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6th International Conference on informatics and Computing, ICIC 2021

作者： Putra, Farrel Athaillah Jamil, Dwi Anggun Cahyati Prabandanu, Briliantino Abhista Faruq, Suhaili Pradana, Firsta Adi Alya, Riqqah Fadiyah Santoso, Heru Agus Al Zami, Farrikh Saputra, Filmada Ocky Dian Nuswantoro University Informatics Engineering Semarang Indonesia Diponegoro University Computer Engineering Semarang Indonesia Telkom Institute of Technology Informatics Engineering Purwokerto Indonesia

ISBN: (纸本)9781665421553

Batik is one of Indonesia's cultural heritages that UNESCO has recognized as an Intangible Cultural Heritage, so we should be proud and preserve it. However, there are problems in the batik industry related to the labelling of traditional and modern batik products. The prevalence of fraud in printed batik, which is given a price equivalent to written batik, which is much more expensive, and public ignorance of the aesthetic value and authenticity of written batik, can disrupt the traditional batik industry in Indonesia. Based on these problems, the authors innovate to develop a machine learning model that aims to classify the authenticity of batik using the Convolutional Neural Network Algorithm with Transfer Learning Method. The classification process consists of several stages: collecting datasets, preprocessing data, developing CNN models with transfer learning, and compiling and training models. The development of the machine learning model that has been trained produces an accuracy of 96.91%. The author hopes that this research can make it easier for people to distinguish between written and printed batik, minimize the existence of batik price fraud, and increase consumer confidence in batik transactions by ensuring the originality of batik products. © 2021 IEEE.

关键词： Classification (of information)

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1-Bit Reconfigurable Phase Shifter for mm-Wave Antenna Beam-Steering Applications

1-Bit Reconfigurable Phase Shifter for mm-Wave Antenna Beam-...

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Antennas and Propagation Society International Symposium

作者： Asif Bilal Abdul Quddious Atsushi Kanno Tetsuya Kawanishi Marco A. Antoniades Stavros Iezekiel EMPHASIS Research Centre University of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Chair for RF and Photonics Engineering Technische Universität Dresden Dresden Germany Nagoya Institute of Technology Aichi Japan National Institute of Information and Communications Technology Tokyo Japan Waseda University Tokyo Japan Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto ON Canada

A 1-bit reconfigurable phase shifter for 28 GHz mm-wave beam steering antennas is proposed. The design uses two beam-lead GaAs PIN diodes loaded on a microstrip transmission line in parallel, to provide two discrete phases for the transmitted signal. When the diodes are switched OFF, no shift in the phase of the transmitted signal is observed while a phase shift of ~90° is achieved when the diodes are switched ON. The total length of the phase shifter is $\sim\lambda /2$ . The compact size, low cost, reduced complexity and easy adaptation in antenna and phased array technology makes it a suitable candidate for 5G mm-wave beam steering applications.

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An Authenticated Method for a Secure Changing Password 5

An Authenticated Method for a Secure Changing Password

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5th International Conference in Electronic engineering, Information technology and Education, EEITE 2024

作者： Kara, Mostefa Karampidis, Konstantinos Kenioua, Laid Karampidis, Manolis Alshaikh, Muath Papadourakis, Giorgos Laouid, Abdelkader National Higher School of Mathematics Scientific and Technology Hub of Sidi Abdellah Algiers16093 Algeria Hellenic Mediterranean University Department of Electrical and Computer Engineering Crete Greece El Oued University LIAP Laboratory PO Box 789 El Oued39000 Algeria College of Computing and Informatics Saudi Electronic University Computer Science Department Riyadh11673 Saudi Arabia

ISBN: (纸本)9798350372878

Despite their age, passwords are still widely used more than ever. In many cases, it is the solution that best fits the usage scenario. Researchers are proposing innovative designs and methods to support these scenarios. Many systems, especially sensitive ones, need to change the password. Classic systems rely on changing passwords in two stages, the first i s authentication, which usually consists of two or three rounds, and the second is creating a new password (PW), which also consists of two or three rounds. In this paper, a hidden transmission of a new random PW using the previous one is presented, we talk about an authenticated changing of PW. The verifier g enerates half of the new password and sends it to the prover, the prover authenticates the sent message using the old PW and then returns the authentication proof. After checking it, the verifier creates the second half of the PW. The proposed method combines the authentication and change PW processes into one process consisting of 3 rounds. Therefore, the proposal facilitates the process of automatic periodic change of PW between two entities (user, app, system, etc). Analysis and experiments show that our technique is robust, lightweight, and reduces many potential risks in the field. © 2024 IEEE.

关键词： Authentication Protocol

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Atomic Lifecycle for Cyber Threat Intelligence

Atomic Lifecycle for Cyber Threat Intelligence

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Information Security and Cryptology (ISCTURKEY), International Conference on

作者： Süleyman Muhammed Arikan Aynur Koçak Mustafa Alkan Computer Forensics Institute of Informatics Gazi University Ankara Turkiye Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Turkiye

ISBN: (数字)9798331533649

ISBN: (纸本)9798331533656

The utilisation of cyber threat intelligence provides a multitude of advantages in the assurance of security. A growing body of research is being published on the subject of cyber threat intelligence. However, the precise sequence of steps involved in the cyber threat intelligence life cycle remains unclear. The life cycle presented in each study is not consistent. Moreover, the transition from data to intelligence throughout the life cycle is not sufficiently delineated. The intelligence produced in many studies can be of different types. In our study, all existing lifecycles were examined and their naming approaches were analysed. The objective was to present a cyber threat intelligence life cycle that is as atomic as possible, with each step clearly expressed. This should facilitate a more rigorous comparison of studies in the existing literature on cyber threat intelligence. Furthermore, the life cycle can be utilised in new cyber threat intelligence studies. Researchers who aspire to implement best practices in their study are able to run more effective processes by following the life cycle.

关键词： Accuracy Cyber threat intelligence Security Best practices Standards

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Distillation of ensemble adaptive teacher assistant knowledge

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International Journal of Machine Learning and Cybernetics 2025年 1-16页

作者： Zhao, Lei Ng, Wing W. Y. Zhang, Jianjun School of Future Technology South China University of Technology Guangzhou China Peng Cheng Laboratory Shenzhen China School of Computer Science and Engineering South China University of Technology Guangzhou China College of Mathematics and Informatics South China Agricultural University Guangzhou China

Knowledge distillation is a proven compression technique for training student models with the guidance of pre-trained teacher models, highlighting the importance of acquiring various facets of information from these teachers. An alternative method for diversifying knowledge involves incorporating perspectives and characteristics from multiple teachers, which allows students to develop a more nuanced understanding. However, existing multi-teacher distillation methods primarily focus on ensemble strategy design and often overlook the gap between teacher and student models. With this in mind, we propose a distillation methodology named Ensemble of Adaptive Teacher Assistant Knowledge (EATAD), which employs teaching assistants to bridge the gap between teachers and students while offering diverse insights. This method not only enhances knowledge diversity but also facilitates a deeper understanding of teacher behavior among students. Specifically, an adapter module is utilized to fine-tune pre-trained teachers, yielding novel networks termed adaptive teacher assistants (ATA) that help reduce the gap between teachers and students. The diversity of distilled knowledge is improved by simultaneously integrating the knowledge from both teachers and assistants. Experimental results show that the proposed EATAD achieves state-of-the-art performance on standard benchmarks, i.e., CIFAR-100 and ImageNet, under both similar-architecture and cross-architecture settings.

关键词： Adapter Fine-tune Knowledge distillation Teacher assistant

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Wide-Area Backup Protection Against Asymmetrical Faults in the Presence of Renewable Energy Sources

SSRN

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SSRN 2022年

作者： Jegarluei, Mohammad Rezaei Aristidou, Petros Azizi, Sadegh The School of Electronic and Electrical Engineering University of Leeds LeedsLS2 9JT United Kingdom The Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol3036 Cyprus

Conventional protection schemes have essentially been developed for power systems dominated by synchronous generators. High penetration of power-electronic interfaced renewable energy sources (PEIRESs) can adversely impact the reliability of protection systems, thereby increasing the risk of widespread disturbances. This paper proposes a robust wide-area backup protection (WABP) scheme against asymmetrical faults for transmission systems with high penetration of renewables. The scheme exploits the full potential of available synchrophasors without placing any rigid constraints on PMU locations. To this end, the faulted line and a few appropriately selected PEIRESs are replaced by equivalent current sources using the Substitution Theorem. The remaining PEIRESs are substituted by their equivalent impedances accounting for their response to a fault, considering the control strategies and overcurrent limits of these PEIRESs. This results in a linear system of equations whose solution readily indicates the faulted line on account of the weighted sum of squared residuals ( WSSR ) concept. To add to the security of the proposed scheme, the fault distance on the pinpointed line is also calculated and checked to ensure it lies within the acceptable range. A total of more than 80,000 simulations conducted on the IEEE 39-bus test system verify that the proposed scheme performs properly irrespective of the numbers/locations of PEIRESs and their control strategies. © 2022, The Authors. All rights reserved.

关键词： Timing circuits

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Predicting Student Academic Performance Using an Optimised Regression Machine Learning Model

Predicting Student Academic Performance Using an Optimised R...

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International Conference on Adaptive Science & technology (ICAST)

作者： Ezekiel Mensah Martey Abubakar Abdullah Obed Appiah Department of Computer Science and Engineering University of Mines and Technology (UMaT) Tarkwa Ghana Department of Computer Science and Informatics University of Energy and Natural Resources (UENR) Sunyani Ghana

ISBN: (数字)9798350385403

ISBN: (纸本)9798350385410

Machine learning has emerged as one transformative tool in predicting student academic performance. This study evaluates machine learning models regression in predicting student academic performance. It can be found optimised Support Vector Regression (SVR) model accurately predicts student academic performance using a benchmark dataset from Kaggle. The approach incorporated Recursive Feature Elimination (RFE) for optimal feature selection while key parameters of the SVR model are tuned through grid search optimisation to enhance model performance. The optimised SVR model achieves exceptional predictive accuracy with an R-squared value of 0.97, Mean Absolute Error of 2.98, Mean Squared Error of 13.28, Root Mean Squared Error of 3.64, Median Absolute Error of 2.65, and Mean Absolute Percentage Error of 0.23. Comparative analysis demonstrates the superior performance of optimised SVR model against Decision Tree, Random Forest, K-Nearest Neighbors, Bayesian Ridge, and Gradient Boosting models. Experimental results demonstrate the validity of robustness and reliability of our approach, offering valuable insights for educational institutions to develop targeted interventions and support systems.

关键词： Support vector machines Analytical models Machine learning algorithms Predictive models Prediction algorithms Boosting Real-time systems Decision trees Random forests Optimization

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The Application of Smart and Precision Agriculture (SPA) for Measuring Leaf Nitrogen Content of Oil Palm in Peat Soil Areas

The Application of Smart and Precision Agriculture (SPA) for...

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2023 International Conference on computer Science, Information technology and engineering, ICCoSITE 2023

作者： Munir, Sirojul Seminar, Kudang Boro Sudradjat Sukoco, Heru Bogor Agricultural University Departemen of Computer Science Bogor Indonesia Nurul Fikri College of Technology Departemen of Informatics Depok Indonesia Bogor Agricultural University Departement of Mechanical and Biosystem Engineering Bogor Indonesia Bogor Agricultural University Department of Agronomy and Horticulture Bogor Indonesia Bogor Agricultural University Department of Computer Science Bogor Indonesia

ISBN: (纸本)9798350320954

One of the laborious tasks in operating and managing oil palm lands is measuring the nutrient content of leaves in a timely and periodic manner. It takes a manual process and takes a long time to get leaf samples that are representative of the observed oil palm area, especially in peat soil area. In addition, laboratory analysis of leaf samples is expensive and introduces creates significant time delays for queuing. This paper discusses methods for measuring leaf nitrogen levels in a timely manner based on imagery obtained by C-SAR Sentinel-1A using smart and precision agricultural approaches and applications. The intelligent computational model uses Random Forest Regression to calculate leaf nitrogen content based on spatial image processing and analysis. The calculated leaf nitrogen content is then used to examine and identify the variability of nitrogen content in a given oil palm area. Identification of nutrient variability is one of the approaches and goals of precision agriculture. Our computation model was developed using 553 leaf sampling units (LSU) and validated using 10-Fold validation method, resulting in correctness, MAPE, RMSE and R2 of 95.69%, 4.31%, 0.1119 and 93.28% respectively. The validated model was tested using a set of new data, which is not in the data samples for model development and validation, was resulting in correctness, MAPE, RMSE and R2 of 89.91%, 10.11%, 0.284, and 53.89% respectively. The visual maps can be produced and displayed to visualize variability of nitrogen contents in a peat soil area. This improves visibility and transparency in monitoring nutrient in timely and periodic manner. The future use of the proposed method is to support the application of smart and precision agriculture practices to recommend fertilizers types and dozes for oil palm in peat soil areas based on the variability of leaf nutrient contents. © 2023 IEEE.

关键词： Intelligent systems

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Millimeter-Wave Gap Waveguide-Based Broadband Slant-Polarized Slot Array Antenna

Millimeter-Wave Gap Waveguide-Based Broadband Slant-Polarize...

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European Conference on Antennas and Propagation, EuCAP

作者： Davood Zarifi Ali Farahbakhsh Michal Mrozowski Department of Microwave and Antenna Engineering Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Gdansk Poland School of Electrical and Computer Engineering University of Kashan Kashan Iran Department of Electrical and Computer Engineering Graduate University of Kerman Kerman Iran

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This research deals with the design of a broadband, slant-polarized antenna array for 26–40 GHz frequency band. The design employs gap waveguide technology to minimize unwanted energy leakage, ensuring high gain and efficiency. In this configuration, the radiating slots are angled at 45°, and a two-layer feed network, utilizing compact folded E-plane groove gap waveguide power dividers, is used to energize the slots. Key advantages of the proposed antenna array include its low profile, low loss, wide bandwidth, and suitability for millimeter-wave applications.

关键词： Power dividers Slot antennas Millimeter wave technology Optical device fabrication Gap waveguide Bandwidth Millimeter wave propagation Broadband communication Broadband antennas Antenna arrays

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A Framework for Big Data Analytics with Wireless Communication of Network, Internet of Things and Cyber Security 2

A Framework for Big Data Analytics with Wireless Communicati...

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2nd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Tedyyana, Agus Sivakumar, G. Kumar, Anuj Velayudham, A. Pavithra, M. Gangodkar, Durgaprasad Politeknik Negeri Bengkalis Department of Informatics Engineering Indonesia Electronics and Communication Engineering Ramco Institute of Technology Rajapalayam India Uit Uttaranchal University Dehradun India Jansons Institute of Technology Department of Computer Science and Engineering Karumathampatti Coimbatore India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9781665437899

Nowadays, big data is being implemented in various fields due to its advantages in risk management, healthcare and other business fields. The conventional big data analytics system is not highly promising for implementation in every system. Therefore, the developers are integrating the Internet of Things (IoT), wireless communication and cyber security systems to strengthen the capability of big data analytics. The current research has explained the framework for big data analytics with IoT, wireless communication and cyber security. Initially, past literature was explained, and then, the research methodology has been described. Primary survey-based research has been conducted with 54 data analysis experts to understand the framework of big data, its applications and solutions for cyber security-based issues. Findings showed that a VPN system with a firewall is a great choice for preventing external attacks. Moreover, as the primary data suggested the use of encryption systems, the researchers used SHA-256 ('Secure Hashing Algorithm') for protecting the collected big data. Internet of Things (IoT) devices is used for collecting customer and operational data. After that, the data is collected via a wireless network and transferred to the respective access points. Users can access the data from access points and can generate meaningful information for executing various purposes. © 2022 IEEE.

关键词： Data Analytics

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