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5th International Conference on Advancements in Computing, ICAC 2023

作者： Yathurshan, K. Barathy, S. Karini, G. Sajitha, P. Abeygunawardhna, Pradeep Rajapakse, Kaushalya Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Engineering Electrical & Electronic Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

This research paper introduces 'Leaf Guard,' a mobile app designed for disease detection and management in banana trees, specifically tailored for Sri Lanka's agricultural landscape. Through the amalgamation of image processing, deep learning, and customized chemical recommendations, this app proficiently identifies early-stage diseases, offering tailored remedies. Catering to farmers and agricultural experts, 'Leaf Guard' provides an intuitive tool, revolutionizing disease management and bolstering sustainable banana cultivation practices. By seamlessly integrating these cutting-edge technologies, this research significantly advances disease detection methods, paving the way for environmentally friendly and economical interventions. The study's findings not only enrich the realm of disease detection technology but also hold promise for future innovations, fostering sustainable approaches to enhance banana cultivation. © 2023 IEEE.

关键词： Cultivation

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Maximum Power Point Tracking Controller with Neural Gas Network PID of Boost Converter 4

Maximum Power Point Tracking Controller with Neural Gas Netw...

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4th International Conference on Advanced electrical and Energy Systems, AEES 2023

作者： Aly, Rabab Hamed M. Hussein, Aziza I. The Higher Institute for Management and Information Technology Minya Egypt Faculty of Computer Science Nahda University Computer Science Department Beni Suef Egypt College of Engineering Effat University Electrical and Computer Engineering Department Jeddah Saudi Arabia

ISBN: (纸本)9798350342659

Each photovoltaic (PV) system demonstrates a specific point on the current-voltage (IV) curve characteristics where the power generated reaches its maximum value which is referred to as the maximum power point (MPP). The maximum power point tracking (MPPT) system is designed to sample the output of solar cells and adjust the load in order to achieve maximum power output under various environmental conditions. In this paper, a design of a boost converter with MPPT based on a PID controller is proposed. The goal is to optimize the extraction of the highest attainable power from photovoltaic systems. The extracted power is subsequently directed to the load through a boost converter, which elevates the voltage to the necessary level. The PID controller is calibrated by Neural Gas Network (NGN) and utilized to achieve a consistent output voltage irrespective of fluctuations in the power source or the connected load. Moreover, an NGN technique is applied to generate the optimal PID parameters before using the PID. The comprehensive system design depicted has been simulated using MATLAB Simulink to verify the functionality of the system. © 2023 IEEE.

关键词： Controllers

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Data Completeness-aware Transmission Control for Large Spatio-Temporal Data Retention

Data Completeness-aware Transmission Control for Large Spati...

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Kaneyasu, Hotaka Nobayashi, Daiki Tsukamoto, Kazuya Ikenaga, Takeshi Lee, Myung Graduate School of Engineering Kyushu Institute of Technology Fukuoka Japan Kyushu Institute of Technology Faculty of Engineering Department of Electrical and Electronics Engineering Fukuoka Japan Kyushu Institute of Technology Faculty of Computer Science and Systems Engineering Department of Computer Science and Networks Fukuoka Japan City College of New York Department of Electrical and Computer Engineering New York United States

ISBN: (纸本)9781665441544

With the development of IoT technology, various kinds of data are generated by IoT devices. Some of this data contains information on geographical location and time. We refer to such data as spatio-temporal data (STD). Since the 'local production and consumption' of STD is effective for location-dependent applications, we have proposed an STD retention system that utilizes vehicles as data sources. STD sources ranges from simple sensory data to large video data. However, since previous methods assumed to retain an STD consisting of only one packet, retention of large STD sources may suffer from frequent packet collisions due to the increase in the number of packet transmissions. In this paper, we propose a data completeness-aware transmission control mechanism for large STD retention. Our simulation results showed that the proposed scheme reduces channel collision by suppressing the forwarding of incomplete data, and achieved a nearly 100% coverage rate. © 2022 IEEE.

关键词： Internet of things

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Power-flow Conformal Metasurfaces for Transmissive Beam Splitting 16

Power-flow Conformal Metasurfaces for Transmissive Beam Spli...

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16th International Congress on Artificial Materials for Novel Wave Phenomena, Metamaterials 2022

作者： Marcus, S. Epstein, A. Technion - Israel Institute of Technology Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering Haifa Israel

ISBN: (数字)9781665465847

ISBN: (纸本)9781665465847

Omega bianisotropic metasurfaces (MSs) are invaluable for wave control. However, an impediment to their general deployment is the requirement that the power flow be locally conserved across the surface. Attempts to achieve this have included introduction of auxiliary fields in the solution, the determination of which is often nontrivial. Power-flow conformal MSs have been shown to mitigate this need by judicious deformation of the surface profile. Facilitated by our recently proposed Fabry-Perot MS platform, we provide insight herein into the validity of this concept for transmissive electromagnetic beam manipulation. As verified via full-wave simulations for asymmetric beam splitting, such configurations could readily implement nonlocal field transformations, paving the path to perfect field molding in transmission. © 2022 IEEE.

关键词： Electric load flow

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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of Structural and Civil engineering 2024年第3期18卷 393-410页

作者： Tram BUI-NGOC Duy-Khuong LY Tam T TRUONG Chanachai THONGCHOM T.NGUYEN-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer Science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat School of Engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

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An Empirical Investigation in Applying Reliable Industry 4.0 Based Machine Learning (ML) Approaches in Analysing and Monitoring Smart Meters using Multivariate Analysis of Variance (Manova) 2

An Empirical Investigation in Applying Reliable Industry 4.0...

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

作者： Rana, Md. Sohel Dixit, Anil Kumar Rajan, M.Sundar Malhotra, Sumit Radhika, S. Pant, Bhasker Nanjing University of Information and Science Technology Computer Science and Technology India Uttaranchal University Dehradun Department of Lcd India Arbaminch University Faculty of Electrical and Computer Engineering Ethiopia Chandigarh University Computer Science and Engineering Gharuan Mohali India Raghu Institute of Technology Department of CSE AndhraPradesh Visakhapatnam India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9781665437899

Conventional power systems have been evolving towards prospective smart grids in recent decades as market needs have changed and independent innovations, such as the 'Internet of Things' (IoT), have developed. The further automation of traditional development of industrial operations with a variety of current advanced techniques is termed as Industry 4.0. The most efficient strategy to boost the productivity of the enterprise environment, such as smart grids, is to use contemporary control technology that regulates and supervises interaction between smart devices. Furthermore, the advancement of loT -enabled smart meters is aided by a separate data connection, such as 'Bluetooth' or the 'Global System for Mobiles' (GSM), for remotely inspecting and operating smart meters. In this context, SPSS software is used for analysing the role of Industry 4.0 based Machine Learning or ML in analysing Smart Meters and MANOV A (and correlation) approach is considered to get proper result. This study proposes a machine learning-based architecture for analysing and monitoring smart meter data. The advantages of loT integration into Industry 4.0 include the ability to exchange actual information across a wide range of smart meters for various applications, such as factories, hospitals and residences, which is critical for smart grids. Results suggested that Smart Grid is beneficial to the extent of reducing electricity cost;however, maintenance cost and security issues are the major challenging factors in the new technology. © 2022 IEEE.

关键词： Internet of things

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Deployable Wideband Circularly Polarized S-Band Antenna Array for CubeSat Applications 12

Deployable Wideband Circularly Polarized S-Band Antenna Arra...

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12th International electrical engineering Congress, iEECON 2024

作者： Supreeyatitikul, Nathapat Akkaraekthalin, Prayoot Kawdungta, Supakit Phongcharoenpanich, Chuwong Civil Aviation Training Center Aeronautical Engineering Division Bangkok10900 Thailand King Mongkut's University Of Technology North Bangkok Department Of Electrical And Computer Engineering Faculty Of Engineering Bangkok10800 Thailand Rajamangala University Of Technology Lanna Faculty Of Engineering Chiang Mai Thailand School Of Engineering King Mongkut's Institute Of Technology Ladkrabang Bangkok10520 Thailand

ISBN: (纸本)9798350383591

A broadband circularly polarized (CP) S-band antenna array for CubeSat technology was proposed. The proposed CP antenna array comprised of 2 × 2 rectangular-shaped ring patches and sequentially rotated feeding structure. Besides, the sequentially rotated feeding structure is utilized to match impedance. This antenna is made of single-layered Roger RT5880 substrate. The simulation results at 2 GHz achieved IBW of 81% (1.3 - 2.92 GHz) and ARBW of 25% (1.85 - 2.35 GHz). The optimal RHCP gain is 4.69 dBic at 2.25 GHz. The half-power beamwidth at 2 GHz is 71.51°. The radiation patterns are RHCP characteristic. The proposed CP S-band antenna array with sequentially rotated feeding structure is deployed with the CubeSat platform, resulting in the proposed CP antenna array befitting CubeSat technology. © 2024 IEEE.

关键词： Antenna arrays

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All-Angle Nonlocal Metasurfaces on Demand: Universal Realization of Normal Susceptibilities via Multilayered Printed-Circuit-Board (PCB) Cascades

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IEEE Transactions on Antennas and Propagation 2025年

作者： Shaham, Amit Epstein, Ariel Technion–Israel Institute of Technology Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering Haifa3200003 Israel

Embedding normal susceptibilities in metasurfaces (MS), in tandem with their tangential counterparts, greatly enriches their spatial dispersion. Particularly, judicious siphoning of the microscopic nonlocality associated with such enhanced meta-atoms facilitates global control over the MS response across the entire angular range, specifically at challenging near-grazing scenarios. In this paper, we introduce a rigorous closed-form methodology to realize such intricate mixtures of tangential and normal components for transverse-electric waves via a highly practical platform—printed-circuit-board- (PCB) compatible cascaded admittance sheets. To this end, we derive a universal all-angular link between this MS-level composite, which leverages macroscopic nonlocality of multiple reflections, to its underlying meta-atom-level susceptibilities. We demonstrate this scheme by devising a PCB all-angle-transparent generalized Huygens’ MS radome and an all-angle perfect-magnetic-conductor (PMC) PCB MS. Validated in simulation and experiment, our results pave the path toward a new paradigm for studying and engineering nonlocal metadevices, e.g., optical analog computers and spaceplates. © 1963-2012 IEEE.

关键词： Analog computers

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Wireless modulation classification based on Radon transform and convolutional neural networks

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Journal of Ambient Intelligence and Humanized Computing 2023年第5期14卷 6263-6272页

作者： Ghanem, Hanan S. Al-Makhlasawy, Rasha M. El-Shafai, Walid Elsabrouty, Maha Hamed, Hesham F. A. Salama, Gerges M. El-Samie, Fathi E. Abd Department of Electrical Engineering Faculty of Engineering Minia University Minia61111 Egypt Department of Computers and Systems Electronics Research Institute Cairo Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electronics and Communications Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Faculty of Engineering Egyptian-Russian University Cairo Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Convolutional Neural Networks (CNNs) are efficient tools for pattern recognition applications. They have found applications in wireless communication systems such as modulation classification from constellation diagrams. Unfortunately, noisy channels may render the constellation points deformed and scattered, which makes the classification a difficult task. This paper presents an efficient modulation classification algorithm based on CNNs. Constellation diagrams are generated for each modulation type and used for training and testing of the CNNs. The proposed work depends on the application of Radon Transform (RT) to generate more representative patterns for the constellation diagrams to be used for training and testing. The RT has a good ability to represent discrete points in the spatial domain as curved lines. Several pre-trained networks including AlexNet, VGG-16, and VGG-19 are used as classifiers for modulation type from the spatial-domain constellation diagrams or their RTs. Several simulation experiments are presented in this paper to compare different scenarios for modulation classification at different Signal-to-Noise Ratios (SNRs) and fading channel conditions. © 2022, The Author(s).

关键词： Fading channels

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RTF Estimation Using Riemannian Geometry for Speech Enhancement in the Presence of Interferences

RTF Estimation Using Riemannian Geometry for Speech Enhancem...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Or Ronai Yuval Sitton Amitay Bar Ronen Talmon Viterbi Faculty of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

We address the problem of multichannel audio signal enhancement in reverberant environments with interfering sources. We propose an approach that leverages the Riemannian geometry of the spatial correlation matrices of the received signals to estimate the relative transfer function (RTF) of the desired source. Specifically, we compute the spatial correlation matrices in short-time segments, and subsequently, their Riemannian mean, which preserves shared spatial components while attenuating unshared ones. This enables an effective rejection of intermittent interference, leading to accurate RTF estimation. We experimentally show that when the proposed RTF estimation is incorporated into the Minimum Variance Distortionless Response (MVDR) beamformer, it enhances the desired signal, outperforming the MVDR beamformer that is based on standard (Euclidean) RTF estimation. These favorable experimental results are demonstrated in challenging acoustic environments including multiple strong interfering sources, noise, and reverberations.

关键词： Geometry Correlation Acoustic distortion Noise Estimation Transfer functions Interference Speech enhancement Reverberation Standards

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