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Multi-robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees

SN computer science 2024年第1期5卷 31页

作者： Mukhopadhyay, Shayok Umari, Hassan Koirala, Koshish Electrical & Computer Engineering and Computer Science Department University of New Haven 300 Boston Post Rd West Haven 06516 CT United States Department of Electrical Engineering American University of Sharjah Sharjah P.O. Box 26666 United Arab Emirates Mechatronics Engineering graduate program American University of Sharjah Sharjah P.O. Box 26666 United Arab Emirates

A map is necessary for tasks such as path planning or localization, which are common to mobile robot navigation. However, a map may be unavailable if the environment in which a robot navigates is unknown. Creating a map requires an exploration algorithm. Such algorithms guide robots to boundaries that separate known portions of a map from the unknown portions. Such boundaries are known as frontiers. There are image processing-based algorithms that detect frontiers. The authors’ previous work uses two, i.e., local and global, rapidly exploring random trees (RRTs) for two-dimensional exploration using a single robot. The present work applies the above to a multiagent system with three robots. A market-based strategy is used to allocate exploration tasks to the robots. Results show that the developed exploration strategy successfully explores a map in a reasonable amount of time compared to image processing-based approaches, and also reduces the map exploration cost. This strategy is readily usable for three-dimensional exploration with drones. It is also shown that the usage of a local frontier detector along with a global frontier detector helps reduce exploration time compared to simply using a global frontier detector alone. As an outline to future work, the paper also shows an extension of the proposed approach towards three-dimensional mapping using a single robot. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Exploration Mapping Multi-agent Navigation ROS RRT

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN)

Development of Detection Lung Disease Stand Alone System Bas...

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International Conference of computer and Informatics engineering (IC2IE)

作者： Edgar Caesar Liewarnata Yosica Mariana Sofyan Tan Suryadiputra Liawatimena Winda Astuti Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Product Design Program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification.

关键词： Training Accuracy Tuberculosis Pulmonary diseases Lungs Stethoscope Recording Convolutional neural networks Mel frequency cepstral coefficient Testing

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Mobile Based Brand and Car Type Detection Using Convolutional Neural Network 8

Mobile Based Brand and Car Type Detection Using Convolutiona...

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8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Ramadhan, Cahaya Saputra, Hasta Ragil Dewi, Ratna Sari Suharjito Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia Industrial Engineering Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

Although the parking lot is equipped with CCTV surveillance, car theft incidents still occur occasionally. These thieves exploit a loophole in the system that prevents the identification of the car's brand and model upon entering and exiting the parking lot using the same ticket. Therefore, the aim of this research is to develop a system capable of detecting the brand and model of cars. The study utilizes convolutional neural network technology and specifically focuses on the EfficientNet, MobileNet, and MobileNetV2 architectures due to their low resource requirements. Training images for the study are sourced from an online marketplace for used cars, with each of the 20 car brand and model variations consisting of 100 photographs. creates a model after being processed. For the prototype, the approach is put into practice through a mobile application. This study compares EfficientNet, MobileNetV1, and MobileNetV2 as the end result. EfficientNet scored 74%, MobileNetV1 74%, and MobileNetV2 66% on the test of accuracy. The accuracy increases to 80% after the EfficientNet has been tuned. © 2023 The Authors. Published by Elsevier B.V.

关键词： Convolutional Neural Network EfficientNet MobileNet V2 MobileNetV1 Parking system Transfer Learning

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A Smote-Based Churn Prediction System Using Machine Learning Techniques

A Smote-Based Churn Prediction System Using Machine Learning...

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2023 International Conference on science, engineering and Business for Sustainable Development Goals, SEB-SDG 2023

作者： Akinrotimi, Akinyemi Omololu Ogundokun, Roseline Oluwaseun Mabayoje, Modinat Abolore Oyekunle, Rafiat Ajibade Adebiyi, Marion Olubunmi Augustine University Department of Mathematics Sciences Computer Science Program Ilara-Epe Epe Nigeria Kaunas University of Technology Department of Multimedia Engineering Lithuania Landmark University Omu Aran Sdg 4. Quality Education Nigeria University of Ilorin Department of Computer Science Ilorin Nigeria University of Ilorin Department of Information and Communication Ilorin Nigeria Landmark University Omu-Aran Department of Computer Science Omu Aran Nigeria

ISBN: (纸本)9798350324785

The financial backbone of every telecommunications company is strictly made up of the number of customers patronizing the organization. Due to the high level of competition amongst existing telecommunication companies, customers sometimes leave, dropping the services of a particular one for the other. Predicting which subscribers may want to leave a telecommunications company and providing solutions to keep them from doing so, are the main objectives of customer churn prediction. Churn prediction helps classify consumers who are likely to move from one business to another. The ability to foresee churners before they leave has been increasingly useful in recent years, especially in light of increased competition among communications carriers. To compute churners for telecommunications providers, the study described in this paper used oversampling techniques to balance churn data and applied the dimensionality reduction technique to discover optimal features with a strong predictive ability for detecting would-be churners and non-churners. The model used Logistic Regression and the Naïve Bayes Classification Algorithm to implement comparative classification strategies. The performance levels of these strategies were compared using a Telecommunications Customer Churn data set, as well as performance metrics such as accuracy, sensitivity, and specificity. The Naïve Bayes Algorithm proves more efficient than its counterpart giving higher positive rate detection and a lower negative rate detection. © 2023 IEEE.

关键词： Forecasting

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Blockchain and API Development to Improve Relational Database Integrity and System Interoperability

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Procedia computer science 2023年 216卷 151-160页

作者： Andhika Naafi Ramadhan Kharisma Naufal Pane Kun Rifki Wardhana Suharjito Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia

Technological developments have resulted in a trend of cryptocurrencies that use a technology called blockchain to create and record all transactions made into a digital ledger. Along with the emergence of the trend of cryptocurrencies, this development has also resulted in crimes that hit the digital world, such as data leakage and cyber espionage. This threat can be prevented by applying blockchain technology to the database that has been used. Therefore, we need a system that can facilitate the use of blockchain technology and can process data from an existing relational database into a blockchain-based database. The system developed in this study was built with the FastAPI framework that uses the Python programming language and the React framework that uses the Javascript programming language. This system was tested using Katalon and Wireshark software to perform throughput testing and man-in-the-middle attacks. Evaluation of this system is assessed based on the average throughput time and also the results of Wireshark packet capture. The system designed in this research is expected to help overcome interoperability problems when using blockchain and improve relational database integrity. The results of the test show that the system is safe from man-in-the-middle attacks while sending data through API and has a faster throughput time than BigchainDB system by 4.151 seconds.

关键词： Blockchai Cybercrim Database Interoperability

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Cryptanalysis of Tripartite Authentication Protocol RFID/NFC Based on ECC 24

Cryptanalysis of Tripartite Authentication Protocol RFID/NFC...

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Proceedings of the 2024 5th International Conference on Big Data Economy and Information Management

作者： Min-Shiang Hwang Yung-Ling Chang Cheng-Ying Yang Chia-Chun Wu Department of Computer Science and Information Engineering Asia University Taichung Taiwan The Ph.D. Program in Artificial intelligence Asia University Taichung Taiwan Department of Computer Science University of Taipei Taipei Taiwan Department of Computer Science and Information Engineering National Quemoy University Kinmen Taiwan

ISBN: (纸本)9798400711862

Recently, Wei & Chen proposed a secure three-party mutual authentication protocol for RFID based on elliptic curve cryptography (ECC). Their approach can allow insecure communication between the reader and the backend, so their approach must achieve mutual authentication between the tag, reader, and backend. In addition, their method also satisfies the essential characteristics of RFID systems, such as confidentiality, anonymity, resistance to tracking attacks, and spoofing attacks. However, this article finds that its method cannot meet the mutual authentication and denial of service attacks.

关键词： ECC

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The Model Regularized CLAHE-CNN for the Traditional Script Character of Kaganga Bengkulu Recognition

The Model Regularized CLAHE-CNN for the Traditional Script C...

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International Conference on Informatics and Computing (ICIC)

作者： Erwin Dwika Putra Ermatita Ermatita Abdiansyah Abdiansyah Engineering Program Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Itis necessary to preserve the Kaganga script to be in demand again, especially by the younger generation today. Using and developing current technology, namely image processing techniques and deep learning, can be one way to reintroduce and preserve the culture of Kaganga script recognition. The purpose of this study is to implement the CNN method in recognizing the Kaganga script, observe the results of the implementation of the $\mathbf{L} 2$ regularization technique in reducing the overfitting process in CNN, and increase the accuracy of Kaganga script recognition using CLAHE and L2 regularization technique in CNN. The collected datasets are divided into test, valid, and training data. To acquire primary data for the Kaganga script, 50 respondents were involved. Each respondent was requested to write a Kaganga script on the provided paper. Organizations engaged in cultural heritage research are gathering data for this project: Yayasan Budaya Nusantara Digital (Jakarta), Yayasan Insani Mandiri Santani (Bengkulu), and Yayasan Sejahtera Bersama (Bengkulu). This study will evaluate using an accuracy measurement model, precision, and recall, which is included in the confusion matrix measurement model. In this research, we conducted four experiments, including CNN with L1, CNN with L2, CNN with dropout and the CLAHE-CNN with best regularization. From the experimental results, CLAHE-CNN with $L 2$ will be found that accuracy during the training stage gets a value of $100 \%$, accuracy during the validation stage gets a value of $85 \%$ and accuracy during the testing stage gets a value of $\mathbf{8 0. 7 5 \%}$

关键词： Training Handwriting recognition Accuracy Image recognition Training data Organizations Character recognition Informatics Testing Overfitting

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Transfer Learning Implementation for Batik Besurek Motifs Classification: A Comparative Study

Transfer Learning Implementation for Batik Besurek Motifs Cl...

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International Conference on Informatics and Computing (ICIC)

作者： Marissa Utami Ermatita Ermatita Abdiansyah Abdiansyah Engineering Program Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

This research discussion will be a comparative model proposal for introducing Besurek batik fabric by implementing MobileNet, ResNet50, InceptionV3 and VGG16. This research also analyzed the influence of augmentation data methods, namely rotation, zoom, width shift and height shift, on the performance of the Besurek batik fabric recognition algorithm based on accuracy, precision and recall results. The size of the batik besurek fabric motif image as an input image is $224 \times 224$ with three channels consisting of red, green, and blue, totalling five classes, namely kaligrafi, bunga rafflesia, burung kuau, lung paku and rambutan. The ratio of sharing training data and test data is 70:30. Accuracy evaluations are carried out on several epochs and data that have been shared. Based on the experiment, the accuracy value of MobileNetV2 can be obtained by training accuracy of $\mathbf{98.14 \%}$, validation accuracy of $\mathbf{94.60 \%}$, and testing accuracy of $\mathbf{96.46 \%}$. Then, the accuracy value of ResNet50 can be obtained by training accuracy at $\mathbf{99.60 \%}$, validation accuracy at 97.44, and testing accuracy at $\mathbf{98.12 \%}$. The accuracy value of InceptionV3 can be obtained by training accuracy at $96.35 \%$, validation accuracy at $96.59 \%$, and testing accuracy at $\mathbf{92.50 \%}$. Finally, the accuracy value of VGG16 can be obtained by training accuracy at $\mathbf{99.67 \%}$, validation accuracy at $96.02 \%$, and testing accuracy at $\mathbf{95.00 \%}$. The accuracy of VGG 16 can be concluded as the best model for Batik recognition.

关键词： Training Accuracy Lungs Transfer learning Training data Fabrics Proposals Informatics Testing Residual neural networks

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Bubble-pen lithography:Fundamentals and applications

Aggregate

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Aggregate 2022年第4期3卷 85-100页

作者： Pavana Siddhartha Kollipara Ritvik Mahendra Jingang Li Yuebing Zheng Walker Department of Mechanical Engineering The University of Texas at AustinAustinTexasUSA Department of Electrical and Computer Engineering The University of Texas at AustinAustinTexasUSA Material Science and Engineering Program Texas Materials InstituteThe University of Texas at AustinAustinTexasUSA

Developing on-chip functional devices requires reliable fabrication methods with high resolution for miniaturization,desired components for enhanced performance,and high throughput for fast prototyping and mass ***,laser-based bubble-pen lithography(BPL)has been developed to enable sub-micron linewidths,in situ synthesis of custom materials,and on-demand patterning for various functional components and *** exploits Marangoni convection induced by a laser-controlled microbubble to attract,accumulate,and immobilize particles,ions,and molecules onto different *** years have witnessed tremendous progress in theory,engineering,and application of BPL,which motivated us to write this ***,an overview of experimental demonstrations and theoretical understandings of BPL is ***,we discuss the advantages of BPL and its diverse applications in quantum dot displays,biological and chemical sensing,clinical diagnosis,nanoalloy synthesis,and *** conclude this review with our perspective on the challenges and future directions of BPL.

关键词： additive manufacturing capillary flow lithography marangoni convection microbubbles sensing

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Low-rank variational Bayes correction to the Laplace method

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2024年第1期25卷 3032-3056页

作者： Janet Van Niekerk Håvard Rue Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia

Approximate inference methods like the Laplace method, Laplace approximations and variational methods, amongst others, are popular methods when exact inference is not feasible due to the complexity of the model or the abundance of data. In this paper we propose a hybrid approximate method called Low-Rank Variational Bayes correction (VBC), that uses the Laplace method and subsequently a Variational Bayes correction in a lower dimension, to the joint posterior mean. The cost is essentially that of the Laplace method which ensures scalability of the method, in both model complexity and data size. Models with fixed and unknown hyperparameters are considered, for simulated and real examples, for small and large data sets.

关键词： information processing rule INLA Laplace LGM variational Bayes

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