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Latent Dirichlet Allocation (LDA) Topic modeling and Sentiment Analysis for Myanmar Coup Tweets 8

Latent Dirichlet Allocation (LDA) Topic Modeling and Sentime...

引用

8th international conference on Information Technology, Information systems and Electrical Engineering, ICITISEE 2024

作者： Manuaba, Ida Bagus Kerthyayana Karim, Mochammad Faisal School of Computing and Creative Arts Bina Nusantara University Computer Science Department Jakarta Indonesia University Islam International Indonesia Faculty of Social Science Depok Indonesia

ISBN: (纸本)9798350368970

Myanmar's coup in 2021 has produced public attention and discussions. Studying the trends and patterns of this event, a technological approach such as Natural Language Processing (NLP) could be used to analyze text data and develop insights. It can classify keywords and also group them into relevant topics, and then highlight aspects of the coup. Latent Dirichlet Allocation (LDA) is an NLP method that is widely used for information extraction and text classification. This paper focuses on the discussion about the utilization of LDA models in classifying the Topic modeling for the N-best topic related to Myanmar's coup tweets data. This study also discussed the sentiment analysis model to visualize the trends and patterns related to public opinion based on the classified topics. The results showed the best-classified topics are 12 topics with the highest coherence score of 4.448, and these topics also can be grouped into three big themes and showed several negative sentiments for specific identified topics. To analyze further, the ANOVA test has been used to analyze further the patterns and trends of this public opinion based on the classified topics and sentiment scores © 2024 IEEE.

关键词： Tweets

来源：评论

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Object Detection in Adverse Weather Conditions using Machine Learning 13

Object Detection in Adverse Weather Conditions using Machine...

引用

13th international conference on System modeling and Advancement in Research Trends, SMART 2024

作者： Rattanpal, Shveta Kashish, Kumari Kumari, Tannu Manvi Gupta, Shikha Chandigarh University Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350380583

Object detection in unfavourable climate situations, such as haze, rainfall, snowfall, and low-mild environments, provides vast challenges for real-time pc vision structures, specifically in crucial packages like autonomous driving, surveillance, and catastrophe reaction. This paper introduces YOLO v9, a novel deep mastering-based totally model optimized for sturdy object detection under such hard conditions. The proposed version builds at the strengths of previous YOLO versions, incorporating a extra efficient convolutional neural community (CNN) spine designed to decorate characteristic extraction in low-visibility situations. Additionally, YOLO v9 leverages superior strategies together with interest mechanisms, neural structure seek (NAS), and multi-sensor records fusion to enhance detection accuracy and reliability across numerous climate situations. We carried out large experiments using a specialised dataset augmented with artificial and real-international pics captured under various damaging climate situations. The outcomes show that YOLO v9 outperforms latest object detection fashions, achieving better suggest Average Precision (mAP) and advanced detection overall performance, specifically in foggy and rainy scenarios. The version's actual-time processing capability makes it appropriate for deployment in programs requiring on the spot decision-making, together with self sustaining cars and out of doors surveillance systems. Our findings spotlight the potential of YOLO v9 to significantly beautify the protection and reliability of item detection systems in environments wherein visibility is compromised by means of detrimental weather. © 2024 IEEE.

关键词： Large datasets

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Development of an Optical System for Non-Invasive Blood Glucose measurement 3

Development of an Optical System for Non-Invasive Blood Gluc...

引用

3rd international conference on Advanced Electrical Engineering, ICAEE 2024

作者： Reguig, Mohammed Anes Bereksi Labdelli, Nassima Tlemcen University Faculty of Technologie Research Laboratory of Biomedical Engineering Department of Biomedical Engineering Algeria Higher School of Applied Sciences Research Laboratory of Biomedical Engineering Tlemcen Algeria

ISBN: (纸本)9798350349351

Several people must frequently evaluate their blood glucose since it is an important indicator of health problems mainly Diabetes. Different medical systems are commercialized to measure blood glucose levels;some are invasive others are noninvasive. The main purpose of this article is to develop a non-invasive device for measuring blood glucose levels based on the detection and analysis of the Photoplethysmogram signal. The developed systems include an optical sensor to detect the PPG signal, digitalizing and acquiring boards to a computer and a software program to process and analyze the digitalized PPG signal regarding some features extracted from its waveform. These features are the systolic amplitude Sa and the b/a amplitude ratio in the second derivative PPG (SDPPG) waveform. An invasive glucometer is also used along with the Sa and b/a ratio determined from the developed system to generate a calibration model which is used to deduce BGL values. The result showed that the calibration model using the b/a ratio is more accurate for non-invasive blood level measurement then that of Sa with a difference in glucose estimation around 2mg/dl and with the correlation coefficient (R2) of the glucose level prediction between 0.8904 and 0.9775. © 2024 IEEE.

关键词： Glucose sensors

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Application of Digital Emotion modeling System in computer Aided Design of Modern Products

Application of Digital Emotion Modeling System in Computer A...

引用

2022 international conference on Sustainable Computing and Data Communication systems, ICSCDS 2022

作者： Zhang, Siwang College of Art Northwest University Xi'an Shaanxi 710127 China

ISBN: (纸本)9781665478847

This paper studies the application of digital emotion modeling in computer-aided design of modern products. First, the fuzzy reasoning method is used to realize the inference of students' expectation of learning events, and the built model is tested and evaluated by computer simulation by constructing a dynamic Bayesian network, and then based on the established emotional system, the computer-assisted modern product flow The line design performs quantum kinetic energy analysis, thereby providing a new emotion recognition model and architecture for building an e-learning system with emotional intelligence, and the effect is improved by 6.5%. © 2022 IEEE.

关键词： Semantics

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Business Intelligence Solutions Adoption Model for Peruvians SMEs Based on UTAUT2 20

Business Intelligence Solutions Adoption Model for Peruvians...

引用

20th international conference on Web Information systems and Technologies, WEBIST 2024

作者： Javier Ortiz Leigh, Luis Gutierrez Huaman, Axel Stuwart Dextre Alarcon, Jymmy School of Systems and Computer Engineering Peruvian University of Applied Sciences 2390 Primavera Avenue Lima Peru

ISBN: (纸本)9789897587184

Small and medium-sized enterprises (SMEs) face significant challenges to grow and make strategic decisions due to their small size and limited resources. This study proposes a model to identify the factors that influence the adoption of Business Intelligence (BI) solutions in Peruvian SMEs, based on the Unified Theory of Acceptance and Use of Technology (UTAUT2). The study methodology is divided into four phases. The first phase consists of analyzing existing technology adoption models to identify critical components that affect BI adoption. In the second phase, the proposed model is developed and survey questions are designed that will measure relevant factors for statistical validation. The third phase involves data collection through surveys targeting SMEs in Peru, followed by analysis to identify significant patterns. The fourth and final phase validates the model using the Partial Least Squares Structural Equation modeling (PLS-SEM) technique, evaluating the robustness and accuracy of the proposed model. The validation results show that the proposed factors Performance Expectation (PE), Price/Value Ratio (PV) and Competitive Pressure (CP) are the most influential in the intention to use BI solutions by Peruvian SMEs. Copyright © 2024 by SCITEPRESS.

关键词： Competitive intelligence

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modeling a Hybrid Stemmer for Kokborok

Modeling a Hybrid Stemmer for Kokborok

引用

2023 international conference on Intelligent systems, Advanced Computing and Communication, ISACC 2023

作者： Debbarma, Pankaj Hrangkhawl, Pusparwng Debbarma, Swapan Tripura Institute of Technology Department of Computer Science and Engineering Narsingarh India Ambedkar College Department of Information Technology Fatikroy India National Institute of Technology Department of Computer Science and Engineering Agartala India

ISBN: (纸本)9798350399387

Kokborok is a resource scarce and vulnerable language and is spoken only by around a million people in the north-east Indian state of Tripura. Lots of unstructured textual data in Kokborok is now available however efficient data mining for such a resource is not applicable. Reasons are the absence of an efficient pre-processing step that can help in solving the information retrieval or natural language processing. In this work, we present a model of hybrid stemming algorithm for the vulnerable and resource-scarce Kokborok language and assess its performance using various methods. Evaluation of the hybrid stemmer was performed on a corpus of 52,482 words that resulted in achieving an accuracy of 89.28%. Recall and Precision of 89.28% and 89.61 %, respectively, with F1-measure of 89.44 has been found for the stemmer. © 2023 IEEE.

关键词： Data mining

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Predictive modeling for Thyroid Disease Diagnosis using Machine Learning 7

Predictive Modeling for Thyroid Disease Diagnosis using Mach...

引用

7th international conference on Inventive Computation Technologies, ICICT 2024

作者： Agarwal, Ruhi Himanshu Degadwala, Sheshang Vyas, Dhairya Manipal University College Melaka Malaysia Sigma University Department of Computer Engineering Gujarat India The Maharaja Sayajirao University of Baroda Gujarat Vadodara India

ISBN: (纸本)9798350359299

Thyroid "conditions pose a worldwide health challenge, demanding precise and timely assessments. This research embarks on a three-stage investigation into machine learning (ML) algorithms for diagnosing thyroid diseases. Initially, the dataset's imbalance is rectified using Synthetic Minority Over-sampling Technique (SMOTE). Following this, models such as SVM, K-NN, Decision Trees, Random Forest, Naive Bayes, and Extra Trees undergo evaluation for predictive effectiveness. Metrics including accuracy, precision, recall, and F1 score are computed to gauge the efficiency of each algorithm. The results provide valuable insights into the optimal ML approach for thyroid disease diagnosis, contributing to the advancement of accurate clinical decision support systems in healthcare. © 2024 IEEE.

关键词： Decision trees

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Quantum computer Assisted Dynamics modeling for the Unified Configuration Analysis of Cultivated Land and Ecological Land with Data Classification Algorithms 4

Quantum Computer Assisted Dynamics Modeling for the Unified ...

引用

4th international conference on Smart systems and Inventive Technology, ICSSIT 2022

作者： Chen, Shiyin School Of Management Guangdong Ocean University Zhanjiang Guangdong524025 China

ISBN: (纸本)9781665401180

Quantum computer assisted dynamics modeling for the unified configuration analysis of cultivated land and ecological land with data classification algorithms is studied in this paper. In the ecological restoration strategy, planting plants with strong heavy metal accumulation capacity can enable ecological land to complete the restoration of damaged farmland in a short time, hence, the computer data collection system is combined to obtain the efficient data sets. Furthermore, the data classification models are combined for the comprehensive analysis. For the dynamics, the novel computer system is designed to validate the model. Comparison simulation is conductedto show the results. © 2022 IEEE

关键词： Heavy metals

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Blockchain-based secure crowdsourcing scheme to support solution reuse 4

Blockchain-based secure crowdsourcing scheme to support solu...

引用

4th international conference on Network Communication and Information Security, ICNCIS 2024

作者： Zhang, Yitong Cui, Wenxuan Miao, Jianchen Xi'an Aviation Computing Technology Research Institute Shaanxi Xian710065 China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

Crowdsourcing is a way to solve complex tasks by publicly collecting solutions on the network. The crowdsourcing system that provides task completion and solution reuse facilitates human life and promotes economic development. With the rise of blockchain technology, it is possible to design and implement a decentralized crowdsourcing scheme. However, due to the nature of data sharing on the blockchain, there are many challenges in the blockchain-based crowdsourcing scheme. In this paper, we first classify the required properties of blockchain-based decentralized crowdsourcing scheme including fairness, reusability and integrity. And then we propose a novel blockchain-based secure crowdsourcing scheme to support solution reuse using the Pedersen commitment, Paillier cryptosystem, secure hash function and Diffie-Hellman key exchange. The security analysis shows that our scheme satisfies the above requirements. Finally, we simulated the crowdsourcing task that may exist in the real world and evaluated the experimental results. © 2025 SPIE.

关键词： Blockchain Defense and security Chemical elements Design systems modeling Silicon computer security Information security Symmetric key encryption Windows

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Petri Net modeling of Root Hair Response to Phosphate Starvation in Arabidopsis Thaliana

Petri Net Modeling of Root Hair Response to Phosphate Starva...

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18th international Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2025

作者： Fijn, Amber H. B. Stiekema, Casper H. Boere, Stijn Višić, Marijan Cao, Lu Leiden Institute of Advanced Computer Science Leiden University Einsteinweg 55 Leiden Netherlands

Limited availability of inorganic phosphate (Pi) in soil is an important constraint to plant growth. In order to understand better the underlying mechanism of plant response to Pi, the response to phosphate starvation in Arabidopsis thaliana was investigated through use of Petri Nets, a formal language suitable for bio-modeling. A. thaliana displays a range of responses to deal with Pi starvation, but special attention was paid to root hair elongation in this study. A central player in the root hair pathway is the transcription factor ROOT HAIR DEFECTIVE6-LIKE 4(RSL4), which has been found to be upregulated during the Pi stress. A Petri Net was created which could simulate the gene regulatory networks responsible for the increase in root hair length, as well as the resulting increase in root hair length. Notably, discrepancies between the model and the literature suggested an important role for RSL2 in regulating RSL4. In the future, the net designed in the current study could be used as a platform to develop hypotheses about the interaction between RSL2 and RSL4. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Plant diseases

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