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Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Dharmesh Dhabliya Vikash Kumar Kharbas Amritpal Sidhu Shweta Singh Gowrishankar J Jaisudha J Department of Information Technology Vishwakarma Institute of Information Technology Pune Maharashtra India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Ramnagar Karnataka India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai

Cooperative spectrum sharing is a method to allocate the radio spectrum amongst users for high-velocity wireless networks. It entails multiple unbiased customers that cooperate to percentage their respective spectra to maximize the records fee and the practical spectrum usage. The cooperative spectrum sharing technique lets non-overlapping frequency bands be utilized by multiple customers supplying a high statistics fee with minimum interference. It affords a green way of handling the radio spectrum, permitting multiple customers to share the to-be-had spectrum sources rather than having an unmarried consumer monopolize an upbeat frequency band. Cooperative spectrum sharing is likewise tremendous because of its low implementation cost and occasional power intake. Furthermore, it could be fast deployed to numerous areas to meet the increasing demand for excessive-speed Wi-Fi networks.

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High gain dual polarized antenna using a narrow pulse model in minkowski fractal patch 18

High gain dual polarized antenna using a narrow pulse model ...

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18th International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON 2021

作者： Wongsin, Norakamon Suangun, Thanakarn Mahatthanajatuphat, Chatree Akkaraekthalin, Prayoot Torrungrueng, Danai Rakluea, Paitoon Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunications Pathum Thani Thailand University of Phayao Faculty of Engineering Department of Electrical Engineering Phayao Thailand King Mongkut's University of Technology North Bangkok Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Department of Teacher Training in Electrical Engineering Bangkok Thailand

ISBN: (纸本)9780738111278

High Gain Dual Polarized Antenna using narrow pulse model in Minkowski fractal Patch (MFP) is presented. This design consists of dual fed by two transmission line feed connectors placed onto the lower substrate as the feeding system, square patch antenna with a dimension of 60 mm × 60 mm, and dual-polarized MFP putting on the upper substrate. The simulated result shows that the antenna has a resonant frequency at 3.48 GHz, by the distance between MFP and square patch antenna is 10 mm. However, the radiation pattern between vertical and horizontal feed for standalone square patch antenna provides a similar gain of 2 dBi. The 2D Radiation patterns on the X-Z plane at phi-angle 45 and -45 degrees are dual-polarization. Moreover, the proposed antenna with MFS improves the gain of 5.6 dBi at 0 degrees on the X-Z plane at phi-angle 45 degrees and -45 degrees with HPBW of 71.7 degrees and 80.4 degrees, respectively. © 2021 IEEE.

关键词： Fractals

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An Enhanced Deep Neural Network Enabled with Cuckoo Search Algorithm for Intrusion Detection in Wide Area Networks 5

An Enhanced Deep Neural Network Enabled with Cuckoo Search A...

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5th International Conference on Information technology for Education and Development, ITED 2022

作者： Jimoh, Rasheed Gbenga Imoize, Agbotiname Lucky Awotunde, Joseph Bamidele Ojo, Stephen Akanbi, Mulikat Bola Bamigbaye, Jesufemi Ayotomide Faruk, Nasir University of Ilorin Faculty of Communication and Information Sciences Department of Computer Science Ilorin Nigeria University of Lagos Department of Electrical and Electronics Engineering Nigeria Institute of Digital Communication Ruhr University Department of Electrical Engineering and Information Technology Bochum44801 Germany Anderson University Department of Electrical and Computer Engineering AndersonSC29621 United States Kwara State Polytechnic Department of Computer Science Ilorin Nigeria Sule Lamido University Department of Physics Nigeria SLU Directorate of ICT Nigeria

ISBN: (纸本)9781509064229

A diversity of harmful software has been created as a result of the dramatic increase in internet usage, posing major risks to computer security. There is a great probability that the numerous computing operations performed through the network will be interfered with or altered, and as a result, effective intrusion detection systems are imperative. In addition, the attacks on the network are unpredictable, something that emphasizes the value of creating effective classification and prediction models. Machine learning (ML) and Deep Learning techniques have been used to evaluate datasets for intrusion detection systems (IDS). The employment of the DL-based approach enabled by feature selection helps to address challenges with data quality, handling high-dimensional data, and other related issues. Therefore, due to the large nature and volume of the IDS datasets, and the ability of DL-based models to learn categories incrementally through their hidden layer architecture to produce more accurate results in big data, this study proposes a Long-Short-Term-Memory (LSTM) model, and to further enhance the classification capacity of the projected DL method, the cuckoo search algorithm was introduced to select optimal features from the wireframe. The accuracy and subsequent detection of the suggested model positive and negative rates were evaluated. The experimental results show that the LSTM outperformed some other existing models with the highest classification accuracy of 99.7% and an error rate of 0.006. © 2022 IEEE.

关键词： Long short-term memory

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Multi-Band Low-Profile Non-Uniform Metasurface Antenna for Sub-6-GHz Applications

Multi-Band Low-Profile Non-Uniform Metasurface Antenna for S...

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World Congress on Computing and Communication Technologies (WCCCT)

作者： Naveed Hamid Nawaz Khan Botao Feng Li Deng Wei Yang Xiao Ding Qingsheng Zeng College of Electronics and Information Engineering Shenzhen University Shenzhen China College of Information and CommunicationEngineering Beijing University of Posts and Telecommunications Beijing China College of Big Data and Internet Shenzhen Technology University Shenzhen China Faculty of Humanities and Arts Macau University of Science and Technology Macau China Department of Computer and Engineering University of Quebec in Outaouais Quebec Canada

ISBN: (数字)9798331512620

ISBN: (纸本)9798331512637

This paper presents the design of a compact nonuniform metasurface antenna with dimensions of 70×70 mm 2 . The antenna basically comprises a 1.6 mm-thick metasurface patch and a 1 mm-thick substrate, separated by a 5-mm air gap to enhance performance. The proposed design is analyzed using CST Microwave Studio, evaluating key parameters such as Voltage Standing Wave Ratio (VSWR), |S11|, and radiation efficiency. Simulation results indicate excellent impedance matching, with |S11| below −10 dB across 2.35 GHz to 6 GHz, reaching a minimum of −36.647 dB at 5.16 GHz. The VSWR remains below 2.5, with a minimum of 1.5 at 5.16 GHz. Additionally, the antenna demonstrates high radiation efficiency, ranging 74% to 80.7%, indicating effective energy radiation. The experiment results highlight the potential of the proposed non-uniform metasurface antenna for next-generation wireless communication systems, especially for 5G and beyond, where compact size, broad bandwidth, and high efficiency are essential. Notably, the integration of a non-uniform metasurface geometry and strategically placed air gap enhances overall performance, making it a promising candidate for future wireless technologies.

关键词： Wireless communication 5G mobile communication Impedance matching Simulation Air gaps Voltage Metasurfaces Antennas Substrates Next generation networking

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Fast Simple Image Encryption Technique Based on Chaos Based System

Fast Simple Image Encryption Technique Based on Chaos Based ...

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Telecommunications Conference (ITC-Egypt), International

作者： Tamer O.Diab Wageda I.Al Sobky Salwa M. SeragEldin Ahmed Khairy Mahmoud Hany Nasry Zaky Mofreh A. Hogo Electrical Engineering Department Benha Faculty of Engineering Banha University Banha Egypt Basic Engineering Sciences Department Faculty of Engineering Banha University Banha Egypt Department of Computer Engineering College of Computers and Information Technology Taif University Department of Electronics and electrical communications Engineering Faculty of Engineering Tanta University Air Defense College Alexandria University Alexandria Egypt Department of Mathematics Military Technical College Egypt

In this paper, a novel image encryption technique based on chaotic maps is described. Encrypting an image with chaotic maps ensures that the safe cipher characteristics of confusion and diffusion are met. Moreover, chaos-based image cryptosystems have many features compared to the classical cryptographic techniques such as fast, effective security, minimum computing overheads, extremely sensitive to the control parameters and initial settings. These all features make effective encryption techniques with the best performance. Four chaotic maps are used in the proposed scheme to generate the encryption key, initial vector, and ciphering encryption S-Boxes. The maps used are the Chebyshev map, 1D improved quadratic map, 1D Improved Logistic Map and Altered Sine-Logistic based Tent map ASLT.

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A Synergy of Freezing and Dropout - A New Learning Strategy of Convolutional Networks 19th

A Synergy of Freezing and Dropout - A New Learning Strategy ...

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19th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2020

作者： Banach, Michal Skubalska-Rafajlowicz, Ewa Faculty of Electronics Department of Computer Engineering Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (纸本)9783030614003

In this work, we explore training efficiency and generalization results on testing sets of a new learning strategy applied to convolutional neural networks. The proposed strategy is to limit the modification of the weights of the networks entering a randomly selected set of neurons (activation function). Randomizing a fragment of the network whose parameters are modified is carried out in parallel with the selection of a mini-batch based on which a stochastic gradient is determined. The strategy of combining dropout with random freezing allows for better generalization while shortening the duration of training in individual epochs. An interesting phenomenon is the widening of the generalization gap while reducing the error on the test set. Computational experiments were carried out on CNN networks with about 1–2 M trainable parameters and CIFAR-10 and CIFAR-100 benchmark data sets. © 2020, Springer Nature Switzerland AG.

关键词： Image classification

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New hybrid method for feature selection and classification using meta-heuristic algorithm in credit risk assessment

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Iran Journal of computer Science 2020年第1期3卷 1-11页

作者： Nourmohammadi-Khiarak, Jalil Feizi-Derakhshi, Mohammad-Reza Razeghi, Fatemeh Mazaheri, Samaneh Zamani-Harghalani, Yashar Moosavi-Tayebi, Rohollah Faculty of Electronics and Information Technology Warsaw University of Technology Warsaw Poland Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Faculty of Electrical and Computer Engineering Islamic Azad University Sari Iran Faculty of Computer Science and Information Technology Universiti Putra Malaysia (UPM) Seri Kembangan Malaysia

Credit risk is a factor that arises from the failure of the party to the contract. It is one of the most important factors of risk production in banks and financial companies. Still, there is no standard set of features or indices which have been declared through all credit institutions and according to the classification of customers, they are able to do through terms of credit value. In this paper, a meta-heuristic of imperialist competitive algorithm with modified fuzzy min–max classifier (ICA-MFMCN) is offered to identify an optimal subset of features and increased through accuracy classification and scalability through assessment of credit risk. Performance of proposed ICA-MFMCN classification is approved and recognized using a real credit set that has been selected from a UCI dataset. Classification accuracy is comparable for what has been indicated through resources. The experimental which result, in obtaining new classification by utilizing the proposed are promising for future classification are selection processes in assessment of credit risk through retail, indicating that ICA-MFMCN is one of the ways which can be used to add existing data mining techniques. © The Author(s) 2019.

关键词： Credit risk Feature selection Imperialist competitive algorithm and modified fuzzy min–max classifier

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Development of compact size on UWB slot antenna using stair-step impedance with pentangular stub for supporting 5G application 18

Development of compact size on UWB slot antenna using stair-...

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18th International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON 2021

作者： Suangun, Thanakarn Wongsin, Norakamon Mahatthanajatuphat, Chatree Akkaraekthalin, Prayoot Torrungrueng, Danai Rakluea, Paitoon University of Phayao Faculty of Engineering Department of Electrical Engineering Phayao Thailand Rajamangala University of Technology Thanyahuri Faculty of Engineering Department of Electronics and Telecommunications Pathum Thani Thailand King Mongkut's University of Technology North Bangkok Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Department of Teacher Training in Electrical Engineering Bangkok Thailand

ISBN: (纸本)9780738111278

This paper presents a development of a compact ultra-wideband (UWB) slot antenna using stair-step impedance technique with a pentangular stub for 5G application. The proposed antenna is miniaturized and fabricated on a very cheap FR4 substrate with a dimension of 20x22 mm2. Also, the stair-step segments and a pentangular stub in the slot antenna provide improving the impedance bandwidth. The stair-step segments are used to tuning at a lower frequency, and a pentangular stub provides to tuning the higher frequency. The proposed antenna can operate the frequency range between 3.1 GHz to 14 GHz. The radiation pattern is bidirectional throughout the operating frequency range, while the average antenna gain is about 3.5 dBi. © 2021 IEEE.

关键词： Slot antennas

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Comparison of Epilepsy Induced by Ischemic Hypoxic Brain Injury and Hypoglycemic Brain Injury using Multilevel Fusion of Data Features

arXiv

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arXiv 2024年

作者： Kadem, Sameer Sami, Noor Elaraby, Ahmed Alyousif, Shahad Jalil, Mohammed Altaee, M. Almusawi, Muntather Ghany, Ismaeel A. Kareem, Ali Kamil Kamalrudin, Massila Ftaiet, Adnan Allwi Dijlah University College Baghdad Iraq Department of Computer Engineering Techniques Mazaya University College Th Qar Iraq Department of Computer Science Faculty of Computer Science and Information South Valley University Qena Egypt Department Of Cybersecurity College of Engineering and Information Technology Buraydah Private Colleges Buraydah Saudi Arabia Department of Electrical and Electronic Engineering College of Engineering Gulf University Sanad26489 Bahrain Research centre Northampton University Faculty of Engineering Department of Electrical and Electronics Engineering University Drive Northampton NN1 5PH United Kingdom Department of Computer Science Alturath University College Baghdad Iraq Department of Medical Engineering Techniques Alfarahidi University Baghdad Iraq College of Technical Engineering The Islamic University Najaf Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq Department of Biomedical Engineering Al-Mustaqbal University College Hillah51001 Iraq Faculty of Information & Communication Technology Universiti Teknikal Malaysia Melaka Durian Tunggal Melaka75450 Malaysia Medical Instruments Engineering Techniques National University of Science and Technology Thi Qar Iraq

The study aims to investigate the similarities and differences in the brain damage caused by Hypoxia-Ischemia (HI), Hypoglycemia, and Epilepsy. Hypoglycemia poses a significant challenge in improving glycemic regulation for insulin-treated patients, while HI brain disease in neonates is associated with low oxygen levels. The study examines the possibility of using a combination of medical data and Electroencephalography (EEG) measurements to predict outcomes over a two-year period. The study employs a multilevel fusion of data features to enhance the accuracy of the predictions. Therefore this paper suggests a hybridized classification model for Hypoxia-Ischemia and Hypoglycemia, Epilepsy brain injury (HCM-BI). A Support Vector Machine is applied with clinical details to define the Hypoxia-Ischemia outcomes of each infant. The newborn babies are assessed every two years again to know the neural development results. A selection of four attributes is derived from the Electroencephalography records, and SVM does not get conclusions regarding the classification of diseases. The final feature extraction of the EEG signal is optimized by the Bayesian Neural Network (BNN) to get the clear health condition of Hypoglycemia and Epilepsy patients. Through monitoring and assessing physical effects resulting from Electroencephalography, The Bayesian Neural Network (BNN) is used to extract the test samples with the most log data and to report hypoglycemia and epilepsy patients non-invasively. The experimental findings demonstrate that the suggested strategy improves accuracy by 95.05% and reduces the error rate to 0.41 when comparing diseases. © 2024, CC0.

关键词： Electroencephalography

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A Non-contact Microwave Sensor System for Characterizing a Binary-liquid Mixed Concentration

A Non-contact Microwave Sensor System for Characterizing a B...

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International Electrical engineering Congress (iEECON)

作者： Somporn Seewattanapon Apirada Namsang Reungyot Lerdwanittip Prayoot Akkaraekthalin Chawalit Rakluea Nattapong Duangrit Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi Thailand Aeronautical Engineering Division Civil Aviation Training Center Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Electronics and Telecommunication Engineering Rajamangala University of Technology Thanyaburi Pathumthani Thailand Centre of Observatory Operation and Engineering National Astronomical Research Instituite of Thailand Chiangmai Thailand

This research presents a design and analysis of an open-loop microstrip resonator which is integrated with a microwave sensor system. It is used for measuring a binary-liquid mixed concentration of sodium chloride (NaCl) and DI-water to detect salinity level. The open-loop resonator is designed to provide a band-stop bandwidth of 1 GHz, which has operated from 2 GHz to 3 GHz. The proposed microwave sensor system consists of a microwave synthesizer, a voltage detector, and an open-loop resonator that is designed to operate at 3 GHz to characterize the salinity level of the sample liquid mixture. A liquid mixture samples of NaCl and Distill-water with 5 different concentration levels of 0%, 2%, 5%, 10%, and 20% were used to assess the salinity level for the proposed microwave sensor system.

关键词： Chlorine compounds Microwave measurement Microstrip resonators Liquids Voltage measurement Salinity (geophysical) Synthesizers

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