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2023 International Conference on computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Sidharta, Sidharta Heryadi, Yaya Lukas, Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University BINUS Graduated Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Currently, the performance of the police in Indonesia is often in the spotlight of the public with cases that occur, both on a national and regional scale, including personal experiences who also feel disappointed with the performance of the police. The cases, such as the rape of three children by a biological father in East Luwu, and the barrage of other cases that have occurred, in their handling have left the public disappointed, giving rise to the hashtag percumlaporpolisi on social media, especially on twitter. This hashtag became trending and was widely responded to by the public. Using free hashtag keywords, tweet data is collected using Twitter's API for sentiment analysis. The datasets obtained from the crawling results is the latest data with a total of 100 datasets. This study applies the naïve bayes algorithm using textblob which aims to determine the value of polarity and subjectivity. From the results of the analysis carried out, the words that appear most often are useless police, police chief, and policeman. While the results of the sentiment analysis that has been carried out are 40 percent positive sentiment, 40 percent are neutral sentiment and 10 percent are negative sentiment from the hashtags used. From these results, according to the keywords used, the percentage of negative sentiment should be greater than positive and neutral sentiment. It is necessary to conduct a more in-depth study related to the model used in the next research. © 2023 IEEE.

关键词： Sentiment analysis

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Synthetic Batik Pattern Generator Using Wasserstein Generative Adversarial Network with Gradient Penalty 6

Synthetic Batik Pattern Generator Using Wasserstein Generati...

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6th International Seminar on Research of Information Technology and Intelligent systems, ISRITI 2023

作者： Andriadi, Kus Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Yogyakarta55281 Indonesia

ISBN: (纸本)9798350358346

Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among the batik making techniques that are widely used are hand-written, stamping, and printing. Batik motifs have been widely used as research material, especially in the field of artificial intelligence. The diverse appearance of batik motifs has attracted many researchers to carry out research on making synthetic batik patterns, one of which uses a Generative Adversarial Network. This paper presents a synthetic batik pattern model based on the Wasserstein Generative Adversarial Network with Gradient Penalty. This model has been proven to create new synthetic batik patterns quite well and almost identical with images provided in the dataset, with the notes if the dataset provided is large. © 2023 IEEE.

关键词： Generative adversarial networks

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Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

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7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of engineering & Technology 2023.

关键词： Support vector machines

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QoS Based Cloud Security Evaluation Using Neuro Fuzzy Model

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computers, Materials & Continua 2022年第1期70卷 1127-1140页

作者： Nadia Tabassum Tahir Alyas Muhammad Hamid Muhammad Saleem Saadia Malik Syeda Binish Zahra Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Statistics and Computer science University of veterinary and animal sciencesLahore54000Pakistan Department of Industrial Engineering Faculty of EngineeringRabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology-RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia

Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network,and users can use them at any *** assessing and choosing cloud providers,however,customers confront the variety and difficulty of quality of service(QoS).To increase customer retention and engagement success rates,it is critical to research and develops an accurate and objective evaluation *** is the emerging environment for distributed services at various *** to the benefits of this environment,globally cloud is being taken as a standard environment for individuals as well as for the corporate sector as it reduces capital expenditure and provides secure,accessible,and manageable services to all stakeholders but Cloud computing has security challenges,including vulnerability for clients and association acknowledgment,that delay the rapid adoption of computing *** of resources in the Cloud is difficult because resources provide numerous measures of quality of *** this paper,the proposed resource allocation approach is based on attribute QoS Scoring that takes into account parameters the reputation of the asset,task completion time,task completion ratio,and resource *** article is focused on the cloud service’s security,cloud reliability,and could *** this paper,the machine learning algorithm neuro-fuzzy has been used to address the cloud security issues to measure the parameter security and privacy,trust *** findings reveal that the ANFIS-dependent parameters are primarily designed to discern anomalies in cloud security and features output normally yields better results and guarantees data consistency and computational power.

关键词： Cloud computing performance quality of service machine learning neuro-fuzzy

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A conceptional structure for challenging the rebound effect of the product-service system 33

A conceptional structure for challenging the rebound effect ...

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33rd CIRP Design Conference

作者： Alfarisi, Salman Mitake, Yuya Tsutsui, Yusuke Wang, Hanfei Shimomura, Yoshiki Faculty of Systems Design Tokyo Metropolitan University Tokyo191-0065 Japan Human Augmentation Research Center National Institute of Advanced Industrial Science and Technology Chiba277-0882 Japan Faculty of Computer Science and Systems Engineering Okayama Prefectural University 719-1197 Japan

The product obsolescence rate is one of the product-service system rebound effect issues. Obsolescence can be generated by both planned obsolescence and post-production obsolescence. Planned obsolescence can increase sales and revenue artificially. However, the pattern of planned obsolescence has demonstrated that obsolescence is no longer limited to functional obsolescence but rather rapidly evolves to include quality and aesthetic aspects. Moreover, post-production consuming behaviours hasten the rate of product obsolescence, especially in the absence of ownership. At this point, rapid obsolescence contradicts the spirit of the Product-service System's (PSS) value proposition. During the stage of value co-creation, such topics must be considered. According to research on PSS and the co-creation process, the co-creation of value is inherent to PSS. Nevertheless, managing the process of value co-creation is another challenge. In addition, decision-making should also be prevented from being dominated by a high degree of centralisation. This paper presents a preliminary investigation into constructing a framework for managing the value co-creation process and decision-making to prevent the rebound effect based on conceptual review. This study identifies methods applicable to the co-creation procedure. A conceptional structure of co-creation of value and decision-making is presented. © 2023 The Authors. Published by Elsevier B.V.

关键词： Obsolescence

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Design and Analysis of Microwave Sensor for Alcohol Concentration with Microstrip Band Stop Filter

Design and Analysis of Microwave Sensor for Alcohol Concentr...

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2023 International Conference on Power, Energy and Innovations, ICPEI 2023

作者： Saeng-On, P. Srisawat, S. Phromloungsri, R. Summatta, C. Sonasang, S. Prabpal, P. Nakhon Phanom University Faculty of Industrial Technology Electronic Technology Nakhon Phanom Thailand UdonThani Rajabhat University Faculty of Technology Computer and Communication Engineering Udon Thani Thailand Nakhon Phanom University Faculty of Industrial Technology Industrial Technology Nakhon Phanom Thailand Sakon Nakhon Technical College Institute of Vocational Education Electrical Technology Sakon Nakhon Thailand

ISBN: (纸本)9798350344585

This paper proposed the design and analysis of the microwave sensor (MS) in line with the microstrip band stop filter (MBSF). The research includes the measurement of alcohol concentrations ranging from 0 to 55%. The measurement was conducted using a network analyzer operating from 100 kHz to 4.5 GHz. The measurements were the insertion loss (S21). The obtained results indicated differences in frequency shifts. The results of the frequency values were observed to be 0, 0.06, 0.14, 0.17, 0.21, 0.23, 0.25, 0.27, and 0.31 GHz, respectively. The percentage correlation between the frequency shift in the insertion loss and frequency was evident, even after adjusting the range of the tested samples. © 2023 IEEE.

关键词： Microwave sensors

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CCPred: Global and population-specific colorectal cancer prediction and metagenomic biomarker identification at different molecular levels using machine learning techniques

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computers in Biology and Medicine 2024年 182卷 109098-109098页

作者： Bakir-Gungor, Burcu Temiz, Mustafa Inal, Yasin Cicekyurt, Emre Yousef, Malik Department of Computer Engineering Faculty of Engineering Abdullah Gul University Kayseri38080 Turkey Department of Electrical and Computer Engineering Faculty of Engineering Abdullah Gul University Kayseri38080 Turkey Department of Information Systems Zefat Academic College Zefat13206 Israel Zefat Academic College Israel

Colorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths. Recent research highlights the pivotal role of the gut microbiota in CRC development and progression. Understanding the complex interplay between disease development and metagenomic data is essential for CRC diagnosis and treatment. Current computational models employ machine learning to identify metagenomic biomarkers associated with CRC, yet there is a need to improve their accuracy through a holistic biological knowledge perspective. This study aims to evaluate CRC-associated metagenomic data at species, enzymes, and pathway levels via conducting global and population-specific analyses. These analyses utilize relative abundance values from human gut microbiome sequencing data and robust classification models are built for disease prediction and biomarker identification. For global CRC prediction and biomarker identification, the features that are identified by SelectKBest (SKB), Information Gain (IG), and Extreme Gradient Boosting (XGBoost) methods are combined. Population-based analysis includes within-population, leave-one-dataset-out (LODO) and cross-population approaches. Four classification algorithms are employed for CRC classification. Random Forest achieved an AUC of 0.83 for species data, 0.78 for enzyme data and 0.76 for pathway data globally. On the global scale, potential taxonomic biomarkers include ruthenibacterium lactatiformanas;enzyme biomarkers include RNA 2′ 3′ cyclic 3′ phosphodiesterase;and pathway biomarkers include pyruvate fermentation to acetone pathway. This study underscores the potential of machine learning models trained on metagenomic data for improved disease prediction and biomarker discovery. The proposed model and associated files are available at https://***/TemizMus/CCPRED. © 2024 Elsevier Ltd

关键词： Plant diseases

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The Effect of Balanced and Imbalanced Dataset on Voice Pathology Detection Using Online Sequential Extreme Learning Machine (OSELM)

The Effect of Balanced and Imbalanced Dataset on Voice Patho...

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Advanced Telecommunication and Networking Technologies (ATNT), IEEE International Conference on

作者： N. F. S. Md Sazihan N. M. Abdul Latiff N. N. N. Abd Malik S. Mashohor K. Alaghbari F. T. AL-Dhief Faculty of Electrical Engineering Universiti Teknolgi Malaysia UTM Johor Bahru Malaysia Dept. of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia Serdang Malaysia

ISBN: (数字)9798350353501

ISBN: (纸本)9798350353518

Voice pathology detection is crucial for early diagnosis and treatment of vocal disorders. This research studies the effect of balanced and imbalanced datasets on the accuracy of voice pathology detection using Online Sequential Extreme Learning Machine (OSELM) on the Saarbruecken Voice Database (SVD). The dataset's balance has been identified as having a significant influence on the performance of the machine learning models. In this work, the voice signals from vowel /a/ of pathology and non-pathology classes are taken from SVD. The dataset is divided into two category which are balanced and imbalanced dataset. Then, the features of the voice signals are then extracted using Mel-Frequency Cepstral Coefficient (MFCC) and fed into classifier called OSELM. The result of balanced and imbalanced dataset is assessed for its accuracy. The results showed that the model achieved an accuracy of 66.25% with the balanced dataset compared to 48% for the imbalanced dataset. These findings highlight the importance of addressing dataset balance to enhance the reliability and effectiveness of voice pathology detection systems.

关键词： Pathology Accuracy Extreme learning machines Databases Machine learning Feature extraction Communications technology Telecommunication network reliability Mel frequency cepstral coefficient

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Sharp analysis of EM for learning mixtures of pairwise differences

arXiv

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arXiv 2023年

作者： Dhawan, Abhishek Mao, Cheng Pananjady, Ashwin School of Mathematics School of Industrial and Systems Engineering School of Electrical and Computer Engineering Georgia Institute of Technology United States

We consider a symmetric mixture of linear regressions with random samples from the pairwise comparison design, which can be seen as a noisy version of a type of Euclidean distance geometry problem. We analyze the expectation-maximization (EM) algorithm locally around the ground truth and establish that the sequence converges linearly, providing an l∞-norm guarantee on the estimation error of the iterates. Furthermore, we show that the limit of the EM sequence achieves the sharp rate of estimation in the l2-norm, matching the information-theoretically optimal constant. We also argue through simulation that convergence from a random initialization is much more delicate in this setting, and does not appear to occur in general. Our results show that the EM algorithm can exhibit several unique behaviors when the covariate distribution is suitably structured. Copyright © 2023, The Authors. All rights reserved.

关键词： Maximum principle

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Development of the Function Check Stability of Digital Media Receivers using Interference Mitigation Techniques

Development of the Function Check Stability of Digital Media...

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International electrical engineering Congress (iEECON)

作者： Pontakan Lhuangchon Chaiyong Soemphol Department of Electrical and Computer Engineering Faculty of Engineering at Mahasarakham University Mahasarakham Thailand Faculty of Engineering at Mahasarakham University Research Unit for Computational Electromagnetics and Optical Systems (CEMOS) Mahasarakham Thailand

ISBN: (数字)9798350383591

ISBN: (纸本)9798350383607

This study explores techniques to mitigate interference in assessing functions related to AM radio wave signals in digital media receivers. Signal transmission cable testing focused on BNC RG59 75-ohm cables with length of 300 mm. Six methods were employed: Method 1 used a Ferrite core, Method 2 used copper tape, Method 3 connected a grounding wire, Method 4 combined grounding wire connection with a Ferrite core, Method 5 combined grounding wire connection with copper tape, and Method 6 combined grounding wire connection with both a Ferrite Core and copper tape. The result has been shown that Method 6 yielded optimal results, with AM 1000 kHz Usable Sens, AM Interstation Noise L, and AM Interstation Noise R functions differing from reference values by −3.53 dBm, −5.05 dBm, and −5.26 dBm, respectively, emphasizing its efficacy in enhancing the assessed functions.

关键词： Ferrites Grounding Wires Noise Receivers Interference Media

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