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Science, engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Emmanuel Adetiba Olumide O. Oluleye Ayodele H. Ifijeh Victoria Oguntosin Olatayo M. Olaniyan Olubunmi Adewale Akinola Gbenga Afolabi Jacob O. Odetola. Abdultaofeek Abayomi Dept. of Electrical & Information Engineering Covenant University Ota Ogun State Nigeria HRA Institute for -Systems Science Durban University of Technology Durban South Africa Dept. of Computer Engineering Federal University Oye-Ekiti Ekiti State Nigereia Dept. of Information and Communication Technology Mangosuthu University of Technology Durban South Africa

Solar irradiance is the energy per unit area received by the Sun as electromagnetic radiation. It is one of the most important renewable energy sources. Photovoltaic or other solar technologies are used to generate power more accurately than direct sun irradiation. Solar irradiance research and measurement have a variety of critical applications, including forecasting power generation from solar power plants, climate modeling, and weather forecasting. This paper presents a neural network-based system identification model developed using measured parameters from solar panels with various wattage specifications, namely, 10W, 20W, 40W, and 100W. The parameters that were measured to train the ANN model for the prediction of the output current and voltage include the angle of panel orientation, panel temperature, ambient temperature, irradiance, and wattage. Several training experiments were conducted and the best ANN model produced at 500 epochs gave an accuracy of 99.81% and a loss of 0.1940. The model was deployed into an intelligent Web App that was also developed in this study. This app could be a potential tool for renewable energy engineers and researchers.

关键词： Temperature measurement Renewable energy sources Voltage measurement Current measurement Weather forecasting Solar energy Predictive models

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Frequency Selective Surface (FSS) Radiofrequency Shield of Solenoid Coil for Low-Field Portable MRI

TechRxiv

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TechRxiv 2023年

作者： Rajendran, Meena Yang, Junqi Tingou, Liang Yu, Wenwei Chen, Xudong Huang, Shao Ying Pillar of Engineering Product Development Singapore University of Technology and Design Singapore Center for Frontier Medical Engineering Chiba University Japan Dept. of Electrical and Computer Engineering National University of Singapore Singapore

In this paper, lightweight cylindrical Frequency Selective Surface (FSS) using high-pass inductive mesh grid is proposed as a radiofrequency (RF) shield for solenoid coils at 2.84 MHz working in a portable MRI system with a transversal B0-field averaged at 67 mT. Using a solenoid coil of 60 mm diameter as an example, the proposed FSS shield shows good shielding effectiveness at different wall-to-wall distances between the coil and the shield (5-25 mm). It also shows less compromise in B1-sensitivity when compared to the coil with a copper shield. The effects of the FSS shield were examined numerically and validated experimentally. When the wall-to-wall distance is 5 mm, the solenoid coil with the proposed FSS shield is compact, lightweight, and shows B1-sensitivity of more than 50% higher than the copper counterparts with comparable shieding effectiveness. Compared to an unshielded coil, it shows a wider bandwidth which benefits the excitation of an MRI system that has less homogeneous fields and a smaller inductance which indicates less trapping of energy and thus can enable different pulse sequence programming by taking this approach. This study shows that an FSS shield with inductive mesh grids around a solenoid coil is a promising approach for compact shielding without a big shielding box. It will contribute to the compactness of a portable MRI system. The study can be extended to other types of FSS for compact shielding for other RF coils. © 2023, CC BY-NC-SA.

关键词： Mesh generation

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B2G (Buggy-to-Grid): Vehicle-to-Grid (V2G) concept in microgrids with strong penetration of electric vehicles

B2G (Buggy-to-Grid): Vehicle-to-Grid (V2G) concept in microg...

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International Young Engineers Forum (YEF-ECE)

作者： Guilherme Santos Joã o Murta Pina Ricardo Belé m Dept. of Electrical and Computer Engineering NOVA School of Science and Technology (FCT NOVA) Caparica Portugal Centre of Technology and Systems (CTS-UNINOVA) NOVA School of Science and Technology (FCT NOVA) Caparica Portugal Technical Director Dom Pedro Investimentos Lisboa Portugal

ISBN: (数字)9781665467315

ISBN: (纸本)9781665467322

This paper aims to evaluate the potential of integrating Vehicle-to-Grid (V2G) technology into a golf course, together with a self-consumption Photovoltaic (PV) system, by using the surplus generated energy to charge the golf buggies and later discharging it according to the course needs. The Dom Pedro Golf Course, located in the south of Portugal, is used as a case study. Its PV system compromises 244 solar panels with 97.6 kWp total, and a predicted annual first-year generation of 176.70 MWh and 9.34 MWh of surplus, that the buggies could discharge through V2G technology. With these integrated technologies, the first year of investment results includes 87% Performance Ratio (PR), 100% of Self-Consumption Ratio (SCR), and 35% Self-Sufficiency Ratio (SSR), while the Benefit-Cost Ratio (BCR) of the V2G technology alone for the whole considered investment horizon of ten years is 1.79. An economic assessment of the project showed that results followed the same positive trend, with a Net Present Value (NPV) of 50,353.42€, an Internal Rate of Return (IRR) of 13%, a Payback Period (PP) of seven years, and a Levelized Cost of Energy (LCOE) of 0.1315 €/kWh, suggesting a beneficial and feasible result for the investment period.

关键词： Vehicle-to-grid Energy consumption Profitability Tariffs Production Microgrids Market research

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Generation of Pulsed Power for Radar Application 1

Generation of Pulsed Power for Radar Application

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1st IEEE International Conference on Power Electronics and Energy, ICPEE 2021

作者： Paul, Akash Kumar Giridhar, A.V. Rai, Krishna Kumar Kirubakaran, A. National Institute of Technology Warangal Dept. of Electrical Engineering Warangal India Center for High Energy Systems and Sciences Defence Rd Organization Hyderabad India

ISBN: (纸本)9781728187730

This paper proposes an efficient method for generation of high power train of pulses which are widely used in many fields. Pulse generators store energy in the form of electric or magnetic field for certain duration and by closing a switch at the load side, complete energy will be discharged to the load in the required form of pulses. The pulse generators are widely used in Radar application to drive magnetron loads with desired magnitude, pulse repetition frequency (PRF) and pulse duration or width. Line type modulator where a Pulse Forming Network (PFN) of type E is used as an energy storage element for generation of pulses. In this work, it is desired to produce rectangular pulses of magnitude 5 kV, PRF of 1.6 kHz and pulse duration of 4 microseconds with minimum rise time required for Radar application to drive load. MATLAB simulation is carried out in order to realize pulses of desired specification and a scaled down hardware setup is developed to verify the system performance. © 2021 IEEE.

关键词： Field programmable gate arrays (FPGA)

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DynaPAT: A Dynamic Pattern-Aware Encoding Technique for Robust MLC PCM-Based Deep Neural Networks

DynaPAT: A Dynamic Pattern-Aware Encoding Technique for Robu...

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IEEE International Conference on computer-Aided Design

作者： Thai-Hoang Nguyen Muhammad Imran Joon-Sung Yang Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan School of Electrical and Electronic Engineering and Dept. of Semiconductor Systems Engineering Yonsei University Seoul South Korea

As the effectiveness of Deep Neural Networks (DNNs) is rising over time, so is the need for highly scalable and efficient hardware architectures to capitalize this effectiveness in many practical applications. Emerging non-volatile Phase Change Memory (PCM) technology has been found to be a promising candidate for future memory systems due to its better scalability, non-volatility and low leakage/dynamic power consumption, compared to conventional charged-based memories. Additionally, with its cell's wide resistance span, PCM also has the Flash-like Multi-Level Cell (MLC) capability, which has enhanced storage density, providing an opportunity for the deployment of data-intensive applications such as DNNs on resource-constrained edge devices. However, the practical deployment of MLC PCM is hampered by certain reliability challenges, among which, the resistance drift is considered to be a critical concern. In a DNN application, the presence of resistance drift in MLC PCM can cause a severe impact to DNN's accuracy if no drift-error-tolerance technique is utilized. This paper proposes DynaPAT, a low-cost and effective pattern-aware encoding technique to enhance the drift-error-tolerance of MLC PCM-based Deep Neural Networks. DynaPAT has been constructed on the insight into DNN's vulnerability against different data pattern switching. Based on this insight, DynaPAT efficiently maps the most-frequent data pattern in DNN's parameters to the least-drift-prone level of the MLC PCM, thus significantly enhancing the robustness of the system against drift errors. Various experiments on different DNN models and configurations demonstrate the effectiveness of DynaPAT. The experimental results indicate that DynaPAT can achieve up to 500× enhancement in the drift-errors-tolerance capability over the baseline MLC PCM based DNN while requiring only a negligible hardware overhead (below 1% storage overhead). Being orthogonal, DynaPAT can be integrated with existing drifttolerance sc

关键词： Phase change materials Resistance Deep learning Microprocessors Neural networks Memory management Switches

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Developing xApps for Rogue Base Station Detection in SDR-Enabled O-RAN

Developing xApps for Rogue Base Station Detection in SDR-Ena...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Jun-Hong Huang Shin-Ming Cheng Rafael Kaliski Cheng-Feng Hung Dept. of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan Dept. of Electrical Engineering National Sun Yat-sen University Kaohsiung Taiwan

In order to support the diverse requirements of 5G communications, a multitude of RAN components are required. To enable multiple vendor support for 5G, each of whom can independently choose components, Open-RAN (O-RAN) defined a set of standards to which the components must adhere. In addition, O-RAN defines the management elements used to manage each component to secure the 5G networks. While the proposed architecture can manage both 4G and 5G environments, including 5G NSA (Non-Standalone), it inherently suffers from the same vulnerabilities found in 4G LTE. Consequently, an attacker can use unprotected signaling and a low-cost Software Defined Radio (SDR) to launch rogue base station (RBS) attacks on the user equipment (UE), even in O-RAN architectures. In this paper, we consider the stability of signals collected from high-quality operational BSs versus cheap RBSs. Using signal stability features, we develop a machine learning (ML) based RBS detector located on the UE. With the aid of an O-RAN xAPP, ML models can be retrained using the data collected from multiple UEs, and the updated model can be delivered to UEs to enable higher detection accuracy. We conduct extensive experiments by implementing an RBS using a USRP B210, enabling O-RAN using E- Release, and data collected from operational BSs. Moreover, the detector is implemented as an Android APP, which realizes the connection to the O-RAN xAPP. The experimental results show that our detector can achieve more than 99% accuracy, precision “recall” and F1 score.

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Achieving Gaussian Vector Broadcast Channel Capacity with Scalar Lattices

Achieving Gaussian Vector Broadcast Channel Capacity with Sc...

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IEEE International Symposium on Information Theory

作者： M. Yusuf Şener Gerhard Kramer Shlomo Shamai Shitz Ronald Böhnke Wen Xu School of Computation Information and Technology Technical University of Munich Munich Germany Munich Research Center Huawei Technologies Duesseldorf GmbH Munich Germany Dept. of Electrical and Computer Engineering Technion—Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

A coding scheme with scalar lattices is applied to K-receiver, Gaussian, vector broadcast channels with K independent messages, one for each receiver. The method decomposes each receiver channel into parallel scalar channels with known interference and applies dirty paper coding with a modulo interval, amplitude shift keying (ASK), and probabilistic shaping to each scalar channel. The achievable rate tuples include all points inside the capacity region by choosing truncated Gaussian shaping, large ASK alphabets, and large modulo intervals.

关键词： Codes Channel capacity Amplitude shift keying Noise Lattices Receivers Interference

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Modified ARQ-based cooperative relaying scheme for a delay tolerant network

Modified ARQ-based cooperative relaying scheme for a delay t...

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2021 IEEE International Conference on electrical, computer, Communications and Mechatronics engineering, ICECCME 2021

作者： Otaru, Musa Adinoyi, Abdulkareem Ajiya, Mohammed Aljlayl, Mohammed Yanikomeroglu, Halim Bayero University Kano Department of Electrical Engineering Nigeria Technology Strategy Architecture Saudi Telecommunications Company Saudi Arabia Carleton University Dept. of Systems and Computer Engineering Ottawa Canada

ISBN: (纸本)9781665412629

We use fixed relays deployed by network operators to reduce re-transmission (thereby reducing network power requirements) in addition to providing excellent end-to-end error performance in a revisit to automatic repeat request-based cooperative relaying. The new relaying scheme facilitates the creation of a connectivity suitable for delay tolerant internet-of-things (IoT)-type services. For IoT devices, link reliability and power efficiency are a major system design consideration. The proposed scheme operates in the following fashion. The source (e.g., a sensor) transmits for a certain time window. During this period, the source and the relays do not require per transmission acknowledgment (ACK) from the destination. At the end of a transmission window, the destination sends a 'group' ACK. If negative, relays are invited to help. Depending on the cooperation strategy, each relay transmits in either one transmission time slot or a few time slots, using a suitably chosen higher-order modulation constellation. If no error occurs, the source continues its transmission. Furthermore, we devise a novel strategy for selecting the best relay for this new way of exploiting the benefits of multiple relays in a network. In the process, we reclaim the bandwidth expansion that comes with multi-relay system but still maintaining E2E bit error rate that is superior to that of a single relay cooperation. Numerical results that reveal the benefits of the new and modified ARQ cooperative relaying scheme are presented. © 2021 IEEE.

关键词： Energy efficiency

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An Implementation of Answer Code Validation Program for Code Writing Problem in Java Programming Learning Assistant System

An Implementation of Answer Code Validation Program for Code...

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Information and Education technology (ICIET), International Conference on

作者： Khaing Hsu Wai Nobuo Funabiki Soe Thandar Aung Khin Thet Mon Htoo Htoo Sandi Kyaw Wen-Chung Kao Dept. of Information and Communication Systems Okayama University Okayama Japan Dept. of Computer and Information Science Tokyo University of Agriculture and Technology Tokyo Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

To assist Java programming learning of novice students, we have developed the web-based Java Programming Learning Assistant System (JPLAS). It provides various exercise problems to cultivate code reading and code writing skills to support studies at various levels. The code writing problem (CWP) asks a student to write a source code to pass the given test code where the correctness is verified by running them on JUnit. Previously, we implemented the answer platform for students to solve CWP assignments with the automatic runs. However, the teacher needs to manually run them one by one to verify a lot of source codes from students. In this paper, we implement the answer code validation program that automatically verifies all the source codes for one test code and reports the number of tests that each code passed with the CSV file. For evaluations, we applied the program to a total of 999 source codes from 12-43 students for a total of 45 test codes that were assigned in the Java programming course in Okayama university, including for final examinations. The application results confirm the validity and effectiveness of the proposal.

关键词： Java Codes Source coding Education Writing Proposals Programming profession

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Clustered Graph Federated Personalized Learning

Clustered Graph Federated Personalized Learning

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Asilomar Conference on Signals, systems & computers

作者： Francois Gauthier Vinay Chakravarthi Gogineni Stefan Werner Yih-Fang Huang Anthony Kuh Dept. of Electronic Systems Norwegian University of Science and Technology Norway Dept. of Electrical Engineering University of Notre Dame Notre Dame IN USA Dept. of Electrical and Computer Engineering University of Hawai'i Hawai'i USA

This paper proposes a graph federated learning approach wherein multiple servers collaborate to enhance personalized learning over clustered clients, essentially performing correlated learning tasks. In contrast to earlier approaches, relying on a cluster-dedicated server topology, the proposed graph federated multitask learning (GFedMt) framework adopts a more general setting wherein clients of the same cluster are distributed across servers. In order to address problems with unbalanced client distributions among servers and clusters as well as data shortage of isolated clients, servers perform intra-cluster and inter-cluster learning collaboratively through local interaction with neighboring servers. Clients use the alternating direction method of multipliers (ADMM) to learn their local models. Numerical simulations demonstrate the ability of the proposed method to ensure fast and accurate convergence when data is scarce.

关键词： Processor scheduling Federated learning Numerical simulation Convex functions Data models Numerical models Topology

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