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Solving Estimation Problems Using Minimax Polynomials and Gröbner Bases 10

Solving Estimation Problems Using Minimax Polynomials and Gr...

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10th International Symposium on Symbolic Computation in Software science - Work in Progress Workshop, SCSS 2024 WiP

作者： Kuramochi, Kenta Terui, Akira Mikawa, Masahiko Master's Program in Mathematics Graduate School of Science and Technology University of Tsukuba Tsukuba305-8571 Japan Institute of Pure and Applied Sciences University of Tsukuba Tsukuba305-8571 Japan Institute of Library Information and Media Science University of Tsukuba Tsukuba305-8550 Japan

We propose a method for solving the speech direction estimation problem by computer algebra. The method is based on the function approximation using the minimax polynomial. The minimax polynomial is obtained by an iterative method called the Remez exchange algorithm, in which Gröbner bases computation is employed. We present an effective way to compute the minimax polynomial using Gröbner bases. © 2024 CEUR-WS. All rights reserved.

关键词： Iterative methods

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Mobile Application as Community Social Media 6

Mobile Application as Community Social Media

引用

6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Pahlevi, Teuku Ryan Haryanto, Johannes Adha, Rahmat Alfian, Bayu Warnars, Harco Leslie Hendric Spits Widiono, Rahayu Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Binus Online Learning Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350398496

Today's society is different from the past, where the speed of the internet is getting more sophisticated, and the existing gadget technology is getting faster, and of course, this is also changing the lifestyle of today's people, which of course almost half of their daily life is spent in front of gadgets. On the one hand, this is undoubtedly very good and supports humans in carrying out their daily life activities, but on the other hand, this raises new problems where humans start to lack time to communicate and socialize with each other and often making them stressed and anxious because they are already tired and do not know how to socialize anymore. This paper begins with a model and implementation of a very simple mobile application that behaves as a social media inspired by *** as a social media for academics. The design of this mobile application is done by using use case diagrams to describe existing processes and class diagrams to describe class relationships. © 2023 IEEE.

关键词： Social networking (online)

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Preventing Cyber Crime in Electronic Medical Records Using Encryption Data 1

Preventing Cyber Crime in Electronic Medical Records Using E...

引用

1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Budiman Mantoro, Teddy Ratmono, Barito Mulyo Persadha, Pratama Dahlian National Intelligence College Post Graduate Program of Medical Intelligence Bogor Indonesia Sampoerna University Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

With the advancement of technology, information systems have become increasingly necessary in almost all areas, including healthcare. One of the technologies used to facilitate this progress is electronic medical records (EMRs). Although EMRs have improved service delivery and patient care in healthcare, they also pose risks to patient data due to cybercrime attacks, which can result in data theft and alteration of medical records. Medical identity theft has become a major issue in healthcare systems around the world, While technology has been beneficial in improving service delivery and patient care in healthcare, it has also introduced numerous risks to patient safety and ultimately impacted patient health. Cybersecurity issues have advanced with technology, thus increasing the rate at which medical identity thefts occur. The healthcare industry lags in curbing cybersecurity issues, and thus, it is vulnerable to many cyberattacks. To address these risks, techniques, and methods are needed to ensure the security of EMR systems against cybercrime attacks. This study used a literature review method and identified eleven articles that met inclusion and exclusion criteria. Through analysis of these articles, several techniques and methods were identified to secure the privacy system in EMRs, such as mIBE-AES, DES, and RSA methods. The literature review revealed that Encryption Data is the safest technique to use, as it is standardized, widely accessible, and cost-effective. Furthermore, mIBE-AES is the safest method for EMRs because it is both secure and efficient for storing medical record documents. Performance evaluations were conducted to test the level of security against cybercrime attacks. © 2023 IEEE.

关键词： Cryptography

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Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

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

ISBN: (纸本)9781665468763

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy. © 2022 IEEE.

关键词： Sentiment analysis

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Towards Trajectory Planning of a Robot Manipulator with computer Algebra using Bézier Curves for Obstacle Avoidance 10

Towards Trajectory Planning of a Robot Manipulator with Comp...

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10th International Symposium on Symbolic Computation in Software science - Work in Progress Workshop, SCSS 2024 WiP

作者： Hatakeyama, Ryo Terui, Akira Mikawa, Masahiko Master's Program in Mathematics Graduate School of Science and Technology University of Tsukuba Tsukuba305-8571 Japan Institute of Pure and Applied Sciences University of Tsukuba Tsukuba305-8571 Japan Institute of Library Information and Media Science University of Tsukuba Tsukuba305-8550 Japan

This paper discusses the trajectory planning of a robot manipulator with computer algebra. In the operation of robot manipulators, it is important to make the trajectory of the end effector so that it does not collide with obstacles. For this purpose, we have proposed a method of generating a method of trajectory planning using cubic spline curves. However, the method has the disadvantage that the trajectory may not be included in the feasible region of the manipulator, thus an extra test for the inclusion of the curve is needed. In this paper, we propose a new method of generating a trajectory using Bézier curves, which is guaranteed to be included in the feasible region. © 2024 CEUR-WS. All rights reserved.

关键词： Trajectories

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Long short-term memory for hate speech and abusive language detection on Indonesian YouTube comment section 11

Long short-term memory for hate speech and abusive language ...

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2021 11th International Workshop on computer science and Engineering, WCSE 2021

作者： Salim, Calvin Erico Rudy Suhartono, Derwin Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9789811817915

Hate speech is one of the most challenging problem internet is facing today. With increasing numbers of users online, hate speech also rise and takes time to be classified manually particularly in languages other than English. This research examines hate speech detection problem in form of Bahasa Indonesia. Millions of comments and text posts are added to various social media and discussion platforms. Manual classification in all of the internet as hate speech and offensive language is a near impossible and time-consuming task. This research uses Long Short-Term Memory (LSTM) and Bidirectional Long Short Term Memory (Bi-LSTM) for the method of classifying hate speech and abusive language. The final accuracy is 88,44% by using 200 neurons with Bi-LSTM method. Most common challenges are different languages, out of vocabulary words, long range dependencies, and sarcasm. © 2021 11th International Workshop on computer science and Engineering, WCSE 2021. All Rights Reserved.

关键词： Long short-term memory

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Protein Secondary Structure Prediction using N-Grams and 1-Dimensional Convolutional Neural Network

Protein Secondary Structure Prediction using N-Grams and 1-D...

引用

International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Annisa Rizqiana Afiahayati Department of Computer Science and Electronics Master Program in Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

In this study, we initiated an approach to predict Protein Secondary Structure Prediction (PSSP) by using n-grams modeling, namely $n$ adjacent amino acid sequences, to represent the amino acid sequence and 1-Dimensional Convolutional Neural Network (CNN). We compare n-grams with a one-hot encoding approach and find that n-grams provide better performance. The analysis results show that bigrams are more effective than trigrams in describing protein amino acid sequence patterns. We also combine it with the PSSM profile feature to improve model performance. The results of this study reveal that the n-grams approach, especially bigrams, in combination with PSSM, can produce more accurate protein secondary structure predictions than previous models, with superior accuracy evaluations of Q8 68.1 % and Q3 82.75 % on the CB513 dataset.

关键词： Proteins Accuracy Convolution Neural networks Predictive models Amino acids Encoding Convolutional neural networks Bioinformatics Kernel

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Explainable Supervised Method for Genetics Ancestry Estimation 1

Explainable Supervised Method for Genetics Ancestry Estimati...

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1st International Conference on computer science and Artificial Intelligence, ICCSAI 2021

作者： Budiarto, Arif Pardamean, Bens Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9781728133331

Ancestry estimation is one crucial stage in genomic research. It generates scores that represent the admixed genetics profile as the result of human evolution. In the previous research, we implemented multiple unsupervised methods to estimate these scores from large genomics data obtained from the 1000 Genome Project. These methods were limited to only cluster the samples to the five global populations in the dataset. The main challenge arose when implementing these methods to cluster the samples into more specific subpopulations. In this paper, we proposed a supervised approach to answer this challenge. Two state-of-the-art supervised machine learning methods, XGBoost and Deep Neural Network (DNN), were applied to the same dataset. These methods were aimed to classify samples, both into five main populations and also into 26 sub-populations. In the first classification task, both methods achieved similar results to our previous unsupervised approach. Interestingly, for the second classification task, which posses a relatively higher difficulty, DNN yielded better performance in the train, validation, and test dataset, despite its overfitting problem. Furthermore, the feature importance scores from each model were calculated using Shapley Additive Explanations (SHAP) method. Finally, 11 overlapped SNPs from all models were evaluated based on the reported Minor Allele Frequency (MAF) from the 1000 Genome Project. Overall, only using these 11 SNPs, we could differentiate each population in regards to its average MAF. © 2021 IEEE.

关键词： Genome

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Literature Review: Analysis of Essential Metadata Attributes of Digital Goods for Transaction in The Virtual World 9

Literature Review: Analysis of Essential Metadata Attributes...

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Martha, Gede Indra Raditya Prabowo, Harjanto Gaol, Ford Lumban Wiputra, Richard BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

In online-based virtual worlds such as Metaverse, Online Games, and other online digital spaces, the virtual/digital goods (digital items / digital assets) are fundamental things that must be available to be able to do business & create an economy in the virtual world through monetization & transactions from these digital goods. This research focuses on summarizing and exploring the attributes used in digital goods in the virtual world by extracting attributes in digital goods from other related studies using the Systematic Literature Review methodology & PRISMA Framework comprehensively so that it can be a reference for developers in designing the properties and functions of digital goods in the virtual world that are being developed, which in this case will be in the form of an NFT in the future. Based on research that has been carried out, 3 essential metadata attributes have the most influence on transactions, number 1 Visual Design / Aesthetic (Representative), number 2 Effect (Utilities), and number 3 Statistics / Performance (Utilities) which must be considered in developing/making digital goods in the form of NFTs in the virtual world so that the value of digital goods can attract users to buy or transact them in the virtual world. © 2024 IEEE.

关键词： Virtual environments

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Imagery contents descriptions for People with visual impairments 23

Imagery contents descriptions for People with visual impairm...

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Proceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems

作者： Alessandra Helena Jandrey Duncan Dubugras Alcoba Ruiz Milene Selbach Silveira School of Technology - Graduate Program in Computer Science PUCRS Brazil

ISBN: (纸本)9798400717154

Image descriptions are crucial in assisting individuals without eyesight by providing verbal representations of visual content. While manual and Artificial Intelligence (AI)-generated descriptions exist, automatic description generators have not fully met the needs of visually impaired People. In this study, we have examined the problems related to image descriptions reported in existing literature using the Snowballing technique. Through this method, we have identified thirteen issues, including ethical concerns surrounding physical appearance, gender and identity, race, and disability. Furthermore, we have identified five reasons why sighted Individuals often fail to provide descriptions for visual content, highlighting the necessity for accessibility campaigns that raise awareness about the social significance of descriptive sentences. We conducted interviews with eight low-vision volunteers, in which we analyzed the characteristics of descriptive sentences for 25 indoor images and gathered participants’ expectations regarding image descriptions. As a result, we propose a set of Good Practices for writing descriptive sentences aimed to assist automatic tools and sighted Individuals in generating more satisfactory and high-quality image descriptions. We hope our results will emphasize the societal importance of imagery descriptions and inspire the community to pursue further interdisciplinary research to address the issues identified in our study.

关键词： Good practices Image descriptions Visually impaired People

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