rearrangement models. We first show that the Pairwise Rearrangement problem in the Single Cut-and-Join model (Bergeron, Medvedev, & Stoye, J. Comput. Biol. 2010) is # P -complete under polynomial-time Turing reductions. Next, we show that in the Single Cut or Join model (Feijao & Meidanis, IEEE ACM Trans. Comp. Biol. Bioinf. 2011), the problem of enumerating all medians (#MEDIAN ) is logspace-computable (FL ), improving upon the previous polynomial-time (FP ) bound of Miklós & Smith (RECOMB 2015). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Phylogenetic

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A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala

arXiv

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arXiv 2024年

作者： Ranathunga, Surangika Ranasinghe, Asanka Shamal, Janaka Dandeniya, Ayodya Galappaththi, Rashmi Samaraweera, Malithi School of Mathematical and Computational Sciences Massey University Auckland102904 New Zealand Department of Computer Science and Engineering University of Moratuwa Katubedda10400 Sri Lanka

This paper presents a multi-way parallel English-Tamil-Sinhala corpus annotated with Named Entities (NEs), where Sinhala and Tamil are low-resource languages. Using pre-trained multilingual Language Models (mLMs), we establish new benchmark Named Entity Recognition (NER) results on this dataset for Sinhala and Tamil. We also carry out a detailed investigation on the NER capabilities of different types of mLMs. Finally, we demonstrate the utility of our NER system on a low-resource Neural Machine Translation (NMT) task. Our dataset is publicly released: https://***/suralk/multiNER. © 2024, CC BY.

关键词： Neural machine translation

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MSIsensor-RNA:Microsatellite Instability Detection for Bulk and Single-cell Gene Expression Data

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Genomics, Proteomics & Bioinformatics 2024年第3期22卷 85-90页

作者： Peng Jia Xuanhao Yang Xiaofei Yang Tingjie Wang Yu Xu Kai Ye Department of Gynecology and Obstetrics Center for Mathematical MedicalThe First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China MOE Key Lab for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China Genome Institute The First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China School of Life Science and Technology Xi’an Jiaotong UniversityXi’an 710049China

Microsatellite instability(MSI)is an indispensable biomarker in cancer ***,MSI scoring methods by high-throughput omics methods have gained popularity and demonstrated better performance than the gold standard method for MSI ***,the MSI detection method on expression data,especially single-cell expression data,is still lacking,limiting the scope of clinical application and prohibiting the investigation of MSI at a single-cell ***,we developed MSIsensor-RNA,an accurate,robust,adaptable,and standalone software to detect MSI status based on expression values of MSI-associated *** demonstrated the favorable performance and promise of MSIsensor-RNA in both bulk and single-cell gene expression data in multiplatform technologies including RNA sequencing(RNA-seq),microarray,and single-cell ***-RNA is a versatile,efficient,and robust method for MSI status detection from both bulk and single-cell gene expression data in clinical studies and ***-RNA is available at https://***/xjtu-omics/msisensor-rna.

关键词： Microsatellite instability Gene expression Single-cell RNA-seq RNA-seq Microarray

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Constructing A Theoretical Model to Bridge Neural Transition with a State Switch in Bipolar Disorder

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Neuroscience Bulletin 2025年第1期41卷 181-185页

作者： Xiaonan Guo Lizichen Chen Jianbo Lai Shaohua Hu Department of Psychiatry the First Affiliated HospitalZhejiang University School of MedicineHangzhou310003China Department of Engineering Mechanics Zhejiang UniversityHangzhou310027China Nanhu Brain-computer Interface Institute Hangzhou311100China The Zhejiang Key Laboratory of Precision Psychiatry Hangzhou310003China MOE Frontier Science Center for Brain Science and Brain-Machine Integration Zhejiang University School of MedicineHangzhou310003China Brain Research Institute of Zhejiang University Hangzhou310003China The State Key Lab of Brain-Machine Intelligence Zhejiang UniversityHangzhouChina Zhejiang Engineering Center for Mathematical Mental Health Hangzhou310003China

Reward or stress,which exists extensively,causes resilient emotional fluctuations under common ***,reward or stress is a typical trigger for manic or depressive episodes of bipolar disorder(BD),which is corroborated by psychological theory,biological findings,and psychosocial treatment approaches[1,2].During an episode of BD,the affective aberration can be persistent and switchable,accompanied by opposite constellations of cognitive and psychomotor *** by uncontrollable mood ranging in severity,duration,and polarity,to disentangle the pathophysiology mechanism of BD is to delineate the mystery of affective fluctuations driven by reward or stress.

关键词： bipolar Transition finding

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A Genetic Algorithm for Solving Sudoku Based on Multi-Armed Bandit Selection

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IEEE Transactions on Games 2024年

作者： Kim, Jon-Lark Eor, Eunjee Sogang University Department of Mathematics Korea and Institute for Mathematical and Data Sciences Seoul Korea Republic of Sogang University Department of Computer Science and Engineering Korea Republic of

In this paper, we introduce a Genetic Algorithm based Upper Confidence Bound (GA-UCB), an innovative hybrid genetic algorithm integrating Multi-Armed Bandit (MAB). It effectively addresses the challenges of solving large and intricate Sudoku puzzles, thus overcoming the constraints of traditional genetic algorithms. In GA-UCB, reinforcement learning (RL) is applied to simulate parent selection and crossover. By learning the optimal parent selection within a given population, the population evolves. Based on this technology, GA-UCB demonstrates improved results in solving complex Sudoku puzzles. GA-UCB is compared with several state-of-the-art algorithms on Sudoku puzzles of different difficulty levels and shows a 55% improvement in convergence speed compared to previous research results, particularly in the most challenging instance among the six Sudoku puzzle instances tested © 2018 IEEE.

关键词： Reinforcement learning

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Bottleneck-Minimal Indexing for Generative Document Retrieval

arXiv

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arXiv 2024年

作者： Du, Xin Xiu, Lixin Tanaka-Ishii, Kumiko Waseda Research Institute for Science and Engineering Waseda University Japan Department of Mathematical Informatics The University of Tokyo Japan Department of Computer Science and Engineering Waseda University Japan

We apply an information-theoretic perspective to reconsider generative document retrieval (GDR), in which a document x ∈ X is indexed by t ∈ T , and a neural autoregressive model is trained to map queries Q to T . GDR can be considered to involve information transmission from documents X to queries Q, with the requirement to transmit more bits via the indexes T . By applying Shannon’s rate-distortion theory, the optimality of indexing can be analyzed in terms of the mutual information, and the design of the indexes T can then be regarded as a bottleneck in GDR. After reformulating GDR from this perspective, we empirically quantify the bottleneck underlying GDR. Finally, using the NQ320K and MARCO datasets, we evaluate our proposed bottleneck-minimal indexing method in comparison with various previous indexing methods, and we show that it outperforms those methods. © 2024, CC BY.

关键词： Signal distortion

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Smoothed-LSTM: Advancing spatio-temporal NDVI prediction in semi-automated dataset for rice crop

Smoothed-LSTM: Advancing spatio-temporal NDVI prediction in ...

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Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS), International Conference on

作者： Anamika Dey Somrita Sarkar Debajyoti Kumar Arijit Mondal Pabitra Mitra Centre for Computational and Data Sciences Indian Institute of Technology Kharagpur Kharagpur India Department of Computer Science and Engineering Indian Institute of Technology Patna Bihta India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India

ISBN: (数字)9798350389678

ISBN: (纸本)9798350389685

Accurate Normalized Difference Vegetation Index (NDVI) forecasting is crucial for effective agricultural planning. However, a good prediction of the same requires sufficient data, but structured data is not available in the public domain or open-source community. Also, most of the existing methods do not consider spatial information. This study presents a novel semi-automated dataset generation framework that utilizes Sentinel-2, POWER Data Access Viewer, and Google Earth Engine to create a comprehensive time-series dataset. We propose a smoothed long short-term memory (LSTM) model considering time series, historical meteorological, and spatial information. The proposed Smoothed-LSTM-based model outperforms Traditional-LSTM models, demonstrating its effectiveness in NDVI prediction for agricultural applications.

关键词： Earth Time series analysis Predictive models Planning Internet Forecasting Long short term memory

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Wireless Capsule Endoscopy Bleeding Images Classification using CNN Based Model

Wireless Capsule Endoscopy Bleeding Images Classification us...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Kumar, Gotte Ranjith Jeyasudha, J. Ravi, G. Jagadesh, T. Madhura, G.K. Sr University School of Computer Science & Artificial Intelligence Warangal India Srm Insitute of Science and Technology Department of Computational Intelligence Chennai India Sona College of Technology Dept of Ece Salem India Kpr Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India Nitte Meenakshi Institute of Technology Department of Ai and Ml Bengaluru India

ISBN: (纸本)9798350313413

Wireless Capsule Endoscopy (WCE) is an effective utensil with probe alimentary region diseases and executes effortless visualizing in intestine. Numerous enterprises produce its broad connection and adaptation challenging things comparable efficacity, forbearance, immunity, and consummation. Self-regulated study of the WCE handed datafile is of immense significance for discriminating peculiarity. Detecting a case's gastrointestinal region through WCE outcomes a huge datafile that involves a significant quantum moment with an exceptional competence put from the therapeutic knowledge. So many computers-backed, eyesight-grounded results can be recommended to determine this controversy, so far it don't give asked position in delicacy, farther advancements just the same as demanded. Combine with deep neural network to develop a proposed model called BIR (bleedy image recognizer) to classify images of bleeding detected by a WCE. The BIR model is combination of MobileNet and a custom-built BERT model. BIR utilizes the MobileNet model for original-position calculation for its lesser calculation energy demand and latterly the affair is fed to the BERT model for farther processing. utilized a datafiles consisting of 1650 pictures captured by WCE for the purpose of training and testing the BIR mode. © 2023 IEEE.

关键词： BERT models Bleedy image recognizer computer vision deep learning gastrointestinal tract infection Wireless capsule endoscopy

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Optimization of Cognitive Radio System Using Self-Learning Salp Swarm Algorithm

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computers, Materials & Continua 2022年第2期70卷 3821-3835页

作者： Nitin Mittal Harbinder Singh Vikas Mittal Shubham Mahajan Amit Kant Pandit Mehedi Masud Mohammed Baz Mohamed Abouhawwash Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India School of VLSI Design and Embedded Systems National Institute of TechnologyKurukshetra136119India School of Electronics&Communication Engineering Shri Mata Vaishno Devi UniversityKatra182320India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computer and Information TechnologyTaif UniversityTaif21994Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

CognitiveRadio(CR)has been developed as an enabling technology that allows the unused or underused spectrum to be used dynamically to increase spectral *** improve the overall performance of the CR systemit is extremely important to adapt or reconfigure the *** Decision Engine is a major module in the CR-based system that not only includes radio monitoring and cognition functions but also responsible for parameter *** meta-heuristic algorithms offer numerous advantages compared to traditional mathematical approaches,the performance of these algorithms is investigated in order to design an efficient CR system that is able to adapt the transmitting parameters to effectively reduce power consumption,bit error rate and adjacent interference of the channel,while maximized secondary user ***-Learning Salp Swarm Algorithm(SLSSA)is a recent meta-heuristic algorithm that is the enhanced version of SSA inspired by the swarming behavior of *** this work,the parametric adaption of CR system is performed by SLSSA and the simulation results show that SLSSA has high accuracy,stability and outperforms other competitive algorithms formaximizing the throughput of secondary *** results obtained with SLSSA are also shown to be extremely satisfactory and need fewer iterations to converge compared to the competitive methods.

关键词： Cognitive radio meta-heuristic algorithm cognitive decision engine salp swarm algorithm

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A Detailed Analysis on Spam Emails and Detection Using Machine Learning Algorithms 1

引用

7th International Conference on Inventive Systems and Control, ICISC 2023

作者： Sulthana, Razia Verma, Avani Jaithunbi, A.K. Department of Computing and Mathematical Sciences University of Greenwich Old Royal Naval College LondonSE10 9LS United Kingdom Department of Computer Science Birla Institute of Technology & Science Pilani Dubai Campus Dubai345055 United Arab Emirates Department of Computer Science RMD Engineering College TamilNadu Kavaraipettai601206 India

ISBN: (数字)9789819916245

ISBN: (纸本)9789819916238

Spam email is the unwanted junk and solicited email sent in bulk to the receivers, using botnets, spambots, or a network of infected computers. These spam emails can be phishing emails that trick users to get their sensitive information, download malware into the user devices or scam the users stealing confidential data. This paper shows a systematic analysis of spam and its types. It also details the procedure of how the spammers get the email addresses of the receivers. It analyses the problems with spamming. A detailed state of the art on spam filters and the factors that put an email into the spam or ham category is also explained. The paper also discusses spam filtering methods of Gmail, Yahoo and Outlook. Finally, it brings out several solutions to detect spam using principles of Machine Learning and Data Mining. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electronic mail

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