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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Supriyanto, Catur Salam, Abu Zeniarja, Junta Wijaya, Adi Universitas Dian Nuswantoro Bachelor Program in Informatics Engineering Faculty of Computer Science Semarang Indonesia Universitas Indonesia Maju Department of Health Information Management Jakarta Indonesia

ISBN: (纸本)9798350339215

The field of dermatology faces considerable challenges when it comes to early detection of skin cancer. Our study focused on using different datasets, including original data, augmented data, and SMOTE oversampled data, to identify skin cancer. Our dataset consisted of images of skin lesions from the MNIST Skin Cancer dataset (HAM 10000), including samples of both cancerous and benign cases in the dataset. We employed data augmentation to expand the dataset's size and increase the diversity of skin lesion features. Furthermore, to tackle class imbalance in the dataset, we applied the SMOTE oversampling technique to generate synthetic samples for the under-represented group. With the original, augmented, and SMOTE oversampled datasets, we trained a Convolutional Neural Network (CNN) model. The performance of the model was evaluated using accuracy, recall, precision, and F1-score. The comparison between the results obtained from the original data, augmented data, and SMOTE oversampling data clearly revealed distinctions in performance. Our findings clearly demonstrate that employing data augmentation and SMOTE oversampling can significantly enhance the efficacy of skin cancer detection. © 2023 IEEE.

关键词： Neural network models

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Deep Reinforcement Learning for Network Security Applications With A Safety Guide

Deep Reinforcement Learning for Network Security Application...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Liu, Zhibo Lu, Xiaozhen Chen, Yuhan Xiao, Yilin Xiao, Liang Bu, Yanling Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China Xiamen University Department of Informatics and Communication Engineering Xiamen China

ISBN: (纸本)9798350345384

Most of the typical reinforcement learning algorithms help wireless devices choose the security policy such as the moving strategy and communication policy by exploring all the possible state-action pairs including the risky policies that cause a severe collision or network disaster. In this paper, we design a safe reinforcement learning algorithm for safety-critical applications (e.g., intelligent transportation systems) to guide the learning agent to avoid exploring risky policies. This algorithm uses Q-network (i.e., a convolutional neural network or a deep neural network) to choose the policy and designs a safety guide to modify the chosen policy that results in dangerous status. More specifically, the safety guide includes a risk alarm module that evaluates the immediate warning value corresponding to the risk of each state-action pair and a G-network that estimates the long-term risk value. By adding the long-term risk value and the long-term expected reward output by the Q-network, this algorithm uses a safety dock to modify the chosen policy. This algorithm uses the immediate warning value to formulate a safe buffer and a risky buffer for the G-network updating to ensure fully exploration in the initial learning process. As a case study, we apply the designed algorithm in a cargo transportation system, in which the experimental results verify the effectiveness of our algorithm compared with the benchmark safe deep Q-network. © 2023 IEEE.

关键词： Network security

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Preprocessing-based Kinodynamic Motion Planning Framework for Intercepting Projectiles using a Robot Manipulator

arXiv

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arXiv 2024年

作者： Natarajan, Ramkumar Yang, Hanlan Xie, Qintong Oza, Yash Das, Manash Pratim Islam, Fahad Saleem, Muhammad Suhail Choset, Howie Likhachev, Maxim The Robotics Institute School of Computer Science Carnegie Mellon University United States Department of Engineering Science University of Oxford United Kingdom

We are interested in studying sports with robots and starting with the problem of intercepting a projectile moving toward a robot manipulator equipped with a shield. To successfully perform this task, the robot needs to (i) detect the incoming projectile, (ii) predict the projectile’s future motion, (iii) plan a minimum-time rapid trajectory that can evade obstacles and intercept the projectile, and (iv) execute the planned trajectory. These four steps must be performed under the manipulator’s dynamic limits and extreme time constraints (≤ 350ms in our setting) to successfully intercept the projectile. In addition, we want these trajectories to be smooth to reduce the robot’s joint torques and the impulse on the platform on which it is mounted. To this end, we propose a kinodynamic motion planning framework that preprocesses smooth trajectories offline to allow real-time collision-free executions online. We present an end-to-end pipeline along with our planning framework, including perception, prediction, and execution modules. We evaluate our framework experimentally in simulation and show that it has a higher blocking success rate than the baselines. Further, we deploy our pipeline on a robotic system comprising an industrial arm (ABB IRB-1600) and an onboard stereo camera (ZED 2i), which achieves a 78% success rate in projectile interceptions. © 2024, CC BY.

关键词： Industrial robots

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Development and Analysis of a Versatile Dataset of Speech, Real and Synthesized, of Arabic Learners 3

Development and Analysis of a Versatile Dataset of Speech, R...

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3rd International Conference on Computing and Information Technology, ICCIT 2023

作者： Alsulaiman, Mansour Algabri, Mohammed Mathkour, Hassan Bencherif, Mohamed A. Muhammad, Ghulam Al-Gahtani, Saad Faisal, Mohammed Mekhtiche, Mohamed Amine Alfakih, Taha King Saud University College of Computer and Information Sciences Computer Engineering Department Riyadh Saudi Arabia AlMaarefa University College of Applied Sciences Computer Science and Information Systems Department Riyadh Saudi Arabia King Saud University College of Computer and Information Sciences Computer Science Department Riyadh Saudi Arabia Riyadh Saudi Arabia King Saud University Arabic Language Institute Saudi Arabia Center of Ai & Robotics Kuwait

ISBN: (纸本)9798350321487

computer-Aided Pronunciation Training (CAPT) systems are gaining popularity recently due to the advancements in deep neural networks (DNN) and machine learning and the availability of databases of speech of language learners. Unfortunately, research in Arabic CAPT systems suffer from the lack of CAPT datasets compared to other languages. In this paper, we present the details of and the ideas used in the development of a versatile dataset of speech, real and synthesized, of Arabic Learners. To develop the dataset, we utilized an existing Arabic speech corpus, King Saud University Speech Database (KSU-SD). KSU-SD's main application was a speaker recognition system, but it was designed to be useful in other applications such as CAPT systems. KSU-SD includes a large number of speakers from diverse nationalities (Saudis, Arabs, and Non-Arabs). KSU-SD contains the recording of about 60 non-native speakers from more than 20 nationalities, hence we selected it to build the non-native Arabic-CAPT corpus. The developed corpus consists of transcribed, segmented, and annotated speech, which makes it suitable for building Arabic CAPT systems. In addition to presenting the details of developing the dataset, we also present an analysis of the text and speech errors of the dataset. The dataset was verified by many CAPT systems. © 2023 IEEE.

关键词： Deep 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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Blockchain and API Development to Improve Relational Database Integrity and System Interoperability 7

Blockchain and API Development to Improve Relational Databas...

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Ramadhan, Andhika Naafi Pane, Kharisma Naufal Wardhana, Kun Rifki 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. © 2022 Elsevier B.V.. All rights reserved.

关键词： Blockchain

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Simulation of Data Acquisition System Using SimulIDE, Virtual Serial Port and Python

Simulation of Data Acquisition System Using SimulIDE, Virtua...

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International Conference on Education and Technology (ICET)

作者： Muhammad Nurul Puji Winda Astuti Computer Engineering Department Automotive and Robotics Engineering Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

Data acquisition systems are commonplace in the current era of digitalization and Industry 4.0. These systems are typically used to obtain data from sensors, whether analog or digital, which is then stored for processing in subsequent stages. However, the implementation of hardware for creating data acquisition systems can be challenging due to constraints such as laboratory facilities, budget limitations, and other factors. Therefore, in this research, SimulIDE simulation software was employed to simulate electronic components and the Arduino Uno. To make this virtual Arduino appear as a physical one to the host computer, PyVirtualSerialPorts was used as a virtual serial port. The data acquisition system was created using Python programming with several key features: it can store data in CSV format, present data plots and graphs, and display the frequency spectrum of signals. The system achieved a sampling speed of 1000 data points per second, with input signals limited to a maximum of 10 Hz. This study also shows that signal distortion can occur due to excessively frequent data plotting and Fast Fourier Transform (FFT) processing. Therefore, the use of SimulIDE simulator, virtual serial port, and Python can be utilized in the learning process of a simple data acquisition system.

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Style Change Detection using Discourse Markers

Style Change Detection using Discourse Markers

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2022 Conference and Labs of the Evaluation Forum, CLEF 2022

作者： Alvi, Faisal Algafri, Hasan Alqahtani, Naif Information & Computer Science Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Computer Science Program Dhanani School of Science and Engineering Habib University Karachi Pakistan

This article presents our approach for the Style Change Detection Task at PAN 2022 using discourse markers. Discourse markers (such as ‘what’, ‘I have’, etc.) are words or expressions used to connect, organise and manage conversations. We present two different approaches for Style Change Detection at PAN-2022. For Task 1, (Style Change Basic) our approach is based on identifying conversational patterns within the documents between a user and a possible respondent. Then, using classification algorithms, we predict the point of style change detection within each document. For Task 2 (Style Change Advanced) and Task 3 (Style Change Real World), we use an extensive list of frequently occurring discourse markers to identify the number of speakers as the number of authors within the document. This prediction serves as the number of clusters for text segments within the document. Subsequently, using unsupervised clustering we detect clusters of similar text segments such that each cluster comprises of text segment groups corresponding to each author. The resulting F1 scores for our approaches on the test set are: 0.70518 for Task 1, 0.32128 for Task 2 and 0.56360 for Task 3. © 2022 Copyright for this paper by its authors.

关键词： Change detection

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The Effect of Cache Decision Policies on QoE in Multiple Video and Audio Streaming over ICN/CCN

The Effect of Cache Decision Policies on QoE in Multiple Vid...

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Communications and Networking (MeditCom), IEEE International Mediterranean Conference on

作者： Keisuke Kobayashi Toshiro Nunome Department of Engineering Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350309485

ISBN: (纸本)9798350309492

This paper considers video and audio transmission in ICN (Information-Centric Networking)/ CCN (ContentCentric Networking), where each intermediate node can cache content. We have proposed LCD with Prob, combining traditional policies: LCD (Leave Copy Down) and probabilistic caching. This paper assumes a case where multiple video and audio streams exist simultaneously. We assess application-level QoS (Quality of Service) and QoE (Quality of Experience) of video and audio transmission utilizing LCD with Prob. We also add a mechanism for further QoE enhancement called “LCD with Prob deletion.” We assess application-level QoS using a computer simulation with a tree network and QoE by means of a subjective experiment. From the assessment result, we show the effectiveness of LCD with Prob deletion against existing policies.

关键词： Network topology Scalability Redundancy Quality of service Streaming media Probabilistic logic Liquid crystal displays

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Data Mining and Bioinformatics Approaches to Elucidate Bacterial Communities in the Extreme Environment

Data Mining and Bioinformatics Approaches to Elucidate Bacte...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Nirwantono, Rudi Asadi, Faisal Pardamean, Bens Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

Bacteria are microscopic organisms that can be found in many environments. They are abundant and have many roles in our life. Studying bacteria is essential so that we can identify the bacteria that are needed for many industrial applications. However, the main problem is that majority of the bacteria are unculturable, hampering the exploration of bacteria from different environments. Metagenomics approach which employs Next Generation Sequencing technology could help study bacteria by utilizing 16S rRNA marker gene. This study aims to demonstrate data mining and bioinformatics approaches to analyze 16S rRNA sequencing data. The raw sequencing data of 16S rRNA was collected from biological database. Then, the data were trimmed, denoised, and clustered to generate Amplicon Sequence Variants (ASVs). Diversity (alpha and beta) and taxonomic analyses were then conducted to elucidate the bacterial diversity and taxonomic profile of ASVs. The results of this work showed that Shannon and PD indices in China's hot spring were higher than Singapore and the USA. Furthermore, a significant difference was observed in the PD index. The unweighted UniFrac distance also showed there was a significant difference of the bacterial communities between the three locations. In addition, the taxonomic investigation unveiled prevalent bacterial groups in the ecosystem, namely Proteobacteria, Chloroflexi, Cyanobacteria, and Crenarchaeota. The research outcomes have the potential to serve as a foundational resource for subsequent bacterial metagenomic research, particularly the hot spring environment. © 2023 IEEE.

关键词： Bacteria

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