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23rd International Scientific Conference on Electric Power engineering, EPE 2023

作者： Pluzek, Aleksandra Nagi, Lukasz Koziol, Michal Zygarlicka, Malgorzata Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Department of Electrical Power and Renewable Energy Opole Poland Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Department of Computer Science Opole Poland

ISBN: (纸本)9798350335934

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength. © 2023 IEEE.

关键词： Nanoparticles

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Implementation of the SPECK Cipher Algorithm on Patient Blood Pressure Data Using the Internet of Things (IoT) 7

Implementation of the SPECK Cipher Algorithm on Patient Bloo...

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7th International Conference on Sustainable Information engineering and Technology, SIET 2022

作者： Santoso, Edy Nurwarsito, Heru Malik, Argandhi Adi Department of Informatics Engineering Faculty of Computer Science University of Brawijaya Malang Indonesia

ISBN: (纸本)9781450397117

Internet of Things technology allows humans to collect information about daily activities, for example to find out someone's health information, but at the time of data transmission it has an impact on one's privacy. Sniffing can record data sent from the user to the database server, this results in a leak of individual privacy. The SPECK algorithm is one of the cryptographic algorithms that guarantees confidentiality because the SPECK algorithm has varying key lengths and block sizes. Adding the SPECK cipher Algorithm to the node that holds sensor data can minimize privacy data leaks caused by data transmission on the Internet of Things. The SPECK algorithm has the same results as the test vectors in published journals and the resulting ciphertext can be returned to its original form by decryption. The encryption time is 0.089354 seconds and the decryption time on the server is 0.00610295 seconds. © 2022 ACM.

关键词： Internet of things

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Knowledge-Enriched Domain Specific Chatbot on Low-resource Language 11

Knowledge-Enriched Domain Specific Chatbot on Low-resource L...

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11th Electrical Power, Electronics, Communications, Control, and informatics Seminar, EECCIS 2022

作者： Perdana, Rizal Setya Adikara, Putra Pandu Indriati Kurnianingtyas, Diva Brawijaya University Faculty of Computer Science Department of Informatics Engineering Malang Indonesia

ISBN: (数字)9781665406482

ISBN: (纸本)9781665406482

This study presents architecture in learning human-machine conversation using a human language known as chatbots. Given an utterance, a chatbot attempt to reply using human language by mimicking human intelligence in communication. Previous works in this domain were mostly implemented in English, thus it remains a problem when bringing to a low-resource language, e.g., Indonesian. The limited availability of human-to-human dialog history led to difficulty in the learning process of machine learning algorithms. Therefore, this study proposed a Knowledgeable Chatbot (KC), an enhanced pipeline that enables to receiving of transferred knowledge from another task. A data augmentation pipeline is proposed to handle the limited number of available. To deal with the low-resource language, this study proposed to incorporate a pre-trained language model to gain contextualized language understanding. As this research can be categorized as preliminary, extensive experiments are required to prove the effectiveness of each part. Standard automatic metrics for information retrieval and classification prove that KC excels in the ablation study. © 2022 IEEE.

关键词： Information retrieval

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Landsat Image Classification Based on K-Nearest Neighbor

Landsat Image Classification Based on K-Nearest Neighbor

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2022 International Seminar on Application for Technology of Information and Communication, iSemantic 2022

作者： Barito, Raynaldi Bismantaka Sanjaya, Muhammad Hafidh Arif, Fajar Muhammad Humam, Naufal Aji, Pri Nugroho Sari, Christy Atika Rachmawanto, Eko Hari Suprayogi Dian Nuswantoro University Informatics Engineering Faculty of Computer Science Semarang Indonesia

ISBN: (数字)9781665488396

ISBN: (纸本)9781665488396

Classification is the process of grouping classes and defining a class and determining the relationship between these classes. Landsat imagery with the distribution of residential areas and agricultural areas can be used to process information on the population density of a particular area. In this study, the classification process of residential images, factory images and rice fields images has been carried out with a total of 58 data. KNN was chosen as the classification algorithm considering the data used is quite simple and few. In this study, GLCM is used for feature extraction features, especially regarding image texture patterns. We have implemented values K=1 to k=11. The best accuracy value is obtained at k=1 which is 100%, while k=3, k=5 has obtained an accuracy of 96.15%. k=7 and k=9 can still be tolerated by getting 76.92% while at k=11 it only gets 57.69%. © 2022 IEEE.

关键词： Image texture

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Streamlit Application for Helmet Detection Based on YOLOS: Case Study Indonesia

Streamlit Application for Helmet Detection Based on YOLOS: C...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Habib, Habib Muchtar, Kahlil Bahri, Al Yuliar Arif, Teuku Arnia, Fitri Safrizal, Safrizal Fuadi Abidin, Taufik Universitas Syiah Kuala Department of Electrical and Computer Engineering Aceh Indonesia Universitas Syiah Kuala Faculty of Mathematics and Natural Sciences Department of Informatics Aceh Indonesia

ISBN: (纸本)9798350369106

Traffic violations are still the biggest problem in the development of traffic in Indonesia. The three biggest violations are (1) running a red light, accounting for 42% of violations, (2) not wearing a helmet, accounting for 23% of violations, and (3) violating traffic signs, accounting for 9% of violations. The violation of not wearing a helmet is the second largest violation in Indonesia, which is due to the lack of awareness of safety while driving. Additionally, the supervision carried out by the security forces is also somewhat inadequate. Supervision is only conducted in certain areas, leading to a high number of violations. To address these issues, the YOLOS (You Only Look at Once Sequence) model, using Vision Transformer and Pytorch, was developed with the assistance of the AI City Challenge 2023 dataset. This model, trained for 200 epochs, is capable of detecting riders who wear helmets and those who do not. It achieves average precision and average recall values for objects with large area coverage in the precision and recall curves (large area), namely 38.8% and 57.2%, and on average precision with an IoU parameter of 0.5, obtaining a value of 63.5%. The implementation of the model in the Streamlit framework to create a system that can be used for detection was successfully completed. The system is capable of performing detection on a single image, webcam video, and video from RTSP CCTV. © 2024 IEEE.

关键词： Traffic signs

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Implementation of Face Detection to Count the Number of Mall Visitors 8

Implementation of Face Detection to Count the Number of Mall...

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8th IEEE International Conference on Computing, engineering and Design, ICCED 2022

作者： Fernandes, Gilang Ryan Wiguna, Didik Natsir, Fauzan Triyadi Suwela, Nandang Birowo, Achmad Indraprasta PGRI University Informatics Engineering Faculty of Engineering and Computer Science South Jakarta Indonesia

ISBN: (纸本)9781665453899

In the current digital era, various data can be generated with the capabilities of a computer system, making it easier and faster to make decisions. Mall is a place for shopping as well as entertainment that presents many well-known brands. In marketing the room to tenants, data is needed that can attract tenants to cooperate with the mall. The method used in this research is the Viola-Jones method which is used to detect objects because this method has an efficient algorithm, so it does not take long to detect objects. There are four main contributions to the Viola-Jones theory, including the Haar Feature, Integral image, Adaptive Boosting or AdaBoost, and the Combination Classifier of Cascade. The purpose of this study is to analyze and evaluate the number of visitors who come as a reference for determining prices for tenants. The results of this study found that the Viola-Jones method can effectively calculate the number of visitors with a face detection approach and make it easier for mall management to get mall visitor data. © 2022 IEEE.

关键词： Face recognition

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Resilient TCP Variant Enabling Smooth Network Updates for Software-Defined Data Center Networks

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Tsinghua Science and Technology 2024年第5期29卷 1615-1632页

作者： Abdul Basit Dogar Sami Ullah Yiran Zhang Hisham Alasmary Muhammad Waqas Sheng Chen Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China and also with Department of Informatics and SystemsUniversity of Management and TechnologyLahore 54660Pakistan Department of Computer Science Shaheed Benazir Bhutto UniversitySheringalUpper Dir 18050Pakistan School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876China Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha 61421Saudi Arabia Department of Computer Engineering Faculty of Information TechnologyUniversity of BahrainSakheer 32038Bahrainand also with School of EngineeringEdith Cowan UniversityPerth WA 6027Australia School of Electronics and Computer Science University of SouthamptonSouthamptonSO171BJUK

Network updates have become increasingly prevalent since the broad adoption of software-defined networks(SDNs)in data *** TCP designs,including cutting-edge TCP variants DCTCP,CUBIC,and BBR,however,are not resilient to network updates that provoke flow *** this paper,we first demonstrate that popular TCP implementations perform inadequately in the presence of frequent and inconsistent network updates,because inconsistent and frequent network updates result in out-of-order packets and packet drops induced via transitory congestion and lead to serious performance *** look into the causes and propose a network update-friendly TCP(NUFTCP),which is an extension of the DCTCP variant,as a *** are used to assess the proposed *** findings reveal that NUFTCP can more effectively manage the problems of out-of-order packets and packet drops triggered in network updates,and it outperforms DCTCP considerably.

关键词： software defined data center networks network updates DCTCP out-of-order packets packet drop SDN

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Solving (Max) 3-SAT via Quadratic Unconstrained Binary Optimization 1

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23rd International Conference on Computational Science, ICCS 2023

作者： Nüßlein, Jonas Zielinski, Sebastian Gabor, Thomas Linnhoff-Popien, Claudia Feld, Sebastian Institute for Informatics LMU Munich Munich Germany Faculty of Electrical Engineering Mathematics and Computer Science TU Delft Delft Netherlands

ISBN: (数字)9783031360305

ISBN: (纸本)9783031360299

We introduce a novel approach to translate arbitrary 3-sat instances to Quadratic Unconstrained Binary Optimization (qubo) as they are used by quantum annealing (QA) or the quantum approximate optimization algorithm (QAOA). Our approach requires fewer couplings and fewer physical qubits than the current state-of-the-art, which results in higher solution quality. We verified the practical applicability of the approach by testing it on a D-Wave quantum annealer. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Qubits

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Development and Validation of the Work Readiness Model of informatics Students Using Multiple Regression 8

Development and Validation of the Work Readiness Model of In...

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8th IEEE International Conference on Computing, engineering and Design, ICCED 2022

作者： Sulistyohati, Aprilia Susanti, Lia Ridwan, Ridwan Paramita, Aulia Nastiti, Tashia Indah Indraprasta PGRI University Informatics Engineering Faculty of Engineering and Computer Science South Jakarta Indonesia

ISBN: (纸本)9781665453899

Universities have a difficult task in preparing their students to have competencies according to the needs of the digital era industry. This study aims to determine the effect of hard skills, soft skills, and digital literacy on IT student work readiness. This is quantitative research, and the population is students of informatics engineering at Indraprasta University in semester 7 or 8 who have not worked. The number of samples is as many as 125 students (the minimum sample from the calculation of Slovin with an error rate of 5% is 93). Questionnaires were distributed through a simple random sampling technique. The data were processed using multiple linear regression analysis techniques. The results of this study obtained the equation Y = 1.821 + 0.757X1 +0.380X2 + 0.306X3 + e. Simultaneously hard skills, soft skills, and digital literacy have a positive and significant 94.3% effect on IT work readiness. Partially, the effect of hard skills (X1), soft skills (X2), and digital literacy (X3) on IT student work readiness (Y) is 37.4%, 34.3%, and 23.6%. This study proves that hard skills (X1), soft skills (X2), and digital literacy (X3) competencies together have a significant effect on IT student work readiness (Y) by 94.3%. © 2022 IEEE.

关键词： Students

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Trimmed Non-Local Means Filtering for the Suppression of Mixed Noise in Color Images

Trimmed Non-Local Means Filtering for the Suppression of Mix...

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2023 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Kusnik, Damian Smolka, Bogdan Smolka, Milena Silesian University of Technology Faculty of Automatics Electronics and Informatics Gliwice Poland Agh University of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Krakow Poland

ISBN: (纸本)9798350322972

In this paper, a novel approach to the problem of mixed Gaussian and impulsive noise reduction in color images is proposed. The elaborated denoising framework is based on the Non-Local Means technique, which has been shown to effectively suppress Gaussian noise. To overcome the inability of this filter to deal with impulsive distortions, a robust similarity measure between image patches, that is insensitive to the impact of impulsive distortions, was developed. First, the distorted pixels of the image are detected using the concept of a peer group. If the number of neighbors of a pixel at the center of a filtering window, whose Euclidean distance in the RGB color space does not exceed a threshold value, is smaller than a predefined value, then the considered pixel is treated as corrupted. Afterwards, the similarity between image patches are calculated in a standard way omitting the noisy pixels. In this way, only the average of distances between pairs of unaffected pixels are calculated. Thus, the closeness measure of the patches, which serves as the coefficient in weighted averaging of pixels in the processing block, is not affected by impulsive noise and is still able to cope with the Gaussian noise component. The proposed filtering design is capable of reducing even strong mixed noise while preserving image details and edges. Moreover, it is not computationally intensive, so it can be used in real-time image processing scenarios. © 2023 IEEE.

关键词： Pixels

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