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Smart Waste Management Using Microservices and Container-based Virtualization 27

Smart Waste Management Using Microservices and Container-bas...

引用

27th Pan-Hellenic Conference on Progress in Computing and informatics with International Participation, PCI 2023

作者： Karagiannakis, Stilianos Theodoropoulos, Ioannis Anagnostopoulos, Apostolos Mamalis, Basilis University of West Attica Dept. of Informatics and Computer Engineering Greece

ISBN: (纸本)9798400716263

One of the most significant issues associated with smart city applications is solid waste management, which has a negative impact on our society's health and the environment. In this paper, a smart waste bin management approach with novel architectural design is proposed, based on modern container-based virtualization and microservices technologies. Its objective is twofold;first, efficient monitoring/tracking of waste bins, analyzing their data and taking further actions in case of out-of-limits values (i.e. with respect to fire danger, fill level etc.) for improving citizens health and daily life, and second, building a flexible application that can easily be deployed and managed in a distributed manner in any relevant environment, with use of modern orchestrators. Beyond the detailed architectural design, several implementation issues of our approach are thoroughly analyzed and discussed, as well as further extensions and initial performance evaluation. © 2023 Owner/Author.

关键词： Internet of things

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5G Impact on the Flow of Wireless Internet Traffic 5

5G Impact on the Flow of Wireless Internet Traffic

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5th International Conference on Computing, Networking, Telecommunications and engineering Sciences Applications, CoNTESA 2024

作者： Tirana, Kledia Elmazi, Donald Universiteti Metropolitan Tirana Dept. of Business Informatics Tirana Albania Universiteti Metropolitan Tirana Dept. of Computer Engineering Tirana Albania

ISBN: (纸本)9798331534530

This paper examines the impact of 5G technology on internet traffic and network capacity management strategies for Communications Service Providers (CSPs). With 5G offering high-speed, low-latency connections, and enhanced support for IoT devices, CSPs face both opportunities and challenges in optimizing their networks for next-generation services. This analysis covers CSP investment strategies, deployment architectures, spectrum utilization, and the economic pressures shaping the shift toward 5G, aiming to highlight effective pathways and potential obstacles in 5G network management and monetization. © 2024 IEEE.

关键词： 5G mobile communication systems

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Indonesian Hate Speech and Abusive Tweets Classification with Deep Learning Pre-trained Language Models 6

Indonesian Hate Speech and Abusive Tweets Classification wit...

引用

6th International Conference on computer and informatics engineering, IC2IE 2023

作者： Yulianto Darmawan, Bagus Tri Irnawan, Bassamtiano Renaufalgi Suzuki, Yoshimi Politeknik Negeri Jakarta Dept. of Computer and Informatics Engineering Depok Indonesia University of Yamanashi Dept. of Computer Science and Engineering Kofu Japan

ISBN: (纸本)9798350345162

Hate speech and abusive language on social media can spread massively and escalate into conflict between two or more individuals or parties. Previous studies about multi-label classification to identify whether the tweet contains hate speech, abusive language, or not have been conducted with machine learning techniques. They applied machine learning with a combination of feature extraction and achieved a good result in recognizing the tweet with hate speech content. In this research, we apply two approaches: first, we use vanilla pre-trained models of IndoBERT, IndoBERTweet, and Indonesian RoBERTa;second, we combine the three previous models with CNN. Our experiment shows that our proposed method has better results compared to previous research with the best performance achieved by IndoBERTweet+CNN with 93.9% Accuracy. © 2023 IEEE.

关键词： Abusive CNN Deep Learning Hate Speech IndoBERT IndoBERTweet Indonesian RoBERTa Indonesian Twitter

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Design and Implementation of Cloud Computing Using the NDLC Method Combined with Tunnel Link Split

Design and Implementation of Cloud Computing Using the NDLC ...

引用

2023 International Conference on Information Technology and Computing, ICITCOM 2023

作者： Wibowo, Iqbal Tri Kurniawan, Asep Noviandri Sulaiman, Nur Fauzi Oktivasari, Prihatin Politeknik Negeri Jakarta Dept. of Informatics and Computer Engineering Depok Indonesia

ISBN: (纸本)9798350359633

Today's education system increasingly incorporates information technology, such as the use of computers, the internet, and mobile devices. Utilization of this information technology can facilitate the teaching and learning process and increase the effectiveness, efficiency and productivity of users, both teachers, students and school administrators. However, given the growing number of users and the amount of data processed, school infrastructure often cannot meet these needs. The system development method will use the NDLC (Network Development Life Cycle) method which will be combined with the Tunnel Link Split to become a system that can be used remotely (remoting). The results of this research are that the results of designing and implementing cloud computing with the NDLC method combined with tunneling can be successful and used. Implementation is also carried out with additional monitoring using observium software and for access to the cloud using additional software, namely owncloud by obtaining an extended processor observium value of 99.90% (idle), detailed observium memory 69% (% of ram), swap storage observium 218.48kb/ s, observium ping response 86.4m/s, and observium traffic port wlo15.63m. © 2023 IEEE.

关键词： Life cycle

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Analysis of *** Email Domain Security Status Using DMARC (Domain-Based Message Authentication, Reporting, and Conformance) 6

Analysis of *** Email Domain Security Status Using DMARC (Do...

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6th International Conference on computer and informatics engineering, IC2IE 2023

作者： Arnaldy, Defiana Theyser, Regina Patricia Politeknik Negeri Jakarta Dept. of Informatics and Computer Engineering Depok Indonesia

ISBN: (纸本)9798350345162

The rapid development of technology not only provides benefits that facilitate all human activities. However, it also encourages more security loopholes due to a person's lack of awareness in maintaining data security. Phishing emails are one of the fastest growing security crimes and harm both businesses and individuals. This research aims to implement DMARC (Domain-based Message Authentication, Reporting, and Conformance) as an email authentication method that can monitor the security status of all types of messages that enter *** email domains. This research uses email phishing and spoofing as penetration testing techniques to analyze how good that email security method is. DMARC is implemented in three types of scenarios (none, quarantine, and reject) which manage to get different delivery rates and the success rate of DMARC work performance reaches 90% in monitoring and managing all email messages that go to the *** email domain. In the situation without policy enforcement, the DMARC system effectively observed a 100.0% external delivery rate during the phishing email delivery test. In the scenario where a quarantine policy was implemented, the DMARC system successfully monitored the external sending of phishing emails at a rate of 88.5%. Similarly, in the case of the reject policy scenario, DMARC effectively oversaw incoming phishing emails with an external delivery rate of 97.7%. © 2023 IEEE.

关键词： Apilogy.id DMARC Email Security Phishing Spoofing

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PhishGuard: A Convolutional Neural Network-Based Model for Detecting Phishing URLs with Explainability Analysis 3

PhishGuard: A Convolutional Neural Network-Based Model for D...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Islam, Md Robiul Islam, Md Mahamodul Afrin, Mst. Suraiya Antara, Anika Tabassum, Nujhat Amin, Al Uttara University Dept. of Computer Science and Engineering Dhaka Bangladesh University of Oslo Dept. of Informatics Oslo Norway Dept. of Building Engineering and Construction Management Khulna Bangladesh BRAC University Dept. of Electrical and Electronics Engineering Dhaka Bangladesh North South University Dept. of Electrical and Computer Engineering Dhaka Bangladesh Dept. of Computer Science American International Dhaka Bangladesh

ISBN: (纸本)9798350372120

Cybersecurity is one of the global issues because of the extensive dependence on cyber systems of individuals, industries, and organizations. Among the cyber attacks, phishing is increasing tremendously and affecting the global economy. Therefore, this phenomenon highlights the vital need for enhancing user awareness and robust support at both individual and organizational levels. Phishing URL identification is the best way to address the problem. Various machine learning and deep learning methods have been proposed to automate the detection of phishing URLs. However, these approaches often need more convincing accuracy and rely on datasets consisting of limited samples. Furthermore, these black-box intelligent models' decision to detect Suspicious URLs needs proper explanation to understand the features affecting the output. To address the issues, we propose a 1 D Convolutional Neural Network (CNN) and trained the model with extensive features and a substantial amount of data. The proposed model outperforms existing works by attaining an accuracy of 99.85 %. Additionally, our explainability analysis highlights certain features that significantly contribute to identifying the phishing URL. © 2024 IEEE.

关键词： Convolutional neural networks

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Lidar-based Human Detection for a Mobile Robot in Social Environment using Deep Learning 25

Lidar-based Human Detection for a Mobile Robot in Social Env...

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25th International Electronics Symposium, IES 2023

作者： Ramadhan, Alif Wicaksana Dewantara, Bima Sena Bayu Setiawardhana Akzada, Fursan Departmen of Electrical Engineering Surabaya Indonesia Dept. of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350314731

Nowadays, robotics implementation spans industries such as manufacturing, healthcare, and logistics, integrating AI-driven capabilities to enhance efficiency and collaboration in diverse operational environments. The ability to respond and interact while considering human presence is crucial for a mobile robot to operate effectively and be accepted in a human social environment. It is necessary to make a robot that can detect the presence of humans around it to make it capable of navigating while considering the social environment. Meanwhile, considering that the lidar sensor is almost always available in many robot navigation cases, it becomes an accessible tool for detecting the presence of humans in its surroundings. We brought the one-dimensional lidar data into two-dimensional image data, then involved some object selection based on weak characteristics, such as the acceptable range radius of the object and the acceptable distance between two legs. The result of the process is a group of human candidates. We use a deep learning model with a pretrained mobilenetv3 model as the feature extractor to ensure whether the candidates are humans and a fully connected layer of neural networks as the classifier. We defined several scenarios in an indoor environment to test the performance of the proposed algorithm. The experiment results show the system's performance with a precision score of 0.902, a recall score of 0.782, and an F1 score of 0.837. © 2023 IEEE.

关键词： Mobile robots

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Sensitive Content Detection in Social Networks Using Deep Learning Models and Explainability Techniques 9

Sensitive Content Detection in Social Networks Using Deep Le...

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9th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2024

作者： Perikos, Isidoros University of Patras Computer Engineering and Informatics Department Patras Greece University of Peloponnese Computer Technology Institute and Press 'Diophantus' Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350394191

In the dynamic landscape of online social networks, recognizing sensitive content is essential for safeguarding user privacy, fostering inclusivity, and enhancing diversity awareness. Building on prior research, this study explores new dimensions and methodologies for detecting sensitive content. We examine the temporal evolution of sensitive content, revealing how patterns shift over time, and address cross-linguistic challenges, emphasizing cultural and contextual nuances in detection. We employ advanced machine learning techniques, including deep learning models and BERT that improve the accuracy and robustness of the detection procedure. In the experimental study, BERT transformer reported the best performance in detecting sensitive content in text. Additionally, we incorporate explainability techniques such as LIME and SHAP to provide deeper insights into the model's decision-making processes, ensuring predictions are interpretable and reliable. Our work enhances the theoretical framework of sensitive content detection in social networks and provide methods that are accurate and scalable and can facilitate the creation of user-centric interaction that prioritize privacy and user experience. © 2024 IEEE.

关键词： Adversarial machine learning

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Detection and Classification of Cardiac Arrhythmia from Photoplethysmography Signal

Detection and Classification of Cardiac Arrhythmia from Phot...

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2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023

作者： Dewantara, Bima Sena Bayu Sari, Dewi Mutiara Fahmi, Ahmad Nur Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350319040

This paper presents the development of an application for classifying cardiac arrhythmia by utilizing photoplethys-mography sensor signals. The Photoplethysmography (PPG) sensor is used as a reader for the cardiovascular system by measuring changes in blood volume in the skin tissue. The PPG sensor captures electrical signals originating from the reflected light source due to changes in blood flow during heart activity. After going through the preprocessing stage, the signals are then extracted into several features that will be classified using the Random Forest algorithm. The results from the Random Forest algorithm will provide a diagnosis based on the detection of arrhythmia. Based on the experimental results, the accuracy achieved using the method and dataset is 72%. The accuracy of the system testing using the smartwatch under normal heart conditions is 88.88%. © 2023 IEEE.

关键词： Photoplethysmography

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Navigation System Development on ATRACBOT using F-SFM 25

Navigation System Development on ATRACBOT using F-SFM

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25th International Electronics Symposium, IES 2023

作者： Widarto, Mochamad Farhan Eka Marta, Bayu Sandi Dewantara, Bima Sena Bayu Setiawardhana Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350314731

Navigation systems are very important for social robots, especially autonomous robots, because they are required to be adaptive to their surrounding environment. This paper proposes a new navigation system for the Autonomous Trash Can Robot (ATRACBOT) using the Fuzzy-based Social Force Model (F-SFM). The navigation system employed in earlier stages of development depended on the Braitenberg approach, leading to the robot's motion appearing rigid. On the other hand, the Social Force Model (SFM) employs the forces surrounding objects to engage with and evade other entities, presenting a different approach. The magnitude of the force to avoid objects is determined by the SFM parameters and the stimulus received by the robot. The Fuzzy Inference System (FIS) is used to obtain the optimal value of the gain factor, k, which is one of the SFM parameters, based on the relative distance, d, and relative angle, \gamma, between the obstacle and robot. The FIS will process both inputs and produce a suitable gain factor, k, so that the stimulus received can match the robot's reactivity and responsiveness. Based on the results from a realistic 3D simulator V-Rep, the implementation of the F-SFM method can deliver the robot to the goal point without hitting obstacles and make the robot's movements more natural compared to the Braitenberg method. © 2023 IEEE.

关键词： Navigation systems

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