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3rd IEEE Mysore Sub Section International Conference, MysuruCon 2023

作者： Mondal, Subhash Barman, Anup Kumar Basumatary, Subungshri Barman, Manas Rai, Chirag Nag, Amitava Bengaluru India Central Institute of Technology Kokrajhar Computer Science and Engineering Assam Kokrajhar India Meghnad Saha Institute of Technology Computer Science and Business Systems Kolkata India Central Institute of Technology Kokrajhar Computer Science and Engineering Kokrajhar India

ISBN: (纸本)9798350340358

Many research studies have been carried out to identify different variations of cancers in the human body throughout the globe. Due to numerous volumes, the primary concern for healthcare researchers is to segregate the article into a well-thought-out manner. Biomedical text classification is a globally volitional realm due to its numerous uses in different fields. This study motivates us to use a dataset related to cancer articles text containing 7570 research papers with categories into three classes. Like the Word2Vec and BERT models, the word embedding technique converts the text into a numeric vector. The text classification-based prediction model considers nine Machine Learning (ML) classifiers. The models are tested with k-fold cross-validation and evaluate the prediction performances by considering the different standard metrics. The model trade-off between bias and variance is controlled by calculating the standard deviation and k-fold mean accuracy to overcome the overfitting problem of the deployed model. The outcome is observed on the Random Forest (RF) classifier in the case of Word2Vec embedding with a mean accuracy of 99.98%. The BERT models also performed well, with about 97.70% mean accuracy and other parameters compared to the Word2Vec model. The other parameters' evaluation score was near 1.00, promising in multiclass text classification deployed model performances. © 2023 IEEE.

关键词： Support vector machines

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Dynamic Independent Set of Disks (and Hypercubes) Made Easier 8

Dynamic Independent Set of Disks (and Hypercubes) Made Easie...

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8th SIAM Symposium on Simplicity of Algorithms, SOSA 2025

作者： Bhore, Sujoy Chan, Timothy M. Department of Computer Science & Engineering Indian Institute of Technology Bombay Mumbai India Department of Computer Science University of Illinois Urbana-Champaign United States

ISBN: (纸本)9781611978315

Maintaining an approximate maximum independent set of a dynamic collection of objects has been studied extensively in the past few years. Recently, Bhore, Nöllenburg, Tóth, and Wulms (SoCG 2024) showed that for (unweighted) disks in the plane, it is possible to maintain O(1)-factor approximate solution in polylogarithmic amortized update time. In this work, we provide a much simpler dynamic O(1)-approximation algorithm, which at the same time improves the number of logarithmic factors in the previous update time bound. Along the way, we also obtain simpler and faster algorithms for dynamic independent set for axis-aligned hypercubes as well as static independent set for fat objects in any constant dimension. All the above results also hold for the minimum piercing set problem for the same classes of objects. Copyright © 2025 Copyright for this paper is retained by authors.

关键词： Consensus algorithm

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Detection of malaria parasite in thick blood smears using deep learning

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Materials Today: Proceedings 2022年 64卷 511-516页

作者： Balaram, Allam Silparaj, Manda Gajula, Rajender Department of Information Technology MLR Institute of Technology Hyderabad 500043 India Department of Computer Science and Engineering Vignan Institute of Technology and Science Hyderabad 508284 India Department of Computer Science and Engineering Vignana Bharathi Engineering College Hyderabad 501510 India

We're working on a deep learning algorithm which can distinguish between malaria parasites in blood smears in a video format which consists of several images. There are two processing steps in our method. Initially, we locate parasites by quickly inspecting a thick smear image and remove noise from that parasite. Then, using a customized Convolutional Neural Network (CNN), each image in a video is classified as one of two ways, whether it consists of parasite or not. We took a datafile of 1817 smear photographs from 148 victims from an openly accessible institute. This datafile was used to assess and trial our algorithm. © 2022

关键词： Iterative methods

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A Novel Approach for Resume Ranking System Using Machine Learning 3rd

A Novel Approach for Resume Ranking System Using Machine Lea...

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3rd International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Rajesh, B. Vignesh, G. Ram Sai Chamakura, Sai Kumar Karthik, N. Vani, V. Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal609609 India Department of Mechanical Engineering National Institute of Technology Karaikal Puducherry609609 India

ISBN: (纸本)9789819783540

Nowadays, many job ads are attracting a vast number of applications in less time on the internet. Screening and sorting these resumes manually is a very time-consuming process and costs a huge amount of money for recruiting organizations. This research paper suggests an automated method for matching resumes to open vacancies. To identify the most accurate machine learning approach, it investigates several of them, including Random Forest, K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Tree, Logistic Regression, Naïve Baye’s Classifier. Based on the findings of this research, Random Forest produces more accurate results for a given dataset. By using this automatic resume categorization method, the recruiting process will be revolutionized in terms of cost, time, and justice. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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AI-Driven Power Gating for Enhanced Energy Efficiency in Superscalar Processors 31

AI-Driven Power Gating for Enhanced Energy Efficiency in Sup...

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31st IEEE International Conference on High Performance Computing, Data, and Analytics Workshops, HiPCW 2024

作者： Kalra, Naman Tudu, Jaynarayan T. Dept. of Electrical Engineering Indian Institute of Technology Tirupati India Dept. of Computer Science Engineering Indian Institute of Technology Tirupati India

ISBN: (纸本)9798331509118

Amid the rising demand for efficient processors, the challenge has always been to reduce power consumption without compromising performance. FinFET technology has significantly reduced leakage power issues, but dynamic power consumption at lower nodes has reemerged as a concern. Methodologies such as power/clock gating, DVFS, and voltage biasing have been proposed in the past. However, next-generation complex SoC designs at © 2024 IEEE

关键词： System-on-chip

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Automated Recognition of Wild Animal Species in Camera Trap Images Using Deep Learning Models 3

Automated Recognition of Wild Animal Species in Camera Trap ...

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3rd International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Thangaraj, Rajasekaran Rajendar, Sivaramakrishnan Sanjith, M. Rithick Saran, K. Sasikumar, Sudev Chandhru, L. KPR Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9781665494007

Wild animal monitoring is one of the essential factors in balancing the ecosystem in protecting the animal habitat. Camera traps are used to capture the images, which play a vital role in the automatic monitoring of wildlife owing to their effectiveness in collecting wildlife data. The images captured from the camera traps are large volumes in nature, and they are inexpensive. However, the manual processing of such a large number of images is a time-consuming, expensive, and challenging task. Such a kind of process provides major hurdles to ecologists in monitoring wildlife. This paper evaluates deep learning models such as DeneseNet169, InceptionResNetV2, ResNetV2-50, and Xception for the automatic identification and recognition of individual animals in different patterns. The effectiveness of the models is measured using precision, recall, and F1 score indicators. Finally, the experimental findings show that the InceptionResNetV2 model outperforms the other models with an accuracy of 99%. © 2023 IEEE.

关键词： Cameras

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An Organized Examination of Image Processing for Detection and Diagnosis of Plant Diseases 7

An Organized Examination of Image Processing for Detection a...

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7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Naveenkumar, M. Akila, M. KPR Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

Agriculture is one of the most important and necessary sources of national wealth. Plant and crop diseases are one of the major factors that affect output quality and quantity. Lack of quality and quantity in food production creates a negative impact on the economy as well. Hence, it is crucial to identify plant diseases. Studies reveal a wide range of plant diseases occurring in different parts of the world. Various components of plants exhibit symptoms of plant diseases especially, the leaves. Extensive research is conducted across the globe and many horticulture specialists in liaison with technological experts apply computer vision and soft computing methods to automatically detect plant diseases from leaf photos. This article provides a summary of several aspects of such studies, along with their benefits and drawbacks. The authors addresses common infections as well as the state of such detection systems' research at various stages. The current feature extraction methods are examined in order to determine which one seems to function best across a variety of crop categories. This study will aid researchers in their understanding of the use of computer vision for identifying and categorizing plant diseases. © 2023 IEEE.

关键词： computer vision

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Changes in physiology, antioxidant system, and gene expression in Microcystis aeruginosa under fenoxaprop-p-ethyl stress

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Environmental science and Pollution research 2024年第19期31卷 28754-28763页

作者： Liu, Sijia Ni, Jiawei Guan, Ying Tao, Jianwei Wu, Liang Hou, Meifang Wu, Shichao Xu, Wenwu Zhang, Chu Ye, Jing School of Chemical and Environmental Engineering Shanghai Institute of Technology Shanghai201418 China Los Angeles Regional Water Quality Control Board Los AngelesCA90013 United States School of Ecological Technology and Engineering Shanghai Institute of Technology Shanghai201418 China School of Computer Science and Information Engineering Shanghai Institute of Technology Shanghai201418 China

Fenoxaprop-p-ethyl (FE) is one of the typical aryloxyphenoxypropionate herbicides. FE has been widely applied in agriculture in recent years. Human health and aquatic ecosystems are threatened by the cyanobacteria blooms caused by Microcystis aeruginosa, which is one of the most common cyanobacteria responsible for freshwater blooming. Few studies have been reported on the physiological effects of FE on M. aeruginosa. This study analyzed the growth curves, the contents of chlorophyll a and protein, the oxidative stress, and the microcystin-LR (MC-LR) levels of M. aeruginosa exposed to various FE concentrations (i.e., 0, 0.5, 1, 2, and 5 mg/L). FE was observed to stimulate the cell density, chlorophyll a content, and protein content of M. aeruginosa at 0.5- and 1-mg/L FE concentrations but inhibit them at 2 and 5 mg/L FE concentrations. The superoxide dismutase and catalase activities were enhanced and the malondialdehyde concentration was increased by FE. The intracellular (intra-) and extracellular (extra-) MC-LR contents were also affected by FE. The expression levels of photosynthesis-related genes psbD1, psaB, and rbcL varied in response to FE exposure. Moreover, the expressions of microcystin synthase-related genes mcyA and mcyD and microcystin transportation-related gene mcyH were significantly inhibited by the treatment with 2 and 5 mg/L FE concentrations. These results might be helpful in evaluating the ecotoxicity of FE and guiding the rational application of herbicides in modern agriculture. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Gene expression

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Leveraging U-Net Variants for High-Precision Flood Mapping: A Performance Evaluation on the ETCI Dataset 2

Leveraging U-Net Variants for High-Precision Flood Mapping: ...

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2nd IEEE International Conference on Emerging research in Computational science, ICERCS 2024

作者： Thirugnanasammandamoorthi, Puviyarasi Ghosh, Debabrata Dewangan, Ram Kishan Thapar Institute of Engineering and Technology Department of Electronics and Communication Engineering Punjab India Bennett University School of Computer Science Engineering and Technology India

ISBN: (纸本)9798331534950

Flood mapping is a crucial task in mitigating the adverse impacts of flooding by providing accurate spatial information about inundated areas. This study explores flood mapping using the ETCI dataset, leveraging the U-Net model and its enhanced variants. Initially, a basic U-Net architecture is employed to generate flood maps, followed by progressively improved versions incorporating batch normalization, dropout, and attention mechanisms. These modifications aim to enhance model generalization, robustness, and feature extraction capabilities. For the purpose of evaluating the model's performance, metrics like accuracy, F1-score, and Intersection over Union (IoU) are utilised. The generated flood maps demonstrate the potential of advanced U-Net architectures for precise and efficient flood delineation, providing a valuable tool for disaster management and planning. © 2024 IEEE.

关键词： Disaster prevention

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Boost Up the Mechanical and Electrical Property of CNT Fibers by Governing Lyotropic Liquid Crystalline Mesophases with Aramid Polymers for Robust Lightweight Wiring Applications

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Advanced Fiber Materials 2023年第2期5卷 514-526页

作者： Ki‑Hyun Ryu Jeong‑Gil Kim Dongju Lee Seo Gyun Kim Bon‑Cheol Ku Jun Yeon Hwang Kwang‑Un Jeong Nam Dong Kim Dae‑Yoon Kim Functional Composite Materials Research Center Korea Institute of Science and TechnologyWanju 55324Republic of Korea Carbon Composite Materials Research Center Korea Institute of Science and TechnologyWanju 55324Republic of Korea Department of Polymer‑Nano Science and Technology Department of Nano Convergence EngineeringJeonbuk National UniversityJeonju 54896Republic of Korea Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and TechnologyDaejeon 34141Republic of Korea

Monofilament type of polyaromatic amide(PA)and carbon nanotube(CNT)composite fibers is presented.A concept of a lyotropic liquid crystal(LLC)constructed via a spontaneous self-assembly is introduced to mitigate the extremely low com-patibility between PA and *** approaches provide an effective co-processing route of PA and CNT simultaneously to fabricate the uniform,continuous,and reliable composite fibers through a ***,the addition of a small amount PA into the dope solution of CNT governs the LLC mesophase not only in a spinneret stage but also in a coagulant ***,the developed PA/CNT composite fibers have the high uniaxial orientational order and the close interfacial packing compared to the pure CNT *** PA/CNT composite fibers achieve the outstanding tensile strength,electrical conductivity,and electrochemical response,while maintaining a *** also exhibit the chemical,mechanical,and thermal *** of these advantages can make flexible,sewable,and washable PA/CNT composite fibers ideal nanocomposite materials for use in next-generation information and energy transporting system by replacing conventional metal electrical conductors.

关键词： Carbon nanotube Aramid polymer Liquid crystal Composite fiber Electrical wire

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