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5th IEEE International Conference on computer and informatics engineering, IC2IE 2022

作者： Zain, Ayu Rosyida Oktivasari, Prihatin Agustin, Maria Kurniawan, Asep Murad, Fachroni Arbi Nurrahman, Iskandar Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia

ISBN: (数字)9781665453387

ISBN: (纸本)9781665453387

LoRaWAN was built to allow long distance communication with a low bit rate and an encrypted system using the 128bit key of Advanced Encryption Standard (AES) algorithm for the messages encryption and decryption. With the various advantages offered by LoRaWAN. However, some features of LoRa technology also bring new security weaknesses. Therefore, we propose an integration encryption method between a mobile application for IoT monitoring system and the LoRaWAN server. With this method it is able to answer security challenges in the application of IoT, but due to limited use and devices, an analysis of the performance of the LoRaWanprotocol is needed for the data encryption process carried out on an integrated smart home system based on the Android-based application. Therefore, this research is focused on analyzing the performance of the LoRaWAnprotocol for data transmission in smart home systems by considering the security of the data information sent. So as to create an IoT-based smart home system that is more efficient and remains safe when used. From the results of this study, it was found that the LoRaWAN protocol still has a vulnerability in the security of its data payload packet because it is not encrypted and this vulnerability is proven in data monitoring tests. © 2022 IEEE.

关键词： Cryptography

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Graph Neural Networks For Affective Social Media: A Comprehensive Overview

Graph Neural Networks For Affective Social Media: A Comprehe...

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2022 International Conference on Information and Knowledge Management Workshops, CIKM-WS 2022

作者： Karavokyris, Michail Sioutas, Spyros Computer Engineering and Informatics Department University of Patras Patras26504 Greece

Social media have become the main platforms for expressing and supplementing nuanced human activity such as engaging in public and private conversations, creating and sharing multimedia content, participating to digital culture events, and recently describing emotions about events, places, or even products. In this survey, we provide a comprehensive overview of graph mining and machine learning on affective social media through graph neural networks (GNNs). The latter are capable of performing a variety of tasks, such as graph and vertex classification, link prediction, and graph clustering using vertex information, edge information, and topological structure. These capabilities are critical in harnessing the vast emotional information available in social media in order to generate meaningful and scalable affective analytics. © 2022 Copyright for this paper by its authors.

关键词： Network topology

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Social Distance Monitoring System Using YOLO and Pixel-to-real-world Distance Mapping 6

Social Distance Monitoring System Using YOLO and Pixel-to-re...

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6th International Conference on informatics and Computational Sciences, ICICoS 2022

作者： Liliana, Dewi Yanti Nalawati, Rizki Elisa Nugrahani, Fitria Muharram, Muhammad Rienaldy Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia

ISBN: (数字)9781665460996

ISBN: (纸本)9781665460996

Covid-19 is an infectious disease caused by the recently discovered coronavirus. This virus spreads through droplets produced when an infected person coughs, sneezes, or exhales. A person can be infected by breathing air containing the virus if a person is too close to someone who is already infected with Covid-19. A person can also be infected by touching contaminated surfaces and then touching their eyes, nose, or mouth. Social distancing is to reduce the spread of viruses, other than washing hands and wearing a mask. With the help of computer Vision Technology, it can monitor the safe distance of human activities in a particular area or environment. The problem is to determine the safe distance in a pixel-based digital image. The difference in the same pixel distance does not always mean the actual distance between adjacent objects is the same. It must consider the actual distance to the camera. Since social distancing requires someone to keep a certain distance from another, a web-based application with a Convolutional Neural Network (CNN) algorithm is employed using the You Only Look Once (YOLO) and Pixel-to-real-world distance mapping technique. In testing, there are several test scenarios with the accuracy results obtained of 95% with a recall of 0.95 and a precision of 0.92, and MAE 5.9 cm. © 2022 IEEE.

关键词： Pixels

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Evaluation of EmoHealth Application Using USE Questionnaire 5

Evaluation of EmoHealth Application Using USE Questionnaire

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5th IEEE International Conference on computer and informatics engineering, IC2IE 2022

作者： Ismail, Iklima Ermis Liliana, Dewi Yanti Zain, Ayu Rosyida Department of Computer and Informatics Engineering Politeknik Negeri Jakarta Depok Indonesia

ISBN: (数字)9781665453387

ISBN: (纸本)9781665453387

The Covid-19 pandemic situation and social restrictions as the impact have resulted in many problems, including mental and emotional health in society. The existence of mobile application technology through smartphones, which many people own, can be a means to assist, especially people with emotional problems. We have developed the EmoHealth Application for this purpose. The EmoHealth application aims to make people get easier to manage and regulate their daily emotions. The EmoHealth has been developed based on Artificial Intelligence. It has four main features, namely: emotional assessment, emotional journey, emo insight, and chatbot features, and is currently developed only in the Bahasa version. This research aims to test the EmoHealth application's usability to get users' feedback before it is widely published. Tests are carried out to ensure that the EmoHealth application is usable and suitable for user needs. The USE Questionnaire is used because it is one of the most frequently used methods in testing mobile-based applications. The USE questionnaire has four attributes: usefulness, ease of use, ease of learning, and satisfaction. Reliability testing aims to measure the consistency of the questionnaire test. The result usability score is 75.9%, which implied that the EmoHealth application can be used well and satisfactorily. © 2022 IEEE.

关键词： Mobile computing

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Analysis of Effectiveness of Iptables on Web Server from Slowloris Attack 5

Analysis of Effectiveness of Iptables on Web Server from Slo...

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5th IEEE International Conference on computer and informatics engineering, IC2IE 2022

作者： Oktivasari, Prihatin Zain, Ayu Rosyida Agustin, Maria Kurniawan, Asep Murad, Fachroni Arbi Anshor, Muhammad Fabian Politeknik Negeri Jakarta Informatics and Computer Engineering Department Depok Indonesia

ISBN: (数字)9781665453387

ISBN: (纸本)9781665453387

In the application of network technology, a Web Server is needed that can run well, by providing data services that have the function to accept HTTP or HTTPS requests by maintaining the security of the Web Server from various disturbances or attacks. Along with the development of information technology, it can cause types of crime in technology, especially on web servers. One type of crime that can occur is the Slow loris Distribute Denial of Service (DDoS) attack, which type of attack is focused on disrupting service availability. To overcome these types of attacks in a simple and fast way, it can be applied using the firewall installation method with IP tables filtering tools by conducting research on testing and comparative analysis from before and after the implementation of the IP tables method against Slow loris attacks. Finally, this paper discusses about future solution of DDoS attack and recommendation for secure environment, using IP tables configuration is very effective for secure data, because a simple configuration of IP tables can also limit and block IP directly or completely to attackers who can overcome the attack. © 2022 IEEE.

关键词： Denial-of-service attack

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Hardware Selection Approach for Custom UAVs 26

Hardware Selection Approach for Custom UAVs

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26th Pan-Hellenic Conference on informatics, PCI 2022

作者： Sdoukou, Evanthia Milidonis, Athanasios Psilias, Dimitrios Efstathiou, Konstantinos Voyiatzis, Ioannis Department of Informatics and Computer Engineering University of West Attica Athens Greece

ISBN: (纸本)9781450398541

The use of Unmanned Aerial Vehicles (UAVs) is growing at a fast pace, as they tend to play an important role in areas such as surveillance, delivery of goods, etc. This is mainly based on their ability to perform flights at low cost with fast deployment. Moreover, they can transmit data produced by embedded sensors and carry packages of different size and weight. Based on these characteristics, the approach of building custom UAVs, for different applications is very common. Since each application requires specific hardware for the UAVs' efficient operation, the selection of the appropriate parts is not an easy task. In this paper, all the necessary information of the basic UAV hardware parts is presented. Using this information, an approach is suggested, for selecting the most suited hardware parts for the most common application domains. © 2022 ACM.

关键词： Antennas

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Improved Dynamic Johnson Sequencing Algorithm(DJS)in Cloud Computing Environment for Efficient Resource Scheduling for Distributed Overloading

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Journal of Systems Science and Systems engineering 2024年第4期33卷 391-424页

作者： Anurag Sinha Pallab Banerjee Sharmistha Roy Nitasha Rathore Narendra Pratap Singh Mueen Uddin Maha Abdelhaq Raed Alsaqour Department of Computer Science Engineering ICFAI Tech SchoolICFAI UniversityJharkhandRanchi834004India Department of Computer Science Engineering Amity UniversityJharkhandRanchi835303India Department of Computing and Information Technology Usha Martin UniversityRanchi835103India Department of Information Technology Bharti Vidyapeeth’s College of EngineeringPaschim ViharNew DelhiIndia Department of CSE Delhi UniversityNew DelhiIndia College of Computing and Information Technology University of Doha for Science and TechnologyDoha24449Qatar Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdurrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology College of Computing and InformaticsSaudi Electronic University93499RiyadhSaudi Arabia

This study introduces an innovative approach to optimize cloud computing job distribution using the Improved Dynamic Johnson Sequencing Algorithm(DJS).Emphasizing on-demand resource sharing,typical to Cloud Service Providers(CSPs),the research focuses on minimizing job completion delays through efficient task *** Johnson’s rule from operations research,the study addresses the challenge of resource availability post-task *** advocates for queuing models with multiple servers and finite capacity to improve job scheduling models,subsequently reducing wait times and queue *** Dynamic Johnson Sequencing Algorithm and the M/M/c/K queuing model are applied to optimize task sequences,showcasing their efficacy through comparative *** research evaluates the impact of makespan calculation on data file transfer times and assesses vital performance indicators,ultimately positioning the proposed technique as superior to existing approaches,offering a robust framework for enhanced task scheduling and resource allocation in cloud computing.

关键词： First come first served(FCFS)scheduling round robin task scheduling queuing model Johnson scheduling algorithm

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Source Code Statement Classification using ANTLR and Random Forest 24

Source Code Statement Classification using ANTLR and Random ...

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24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023

作者： Putro, Hanson Prihantoro Yuhana, Umi Laili Yuniarno, Eko Mulyanto Purnomo, Mauridhi Hery Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Surabaya Indonesia Universitas Islam Indonesia Department of Informatics Yogyakarta Indonesia Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Computer Engineering Department of Electrical Engineering Surabaya Indonesia

ISBN: (纸本)9798350313956

In software development, source code analysis is essential to maintain software. One of the metrics used to assess software quality is software complexity, which can be calculated by analyzing source code statements like declaration, expression, and control. However, analyzing source code statements using an existing popular technique, like NLP, requires another structured form of data, which can be obtained by converting the source code into a token stream using a programming language processor. This study aims to get the best source code statement classification from six observed models and two source code forms. The models are Decision Tree, Naïve Bayes, SVM, kNN, Rocchio Algorithm and Random Forest. The source code forms are the raw source code and token stream object. The dataset collection used 562 rows of source code statements from an open-source Java project in a public repository. Next, we use ANTLR to transform the raw source code and get the token stream object. Later, the dataset was modeled using TF-IDF as an NLP technique to get the source code features. Then, six machine learning models were built and evaluated as a comparison for the classification process. As a result, Random Forest became the best model with the highest accuracy values among other machine learning models. Moreover, the token stream became the best object over source code as a contribution from the ANTLR. The model successfully predicted source code statements with a 96.1% accuracy score using the Random Forest model and ANTLR tools. In advance, this multiclass classification was also evaluated and gave a result. No declaration statement was predicted as a control statement, and vice versa (100% accuracy), but some miss prediction was observed in declaration-expression and expression-control pairs. Nevertheless, the Random Forest model's high accuracy and precision make it suitable for classifying source code statements. © 2023 IEEE.

关键词： Decision trees

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Identification of the effect of different feature samples on Handwritten Japanese Character Recognition using YOLOv4 24

Identification of the effect of different feature samples on...

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24th International Electronics Symposium, IES 2022

作者： Karlita, Tita Adiputra, Andro Aprila Kusumaningtyas, Entin Martiana Institute of Surabaya Electronic Engineering Polytechnics Department of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (数字)9781665489713

ISBN: (纸本)9781665489713

Handwritten Japanese character recognition has been one of the major tasks in the computer vision field. Previously, various approaches to distinguish characters had proposed, ranging from traditional machine learning, end-to-end model, images retrieval and object detection model. Most research focuses on model performances in ideal conditions with a similar feature distribution and produces an excellent result. In the character recognition task, one of the most efficient ways is to utilize an end-to-end object detection model to avoid sequences and robust against different feature distributions. YOLOv4 is one of the end-to-end object detection models that applies various concepts such as a bag of freebies and bag of specials to increase the robustness of the model by improving the context generalization. In this research, our target is to identify the effect of different feature distributions applied to ideal datasets using YOLOv4 on Japanese character recognition tasks. The result of classification reveals both F1-score and Map accuracy of mAP@50 in the ideal dataset achieve 99%. While in the combined dataset, the performance degradation is 12% lower compared to the ideal dataset. YOLOv4 backbone has proven to be robust generalize different feature distributions. © 2022 IEEE.

关键词： Object detection

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A comprehensive evaluation of large language models in mining gene relations and pathway knowledge

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Quantitative Biology 2024年第4期12卷 360-374页

作者： Muhammad Azam Yibo Chen Micheal Olaolu Arowolo Haowang Liu Mihail Popescu Dong Xu Department of Electrical Engineering and Computer Science University of MissouriColumbiaMissouriUSA Bond Life Sciences Center University of MissouriColumbiaMissouriUSA Institute for Data Science and Informatics University of MissouriColumbiaMissouriUSA Department of Biomedical Informatics Biostatistics and Medical EpidemiologyUniversity of MissouriColumbiaMissouriUSA

Understanding complex biological pathways,including gene–gene interactions and gene regulatory networks,is critical for exploring disease mechanisms and drug *** literature curation of biological pathways cannot keep up with the exponential growth of new discoveries in the ***-scale language models(LLMs)trained on extensive text corpora contain rich biological information,and they can be mined as a biological knowledge *** study assesses 21 LLMs,including both application programming interface(API)-based models and open-source models in their capacities of retrieving biological *** evaluation focuses on predicting gene regulatory relations(activation,inhibition,and phosphorylation)and the Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway *** indicated a significant disparity in model ***-based models GPT-4 and Claude-Pro showed superior performance,with an F1 score of 0.4448 and 0.4386 for the gene regulatory relation prediction,and a Jaccard similarity index of 0.2778 and 0.2657 for the KEGG pathway prediction,***-source models lagged behind their API-based counterparts,whereas Falcon-180b and llama2-7b had the highest F1 scores of 0.2787 and 0.1923 in gene regulatory relations,*** KEGG pathway recognition had a Jaccard similarity index of 0.2237 for Falcon-180b and 0.2207 for *** study suggests that LLMs are informative in gene network analysis and pathway mapping,but their effectiveness varies,necessitating careful model *** work also provides a case study and insight into using LLMs das knowledge *** code is publicly available at the website of GitHub(Muh-aza).

关键词： biomedical text mining gene-gene interaction KEGG pathway large language model

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