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Real Time Chest X-Ray Interpretation Applying Vision Transformer for Tuberculosis Detection

Real Time Chest X-Ray Interpretation Applying Vision Transfo...

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2024 International Conference on computer Engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Irhamsyah, Muhammad Roslidar Yunidar Al Lail Qadrillah, M. Nasaruddin Arnia, Fitri Munadi, Khairul Universitas Syiah Kuala Post Graduate Program in Engineering Banda Aceh2311 Indonesia Faculty of Engineering Department of Electrical and Computer Engineering 2311 Indonesia

ISBN: (纸本)9798350368802

Tuberculosis (TB) is an infectious disease that can attack the lungs and other organs. In the diagnosis of TB, the interpretation of X-ray radiological images requires special skills from medical specialists. However, the lack of experience of medical personnel and focus on X-ray examinations can be a challenge for radiologists because it has the potential to cause diagnostic errors in image interpretation. Therefore, we proposed a web-based application of real-time chest X-ray interpreter by integrating the deep learning model of Vision Transformer (ViT) to interpret chest X-ray images. The inference model was trained and tested on 652 normal and 652 tuberculosis X-ray images. The data preprocessing of Contrast Adaptive Histogram Equalization (CLAHE) was implemented to increase chest X-ray image contrast as well as inference model performance. The proposed real time system can inteprete the tested chest x-ray images with an accuracy of 95% and with simulation duration time of 4.7 seconds. © 2024 IEEE.

关键词： Diagnosis

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Enhancing Fake News Detection with Sentiment Analysis Using Machine Learning 7

Enhancing Fake News Detection with Sentiment Analysis Using ...

引用

7th International Conference on Electronics, Materials Engineering and Nano-Technology, IEMENTech 2023

作者： Bose, Shreea Roy, Reek St Xavier's College Department of Post Graduate and Research Computer Science Kolkata India Belda College Department of Computer Science Paschim Medinipur India

ISBN: (纸本)9798350305517

In the digital age we live in today, fake news has become a serious problem because it has the power to sway public opinion, affect policy decisions, and upend social harmony. Sentiment analysis, which evaluates the content's emotional tone, is essential for spotting and stopping the spread of false information. In this work, we leverage machine learning techniques for sentiment analysis to increase the detection accuracy of fake news. To scrutinize the affective milieu present in news pieces and headlines, we investigate the amalgamation of various sentiment analysis instruments, such as VADER, TextBlob, and NLTK. By translating textual input into numerical properties, TF-IDF vectorization is utilized in conjunction with sentiment analysis to increase the predictive power of machine learning models. Enhancing the feature set through the use of TF-IDF vectorization is essential for teaching machine learning models to discern between authentic and fraudulent news. As classification models, Decision trees, SVM, and Logistic regression are used;each has advantages when it comes to processing tasks involving sentiment-based classification. In this study, we try to classify the emotions that the fake news mainly shows after the prediction. We have seen the trend that mainly Negative emotion is conveyed with fake news. The models have been compared and we're getting 98% accuracy. © 2023 IEEE.

关键词： Decision trees

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Variational quantum neural network with optimized ansatz for predicting malignant ventricular arrhythmias 9th

Variational quantum neural network with optimized ansatz for...

引用

9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Dominic, Nicholas Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

Preventive strategies should be the utmost priority when dealing with diverse patients suffering from malignant ventricular arrhythmia (MVA) that can lead to sudden cardiac death (SCD). Electrocardiogram (ECG) data is commonly used as a predictor for MVA predictive models. In this study, all ECG signals from MIT-BIH databases were fragmented into five-minute durations with a frequency sampling of 128 Hz. To solve the absence of hybrid optimizations in Machine Learning (ML) models, a novel Variational Quantum Neural Network (VQNN) was invented. Empowered by deep learning capabilities and optimized quantum circuits design, VQNN achieved remarkable performances designated by an accuracy of up to 95.1%, a perfect 100% recall, and a 95.2% score of the area under the Receiver Operating Characteristic curve (AUC ROC) with Conjugate Gradient as an optimizer and EfficientSU2 as a quantum ansatz. Despite the susceptibility to quantum noise, this research settles a new trajectory of utilizing quantum variational algorithms to predict and expand its applicability for MVA cases. © 2024 The Authors.

关键词： Quantum computers

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Analyzing the Impact of Service Design on Maintainability Factor in Microservices Architecture 15

Analyzing the Impact of Service Design on Maintainability Fa...

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15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Gintoro Gaol, Ford Lumban Soeparno, Haryono Arifin, Yulyani Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350383829

Applications designed utilizing Microservices Architecture (MSA) provide the desirable trait of good maintainability. To ensure optimal maintainability, it is important to provide services that are suitable and adhere to prescribed rules. Multiple aspects must be taken into account while designing services to ensure optimal maintainability. The objective of this study is to examine the elements that impact the capacity to sustain and improve maintainability in service design, ultimately resulting in an application that possesses strong maintainability. The Systematic Literature Review (SLR) will be utilized to identify variables and strategies for their enhancement, by examining pertinent publications on the subject. After examining 45 publications, the study discovered 8 elements and 14 solutions that can enhance the highlighted parameters throughout the services design process. The outcomes of this systematic literature review (SLR) are anticipated to give valuable insights to application developers, empowering them to generate service designs that exhibit commendable maintainability for the developed applications. © 2023 IEEE.

关键词： Maintainability

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A Survey of Refactoring Techniques to Maximize Code Coverage Metric 15

A Survey of Refactoring Techniques to Maximize Code Coverage...

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15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Simatupang, Johannes Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350383829

Refasctoring is a technique used in software development to improve the quality of code without changing its functionality. One metric that is often used to measure code quality is Code Coverage. This study aims to examine refactoring techniques that can maximize Code Coverage Metric. Through the study, identification, evaluation, and summary of empirical evidence from various literature sources are carried out. The results of this study provide guidance on effective refactoring techniques to improve Code Coverage as well as other positive impacts for software development. There are ten refactoring techniques that can be used to improve Code Coverage Metrics in software testing. © 2023 IEEE.

关键词： Software testing

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COCOMO II Analysis of Developing Multi-Account Partner Software for Crypto Exchange 15

COCOMO II Analysis of Developing Multi-Account Partner Softw...

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15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Darmawan, Oscar Adam Gaol, Ford Lumban Soeparno, Haryono Arifin, Yulyani Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350383829

The technique of calculating the work required for software development is known as software development estimation. The objective cost estimating technique for organizing and carrying out Multi Account Partner (MAP) software projects, COCOMO II, was employed in this study. The MAP software is a software architecture designed to support brokerage cryptocurrency exchanges using the order book and liquidity of established crypto exchanges. This research uses data sets from MAP project development at Indonesia Crypto Exchange Platform. It aims to create a software cost estimation model for MAP software using COCOMO II so that the resulting estimation model can be used as input or reference for estimates of subsequent MAP software development. The result estimated that MAP software finished in about four to five months, with a price range for software development of $7,441 to $8,780. Further research is needed with datasets from other crypto exchanges tested to increase cost estimation accuracy using COCOMO II. © 2023 IEEE.

关键词： Blockchain

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Multi-Criteria based Decision Model for Evaluation 6

Multi-Criteria based Decision Model for Evaluation

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

作者： Utama, Ditdit Nugeraha Bin Widayat, Muhamad Akbar Bina Nusantara University BINUS Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350358346

Addressing multiple criteria and parameter issues in computer modelling presents a significant challenge. Several factors including data types, parameter behaviours, and purposes, must be taken into account to enhance computer modelling capability;particularly in evaluation cases. Through the utilization of a multi-criteria and method approach, a decision model was effectively developed to assess a case of environmental sustainability level of a building. One method operated in the study is the curve method for handling membership function form in realizing fuzzy logic. This innovative model demonstrates superior performance. It achieves an impressive accuracy rate of 96%, surpassing the previous model that employed a trapezoidal approach to describe fuzzy membership functions hy 1%. © 2023 IEEE.

关键词： Fuzzy logic

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An Object Oriented Floating Fuzzy Decision Model for Evaluating the Student Performance 6

An Object Oriented Floating Fuzzy Decision Model for Evaluat...

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

作者： Utama, Ditdit Nugeraha Bina Nusantara University BINUS Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350358346

The concept of object-oriented (OO) serves is a fundamental approach in the development of models. The stages associated with this method contribute significantly to ensuring that the resulting model is both lucid and transparent. The primary objective of the study is to create a decision model for evaluating student performance. Floating fuzzy logic (FFL) is employed as a technique to handle fluctuating data within the model. Moreover, OO conception plays a central role in analyzing, designing, and constructing the model through the utilization of four distinct types of Unified Modeling Language (UML) diagrams: object, activity, state-machine, and sequence diagrams. The model itself is crafted using the Python programming language and executed in the Google Colab platform. Additionally, this model has the capability to simulate changes in students' performance on a semester-by -semester basis, exhibiting a variance of 15 % when compared to the conventional fuzzy logic model. © 2023 IEEE.

关键词： Fuzzy logic

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Irrigation Control System for Seedlings Based on the Internet of Things 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： de Carvalho, André Kusuma, Gede Putra Handoyo, Alif Tri Department of Computer Science BINUS Graduate Program—Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

The agricultural activities in the Vocational School of Agricultural Engineering (ESTVA) in Timor-Leste requires large quantities of water with high availability for the production and cultivation of plants. However, the crop results sometimes decrease due to challenges problem faced by the management of the water resources. This study aims to design an Internet of Things (IoT) based automatic control system to control water supply and maintain soil moisture conditions effectively. The evaluation of manual and automatic irrigation systems during the 21 days trial shows that the automatic system provides stable utilization of water with watering frequency of 274 occurs only in 12 days, with an amount of total watering of 35.3 L. Meanwhile, the manual system uses up to 49.8 L of water, which is 14.5 L more than the water spent by the automatic system. The results of the evaluation also indicate that automatic system obtains the average moisture value of 509 with a standard deviation of 63, which is smaller than the manual system that obtains an average moisture value of 559 and a significant standard deviation of 126. From these results, the automatic system is more effective in maintaining the soil moisture level and yet requires less water compared to the manual watering system. Furthermore, the quality and productivity of the growth of mustard seedlings with automatic system prove that the seeds are more stable and feasible to continue transplanting since the automatic system produces 12 more mustard trees compared to the manual system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Soil moisture

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Easy Data Augmentation for Handling Imbalanced Data in Fake News Detection 1

Easy Data Augmentation for Handling Imbalanced Data in Fake ...

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

作者： Pradana, Rilo Chandra Joddy, Setiawan Girsang, Abba Suganda Binus Graduate Program-Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350360554

Detecting fake news in the digital era is challenging due to the proliferation of misinformation. One of the crucial is-sues in this domain is the inherent class imbalance, where genuine news articles significantly outnumber fake ones. This imbalance severely hampers the performance of machine and deep learning models in accurately identifying fake news. Consequently, there is a compelling need to address this problem effectively. In this study, we delve into fake news detection and tackle the critical issue of imbalanced data. We investigate the application of Easy Data Augmentation (EDA) techniques, including back-translation, random insertion, random deletion, and random swap to mitigate the adverse effects of imbalanced data. This study focuses on employing these techniques in conjunction with a deep learning framework, specifically a Bidirectional Long Short-Term Memory (BiLSTM) architecture. The results of the EDA techniques will be systematically compared to see their effectiveness and their impacts on model performance. This study reveals that various EDA techniques, when coupled with a BiLSTM architecture, yield significant improvements in fake news detection. Among the experiments, it shows that Random Insertion, with an impressive accuracy rate of 81.68%, a precision score of 89.38%, and an F1-Score of 87.77% emerges as the most promising technique. The study also highlights the exceptional potential of Back-translation stands out with an 87.16% recall performance. © 2023 IEEE.

关键词： Long short-term memory

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