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Conference on New Media Studies (CoNMedia)

作者： Lindung Parningotan Manik Harry Susianto Arawinda Dinakaramani Niken Pramanik Totok Suhardijanto Research Center for Data and Information Sciences National Research and Innovation Agency Bandung Indonesia Department of Computer Science University of Nusa Mandiri Jakarta Indonesia Faculty of Psychology University of Indonesia Depok Indonesia Faculty of Computer Science University of Indonesia Depok Indonesia Department of Linguistics Faculty of Humanities University of Indonesia Depok Indonesia

An essential endeavor in natural language processing, sentiment analysis entails determining the sentiment expressed in a text. Transformer-based models like BERT have attained state-of-the-art performance in sentiment analysis tasks. However, these algorithms may have difficulty distinguishing sentiment-laden words. In response, we proposed combining lexicon-based sentiment analysis and transformer-based models. This study investigates the effect of lexicon-based sentiment analysis, particularly SentiStrength, on BERT's efficacy in sentiment analysis tasks. Experimental evaluations reveal that incorporating sentiment lexicons enhances the accuracy and F1-score of classical sentiment analysis compared to the baseline BERT model. Our findings demonstrate the value of incorporating external knowledge sources into transformer-based sentiment analysis models.

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Multi-dimensional continuous time quantum walks related to the birth and death chains

arXiv

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arXiv 2024年

作者： Ide, Yusuke Konno, Norio Narimatsu, Akihiro Department of Mathematics College of Humanities and Sciences Nihon University Se-tagaya Tokyo156-8550 Japan Department of Mathematical Sciences College of Science and Engineering Ritsumeikan University 1-1-1 Noji-higashi Kusatsu525-8577 Japan Center for Mathematical and Data Sciences The University of Fukuchiyama Hori 3370 Fukuchiyama Kyoto620-0886 Japan

In this paper, we consider multi-dimensional birth and death chains and continuous time quantum walks (CTQW) related to them. For CTQW related to our forms of multi-dimensional birth and death chains, we obtain the time scaled independence between multiple dimensions about the transition probability of CTQW. By using this feature, we analyze CTQW on the path graph, which is related to 1-dimensional Ehrenfest model. We also have a random variable which is related to our models and converges to the standard Gaussian *** Codes 81Q99, 05C50 © 2024, CC0.

关键词： Continuous time systems

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Influence of Tea Leaf Particle Size on Catechin Extraction and Green Tea Sensory Acceptance

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Food and Nutrition sciences 2023年第11期14卷 1043-1056页

作者： Dongyang Li Yu Zhang Ritsuko Tamura Toshiro Nakajima Sabine Gouraud Julien Tripette Yuko Caballero Graduate School of Humanities and Sciences Ochanomizu University Tokyo Japan Leading Graduate School Promotion Center Ochanomizu University Tokyo Japan Department of Occupational and Environmental Health Nagoya University Graduate School of Medicine Nagoya Japan Research Center for Agricultural Information Technology National Agriculture and Food Research Organization Ibaraki Japan Tohoen Company Tokyo Japan Department of Natural Science College of Liberal Arts International Christian University Tokyo Japan Center for Interdisciplinary AI and Data Science Ochanomizu University Tokyo Japan Utsunomiya University Utsunomiya Japan

The intensity of the bitterness of catechins increases with increased concentration, but the taste palatability decreased in green tea extract. The aim of this study was to investigate whether a blend of tea leaf particles of various sizes would result in a good balance between catechin content and appreciable taste. The control is common tea (CT) with 6 - 10 mm long leaves. Blend tea (BT) was prepared by mixing 5 mm and 120 - 130 mm long tea leaves in a ratio of 3:2. The catechin content of hot water extracts was analyzed by HPLC, and the sensory test was conducted with 99 volunteers. In BT, the total catechin content was significantly higher than that in CT. The sensory test results revealed that BT was less bitter and had more preferable color than CT. More catechins were extracted from BT, but it tasted less bitter. Thus, the recalibration of the tea leaf particle size can result in good balance between catechin content and palatability.

关键词： Blend Tea Catechin Content Sensory Test Bitterness Palatability

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Fine-scale genetic structure of Tujia and central Han Chinese revealing massive genetic admixture under language borrowing

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植物分类学报 2021年第1期59卷 1-20页

作者： Guang-Lin He Ying-Xiang Li Meng-Ge Wang Xing Zou Hui-Yuan Yeh Xiao-Min Yang Zheng Wang Ren-Kuan Tang Su-Min Zhu Jian-Xin Guo Ting Luo Jing Zhao Jin Sun Zi-Yang Xia Hao-Liang Fan Rong Hu Lan-Hai Wei Gang Chen Yi-Ping Hou Chuan-Chao Wang Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and Medicineand School of Life SciencesXiamen UniversityXiamen 361005FujianChina Institute of Forensic Medicine West China School of Basic Science and Forensic Medicine Sichuan UniversityChengdu 610041China Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and Medicineand School of Life SciencesXiamen UniversityXiamen 361005FujianChina Institute of Forensic Medicine West China School of Basic Science and Forensic Medicine Sichuan UniversityChengdu 610041China Institute of Forensic Medicine West China School of Basic Science and Forensic Medicine Sichuan UniversityChengdu 610041China School of Humanities Nanyang Technological UniversityNanyang 639798Singapore Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and Medicineand School of Life SciencesXiamen UniversityXiamen 361005FujianChina Institute of Forensic Medicine West China School of Basic Science and Forensic Medicine Sichuan UniversityChengdu 610041China Department of Forensic Medicine College of Basic Medicine Chongqing Medical UniversityChongqing 400000China Department of Forensic Medicine College of Basic Medicine Chongqing Medical UniversityChongqing 400000China Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and Medicineand School of Life SciencesXiamen UniversityXiamen 361005FujianChina Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and Medicineand School of Life SciencesXiamen UniversityXiamen 361005FujianChina Department of Anthropology and Ethnology Institute of AnthropologyNational Institute for Data Science in Health and Medicineand School of Life SciencesXiamen UniversityXiamen 361005FujianChina Department of Anthropology and Ethnology In

Archaeological,genetic,and linguistic evidence has supported the idea that northern China is the original center of modern Sino-Tibetan-speaking ***,the demographic history of subsequent southward migration and genetic admixture of Han Chinese with surrounding indigenous populations remain uncharacterized,and the language shifts and assimilations accompanied by movement of people,or just an adaptation of cultural ideas among populations in central China is still unclear,especially for Tibeto-Burman-speaking Tujia and central Han Chinese *** resolve this,we genotyped over 60K genome-wide markers in 505 unrelated individuals from 63 indigenous *** results showed both studied Han and Tujia were at the intermediate position in the modern East Asian North-South genetic cline and there was a correlation between the genetic composition and the *** observed the strong genetic assimilation between Tujia people and central Han Chinese,which suggested massive population movements and genetic admixture under language *** and central Han Chinese could be modeled as a two-way admixture deriving primary ancestry from a northern ancestral population closely related to the ancient DevilsCave and present-day Tibetans and a southern ancestral population closely related to the present-day Tai-Kadai and Austronesian-speaking *** ancestral northern population we suspect to be related to the Neolithic millet farming groups in the Yellow River Basin or central *** showed that the newly genotyped populations in Hubei Province had a higher proportion of DevilsCave or modern Tungusic/Mongolic-related northern ancestries,while the Hunan populations harbored a higher proportion of Austronesian/Tai-Kadai-related southern ancestries.

关键词： demographic history gene flow genetic admixture language borrowing Tibeto-Burman Tujia

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Geochemistry and the optics of geospatial analysis as a preposition of water quality on a macroscale

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Environmental science and Pollution Research 2024年第22期31卷 32614-32636页

作者： Lozano, Liliana P. Taleb, Manal F. Abou Ibrahim, Mohamed M. Gonçalves, Janaína O. Neckel, Alcindo Schmitz, Guilherme P. Bodah, Brian William Korcelski, Cleiton Maculan, Laércio Stolfo Silva, Luis F. O. Department of Civil and Environmental Engineering Universidad de La Costa CUC Calle 58 #55-66 Atlántico Barranquilla Colombia Postgraduate Doctoral Program in Society Nature and Development Universidade Federal Do Oeste Do Pará UFOPA Paraná68040-255 Brazil Department of Chemistry College of Science and Humanities in Al-Kharj Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia Department of Chemistry College of Science Taif University Taif21944 Saudi Arabia ATITUS Educação RS Passo Fundo30499070-220 Brazil Universidade Do Minho UMINHO Porto4710-057 Portugal Thaines and Bodah Center for Education and Development 840 South Meadowlark Lane OthelloWA99344 United States Workforce Education & amp Applied Baccalaureate Programs Yakima Valley College South 16 Avenue & Nob Hill Boulevard YakimaWA98902 United States CDLAC—Data Collection Laboratory and Scientific Analysis LTDA Porto Alegre90670-090 Brazil

The water treatment depends exclusively on the identification of residues containing toxic chemical elements accumulated in NPs (nanoparticles), and ultrafine particles sourced from waste piles located at old, abandoned sulfuric acid factories containing phosphogypsum requires global attention. The general objective of this study is to quantify and analyze the hazardous chemical elements present in the leachate of waste from deactivated sulfuric acid factories, coupled in NPs and ultrafine particles, in the port region of the city of Imbituba, Santa Catarina, Brazil. Samples were collected in 2020, 2021, and 2022. Corresponding images from the Sentinel-3B OLCI satellite, taken in the same general vicinity, detected the levels of absorption coefficient of Detritus and Gelbstoff (ADG443_NN) in 443 m−1, chlorophyll-a (CHL_NN (m−3)), and total suspended matter (TSM_NN (g m−3) at 72 points on the marine coast of the port region. The results of inductively coupled plasma atomic-emission spectrometry (ICP-AES) and inductively coupled plasma mass spectrometry (ICP-MS) demonstrate that the leaching occurring in waste piles at the port area of Imbituba was the likely source of hazardous chemical elements (e.g., Mg, Sr, Nd, and Pr) in the environment. These leachates were formed due to the presence of coal pyrite and Fe-acid sulfates in said waste piles. The mobility of hazardous chemical elements potentiates changes in the marine ecosystem, in relation to ADG443_NN (m−1), CHL_NN (m−3), and TSM NN (g m−3), with values greater than 20 g m−3 found in 2021 and 2022. This indicated changes in the natural conditions of the marine ecosystem up to 30 km from the coast in the Atlantic Ocean, justifying public initiatives for water treatment on a global scale. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Nanoparticles

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Canonical Workflow for Experimental Research

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data Intelligence 2022年第2期4卷 155-172页

作者： Dirk Betz Claudia Biniossek Christophe Blanchi Felix Henninger Thomas Lauer Philipp Wieder Peter Wittenburg Martin Zunkeler TIB-Leibniz Information Centrefor Science and Technology Welfengarten 1B30167 HannoverGermany Center for Empirical Research in Economics and Behavioral Sciences(CEREB) University of ErfurtNordhauser Str.6399089 ErfurtGermany DONA Foundation C/O Universitede GeneveRuedu General-Dufour 241204 GeneveSwitzerland Statistics and Data Science in Social Sciences and the Humanities Department of StatisticsLudwig-Maximilians-University MunchenLudwigstr.3380539 MunchenGermany GWDG Burckhardtweg 437077 GotingenGermany FDO Forum Gemeindeweg 5547533 KleveGermany 7KAIROS Bochum UniversitatsstraBe 13644799 BochumGermany

The overall expectation of introducing Canonical Workflow for Experimental Research and FAIR digital objects(FDOs)can be summarised as reducing the gap between workflow technology and research practices to make experimental work more efficient and improve FAIRness without adding administrative load on the *** this document,we will describe,with the help of an example,how CWFR could work in detail and improve research *** have chosen the example of"experiments with human subjects"which stretches from planning an experiment to storing the collected data in a *** we focus on experiments with human subjects,we are convinced that CWFR can be applied to many other data generation processes based on *** main challenge is to identify repeating patterns in existing research practices that can be abstracted to create *** this document,we will include detailed examples from different disciplines to demonstrate that CWFR can be implemented without violating specific disciplinary or methodological *** do not claim to be comprehensive in all aspects,since these examples are meant to prove the concept of CWFR.

关键词： Experiments Experimental economics FAIR digital objects Information science FAIR research output

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Sentiment Analysis of Movie Review using Hybrid Optimization with Convolutional Neural Network in English Language

Sentiment Analysis of Movie Review using Hybrid Optimization...

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Artificial Intelligence and Smart Systems (ICAIS), International Conference on

作者： Vishal M. Tidake Nilanjan Mazumdar A. Suresh Kumar B. Nageswara Rao Gulnaz Fatma I. Infant Raj B. Kiran Bala Sanjivani College of Engineering Savitribai Phule Pune University Department of Business Administration University of of Science and Technology Meghalaya Computer Science and Engineering Coimbatore Department of Science and Humanities Lendi Institute of Engineering and Technology Jonnada Vizinagaram Dept of English Language Center Jazan University Jazan Saudi Arabia Department of Computer Science and Engineering K.Ramakrishnan College of Engineering Trichy Tamil Nadu India Department of Artificial Intelligence and Data Science K.Ramakrishnan College of Engineering Trichy Tamil Nadu India

There seems to be a growing amount of user-generated material online as more people become familiar with the Internet. Understanding hidden thoughts, emotions, and attitudes in tweets, emails, comments, and reviews is difficult yet essential for market analysis, brand tracking, social media tracking, and customer support. Sentiment Analysis (SA) identifies the emotional undertone of a string of words and also might basically be employed to comprehend a user’s attitude, thoughts, and emotions. The Harris Hawks Optimization - Sparrow S earch Algorithm with Convolutional Neural Network i.e., (HH-SSA-CNN) proposed in this study is an innovative SA algorithm. Pre-processing, sentiment categorization, and feature extraction make up the procedure. The preprocessing phase removes the unwanted info from input text evaluations using NLP algorithms. A hybrid technique that combines review-related features and aspect-related features has been presented for efficiently retrieving the features. This method creates unique composite features for every review. The created HH- SSA-CNN is used to accomplish sentiment categorization. This approach has been used in the IMDb dataset. To assess the model’s efficacy, the outcomes of the HH-SSA-CNN model are contrasted with those of alternative methodologies. The result indicates that the developed model accurately classifies the sentiments while compared to other existing methods.

关键词： Sentiment analysis Analytical models databases Social networking (online) Motion pictures Feature extraction Internet

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Demand Response Strategy Model Based on User Satisfaction 16th

Demand Response Strategy Model Based on User Satisfaction

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16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information Technology, Applications and Tools, FITAT 2020

作者： Guo, Xiaoli Sun, Yuhan Feng, Li Qu, Chaoyang Sun, Tieli School of Computer Science of Northeast Electric Power University Jilin City132012 China College of Humanities and Sciences of Northeast Normal University Changchun City130117 China Jilin Engineering Technology Research Center of Intelligent Electric Power Big Data Processing Jilin City132012 China State Grid Xin Yuan Fengman Training Center Jilin City132018 China

ISBN: (纸本)9789813364196

The demand response model of household microgrid based on satisfaction of customers is proposed after the users’ habit of using electricity which is found from the historical electricity data and aims at the problems of the load diversity of the household microgrid and the improvement of user satisfaction in response process, combined with the demand response theory of the users and the thought of data mining. The demand response strategy model based on users’ satisfaction is designed with the research of demand response behavior integrated with user’s side experience. The model takes the user's demand responsiveness as the load constraint, takes user’s comprehensive satisfaction maximum as the demand response objective, and takes the bacterial colony chemotaxis hybrid algorithm to solve the model. Finally, the optimal load power consumption plan is obtained as the user’s demand response strategy. The experimental simulation results verify the energy-saving effect of the model and the effectiveness of the algorithm. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Energy conservation

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Pilot test of the mutual assistance system using a wearable device for the elderly in WEB3.0 technology

Pilot test of the mutual assistance system using a wearable ...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Kenji Nakamura Keiichi Yamazaki Yusuke Arano Akiko Yamazaki Hiroshi Koga Naoya Ohta Takuya Mitsuhashi Hideru Obinata Yoshiaki Ohyama Center for Mathematics and Data Science Gunma University Gunma Japan Graduate School of Humanities and Social Sciences Saitama University Saitama Japan Faculty of Media Studies Tokyo University of Technology Tokyo Japan Department of Dermatology School of Medicine Shinshu University Nagano Japan Faculty of Engineering Gunma University Gunma Japan Division of Advanced Science and Technology Japan Advanced Institute of Science and Technology Tokyo Japan Graduate School of Medicine Gunma University Gunma Japan Innovative Medical Research Center Gunma University Hospital Gunma Japan

Using wearable devices and WEB3.0 to make doctor-patient interaction smarter. The aging of the population and COVID-19 have placed a tremendous workload on the medical field. Traditional monitoring has been centralized, with healthcare professionals providing face-to-face care to all patients. This is where blockchain is utilized, where users themselves have data and monitor each other. Mutual monitoring of medical information on the blockchain creates a mutually supportive relationship where users themselves monitor each other. In this demonstration experiment, the system was introduced to six elderly people. This decentralized system in which users themselves monitor each other is called the Web3 type. The Web type is a technology that is expected to break through the current concentration of data in overseas digital industries and leave digital data resources in Japan. This research is unique in that it combines blockchain technology, which is at the core of this technology, with medical information. A mutual assistance system was constructed to visualize and mutually monitor their exercise habits using wearable terminals. As a result, the exercise habits of all participants improved, and unique information was obtained from the questionnaire survey.

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Performance analysis of a novel hybrid deep learning approach in classification of quality-related English text

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Measurement: Sensors 2023年 28卷

作者： Orosoo, Myagmarsuren Govindasamy, Santhakumar Bayarsaikhan, Narmandakh Rajkumari, Yaisna Fatma, Gulnaz Manikandan, R. Kiran Bala, B. School of Humanities and Social Sciences Mongolian National University of Education Mongolia Department of Electronics and Communication Engineering Sri Krishna College of Technology Tamil Nadu Coimbatore India Theory and Methodology of Physical Education Mongolian National University of Education India Dept of Humanities and Social Sciences NIT Hamirpur India Dept of English Language Center Jazan University Jazan Saudi Arabia Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Tamil Nadu Chennai600062 India Department of Artificial Intelligence and Data Science K.Ramakrishnan College of Engineering Tamil Nadu Trichy India

Text classification technique is advancing rapidly alongside AI technology, showing signs of maturity. Moreover, there are always many unrestricted constraints that text classification must deal with in practical settings. English text is indeed a significant component of textual data and a significant source of data for persons seeking data from other countries. This study enhances the text classification method currently in use using text classification depending upon English quality. By using an illustration of English quality-related text classification systems, the concept as well as execution of text classification systems is demonstrated, concluding the study on text classification algorithms. The main task of this article is to categorize, and analyze huge volumes of information in English text using technique of integrating qualitative. Therefore, the fundamental components of superior English compositions are attained using Lion Optimization Algorithm (LOA). Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) is utilized to classify the obtained texts. If there is a lot of training input, the typical English text classification method can easily display flaws like ambiguous characteristic elements. In light of such issues, the research suggests a quality-related English text classification approach based on convolutional neural network in order to enhance the precision and adaptability of English text classification. © 2023

关键词： Long short-term memory

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