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Wireless and Optical Technologies (GCWOT), 2020 Global Conference on

作者： Shehnila Zardari Nida Nisar Zainab Fatima Lubna Luxmi Dhirani Department of Software Engineering NED University of Engineering & Technology Karachi Pakistan Department of Electronic and Computer Engineering University of Limerick Limerick Ireland

Internet of Things (IoT) is a system of interconnected devices and networks that provides autonomous functioning capability. Increasing expansion rate of IoT system in diverse set of domains has resulted in inclination of associated risks as well. This research paper presents classification of assets which are part of IoT system, identify platform-independent threats, and consolidate potential solutions to secure the IoT system from threats. Various researchers have conducted studies which are focused on specific industry/domain. Therefore, there is an inevitable necessity to present generalized assessment of IoT system and associated threats, irrespective of the industry or domain. In addition, this research presents prioritization, in terms of criticality, of IoT assets and threats that will enable stakeholders to identify the items that are crucial and items that can be ignored considering the low priority. This would enable researchers and stakeholders of IoT system (such as policy makers, end-users, manufacturers, and security experts etc. to have a deeper understanding of the implications and have an insight on solutions/recommendations in a broad-spectrum. Survey findings showed that DDoS (distributed denial of service), privacy attack, and information modification are the top three threats in terms of criticality ranking. A generalized (industry-independent) set of recommendations have been consolidated based on literature analysis and survey findings in three categories, which are related to policies, organizational measures, and technical measures.

关键词： Wireless communication Industries Privacy Taxonomy Threat assessment Internet of Things Stakeholders

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A Multi-Level Home Energy Management System (HEMS) for DC-Microgrids

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IEEE Transactions on Sustainable Energy 2025年

作者： Lin, Xin Zamora, Ramon Jiang, Yazhou Chen, Gang Srivastava, Anurag K. Sanming University School of Mechanical and Electrical Engineering Sanming365004 China Auckland University of Technology Electrical and Electronic Engineering Department Auckland1142 New Zealand Clarkson University Electrical & Computer Engineering Department PotsdamNY13699 United States West Virginia University Computer Science and Electrical Engineering Department MorgantownWV26506-6695 United States

It is essential for Home Energy Management Systems (HEMSs) to minimize the system operating cost while maintaining the user comfort under forecasting uncertainties of solar and electricity load demand. However, the existing HEMS excessively relies on a single battery system and may not effectively assess user comfort. To this end, a hierarchical HEMS, i.e., system- and local-level, is proposed in this article to coordinate the dispatch of home resources including battery energy storages and supercapacitors (SC). The system-level HEMS consists of long-term (LT) and short-term (ST) optimization based on Model Predictive Control (MPC). The LT optimization optimizes resource dispatch by using forecasted load and solar generation to minimize house operating costs and maximize the user comfort. The ST layer one is proposed to track the optimal power scheduling to minimize the cost error, refine the dispatch of resources and ensure a safe operational level of hybrid energy storage systems including the SC. The SC is employed to compensate the transient power and alleviate the battery degradation effects. The local-level HEMS is used to achieve DC voltage restoration, power sharing, voltage recovery of SC and state of charge (SoC) balance between batteries. The interaction between system- and local-level is also discussed. By using the dataset from NREL and Ameren Illinois Company, the test results show that this methodology can potentially reduce the system operating cost by 4.3500%, 7.7600%, and 37.7253% compared to the other single and multi-layer HEMSs. © 2025 IEEE. All rights reserved.

关键词： Microgrids

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The contribution of innovative semi-transparent photovoltaics for energy autonomy in the field of greenhouse systems

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VDI Berichte 2022年第2406期2022卷 61-68页

作者： Kavga, A. Petrakis, T. Thomopoulos, V. Computer Engineering and Informatics Department University of Patras Patras Greece

Greenhouse systems, which can increase production even in off-season crops without sacrificing quantity or quality, can be a significant benefit for managing the gradual increase in world population. On the other hand, greenhouses' significant energy consumption, whether for heating, cooling, or artificial lighting, cannot be overlooked, accounting for up to 50% of the cost of the product produced. Due to the severity of climate change brought on by the usage of fossil fuels for energy production, and since the agricultural sector is part of a wider political, social, and economic context, it is essential that the energy consumed is produced from environmentally friendly sources, such as solar energy, also known as Renewable Energy Sources – RES. At the same time, the demand for land is constantly increasing, creating both spatial and economic issues. Thus, the installation of semi-transparent photovoltaics on the roof of each construction unit of a greenhouse, replacing the existing cover, leading to double use of the land, is presented as a particularly good solution, for the simultaneous production of both energy and food. In this paper, a Greenhouse Integrated Photovoltaic System (GIPV) is presented, using all the above elements, with the aim of its complete energy autonomy. © 2022, VDI Verlag GMBH. All rights reserved.

关键词： Greenhouses

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Motion Error Estimation and Coherent Integration for High-Speed Target With Airborne Bistatic Radar

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IEEE Transactions on Aerospace and electronic Systems 2024年

作者： Li, Xiaolong Zhang, Zerui Yang, Fan Wang, Mingxing Yeo, Tat Soon Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China National University of Singapore Department of Electrical and Computer Engineering 119077 Singapore

With flexibility in maneuverability and remarkable adaptability, airborne bistatic radar system can obtain excellent detection performance for high-speed target by employing coherent integration. However, range migration (RM) and Doppler frequency migration (DFM) could become serious issues due to the relative motion characteristics of airborne platforms and high-speed target. Meanwhile, various unpredictable factors such as atmospheric turbulence and mechanical issues, etc., resulting in additional motion errors, would have further negative impacts on motion state and flight trajectory of airborne platforms. This phenomenon would serious consequence on coherent integration and target detection. Thus, we make contributions to tackle these limitations and enhance coherent integration and detection performance. First, we establish signal model with high-speed target in three-dimensional (3-D) space for airborne bistatic radar system, along with motion error model which simultaneously includes translational error and rotational error. Next, we articulate range history's mathematical expression and further derive echo signal model. We then propose an improved generalized Radon Fourier transform (IGRFT) method. More specifically, the purpose of IGRFT is achieving joint search for the parameters of the target motion and the parameters of motion error, to ensure high precision parameter estimation and high gain integration. However, the computational complexity surges due to the increasing of search dimensionality. To devise computationally feasible methods for practical applications, we split the high-dimensional maximization process into two disjoint problems by sequentially searching motion parameters and then motion error parameters, and this method is named GRT (generalized Radon transform)-IGRFT. Numerical simulations show that the proposed algorithms can correctly estimate parameters and achieve signal integration and target detection. Finally, we present performanc

关键词： Flight paths

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Decentralized Federated Deep Reinforcement Learning Framework for Energy-Efficient Base Station Switching Control

Decentralized Federated Deep Reinforcement Learning Framewor...

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International Symposium on Telecommunications, IST

作者： Narges Movahedkor Reza Shahbazian Department of Computer Engineering Amirkabir University of Technology (Tehran Polytechnique) Tehran Iran Department of Informatics Modeling Electronics and System Engineering (DIMES) University of Calabria Rende Italy

ISBN: (数字)9798350356250

ISBN: (纸本)9798350356267

G cellular networks have achieved significant improvements in capacity and performance, while they have incurred a substantial increase in energy consumption at the base station (BS) level. To address this escalating energy consumption in dense 5G networks, this paper proposes a decentralized federated learning (DFL)-enhanced Deep Reinforcement Learning (DRL) framework for intelligent BS switching. Our approach leverages the distributed nature of 5G networks to collaboratively learn optimal BS on/off policies without centralized control. By combining DFL with DRL, we enable efficient knowledge sharing among BSs while maintaining privacy and reducing communication overhead. The cost function designed in this paper aims to balance energy savings as well as Quality of Service ($\mathbf{Q o S}$) requirements. Moreover, to enhance exploration and accelerate convergence, we incorporate an exploration network into the DRL agent and adopt a novel approach of model training. Performed simulations demonstrate the effectiveness of our proposed framework in achieving significant energy reduction of over 23% and total cost of 19%, while maintaining satisfactory QoS performance compared to the existing methods.

关键词： Training Base stations Energy consumption Privacy 5G mobile communication Federated learning Switches Quality of service Deep reinforcement learning Telecommunications

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Dual-Path Spectrogram Refinement Network for Robust Speaker Verification

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Journal of Shanghai Jiaotong University (Science) 2025年 1-9页

作者： Wang, Zonghui Fang, Zhihua He, Liang School of Computer Science and Technology Xinjiang University Urumqi830017 China School of Intelligence Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China Department of Electronic Engineering Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

The accuracy and reliability of automatic speaker verification (ASV) face significant challenges in noisy environments. In recent years, joint training of speech enhancement front-end and ASV back-end has been widely applied to improve the robustness of ASV systems. Traditional joint training directly uses the enhanced speech features as the input of the back-end. However, the diversity of noise types and noise intensities will excessively suppress the enhanced features, resulting in speech distortion or residual noise. To alleviate this problem, we propose a dual-path spectrogram refinement network that enables the enhanced features to learn supplementary information from the separated noise features. In addition, we incorporate coordinate attention into the overall joint architecture to capture more comprehensive frequency and temporal information of the speaker from different spatial positions. We conduct extensive experiments on the VoxCeleb1 test set, the out-of-domain noise test set, and the VOiCES corpus. The experimental results demonstrate that our proposed method significantly improves the accuracy and robustness of speaker verification systems in both clean and noisy environments. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Spectrographs

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Low-Power Collision Avoidance Memristive Circuit for Swarms of Miniature Robots

Low-Power Collision Avoidance Memristive Circuit for Swarms ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Ioannis K. Chatzipaschalis Theodoros Panagiotis Chatzinikolaou Emmanouil Stavroulakis Evangelos Tsipas Iosif-Angelos Fyrigos Antonio Rubio Georgios Ch. Sirakoulis Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Electronic Engineering Universitat Politécnica de Catalunya Barcelona Spain

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

A swarm of miniature robots comprises mini-robots collaborating to achieve common goals, inspired by the collective behavior of insects. This concept mimics decentralized cooperation, enabling complex task accomplishment across various fields such as healthcare, exploration, and rescue missions. Mini-robots operate in confined spaces and time frames with minimal energy, requiring efficient path planning to prevent collisions within their group and surroundings. Integrating ultra-low-power electronics in these robots is essential. Memristors, renowned for their low power consumption, simplicity, and high integration density, hold significant promise. This paper proposes an integrated collision avoidance memristive circuit with neuromorphic behavior for miniature robots. This circuit not only enhances swarm efficiency but also lays the groundwork for fully analog mini-robots.

关键词： Power demand Neuromorphics Voltage-controlled oscillators MIMICs Memristors Medical services Path planning

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Performance Improvements of Vehicular PKI Protocol for the Security of V2X Communications 46

Performance Improvements of Vehicular PKI Protocol for the S...

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46th International Conference on Telecommunications and Signal Processing, TSP 2023

作者： Farran, Hassan Khoury, David Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services BudapestH-1111 Hungary American University of Science and Technology Department of Computer Science and Information and Communication Technology Beirut Lebanon

ISBN: (纸本)9798350303964

Vehicle-to-Everything (V2X) technology allows vehicles to communicate with numerous transportation system components. To provide safe communication between vehicles and other entities, V2X depends on Public Key Infrastructure (PKI). However, the present PKI employed in V2X has certain drawbacks, including scalability and high computational cost. This article offers an enhancement to the current PKI in V2X that tackles these constraints by managing and distributing keys using blockchain technology. The suggested Public Key Infrastructure enhancement is intended to be secure, efficient, and scalable, providing a more solid and trustworthy foundation for V2Xcommunication. The article explains the suggested PKI enhancement and examines its advantages and disadvantages. Overall, the suggested Public Key Infrastructure enhancement has the potential to increase the security and dependability of Vehicle-to-Everything communication, allowing for a secure and more effective transportation system. © 2023 IEEE.

关键词： Vehicle to Everything

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Soft Magnetic Properties of Amorphous Ring Cores Prepared Via Spark Plasm Sintering Using Fe-Based Amorphous Powders (Fe, Co)68.7(C, Si, B, P)24.5(Mo,Al)6.8

SSRN

引用

SSRN 2024年

作者： Yi, Seonghoon Lee, Jae-Won Kim, Jin-Ah Sohn, In-Joon Yun, Kyyoul Department of Materials Science and Engineering Kyungpook National University Daegu Korea Republic of Department of Electrical Electronic and Computer Engineering Gifu University Gifu Japan

In this study, an Fe-based amorphous alloy (Fe, Co)68.7(C, Si, B, P)24.5(Mo,Al)6.8 with a large supercooled liquid region was developed for fabricating soft magnetic composites utilized in applications involving high-frequency conditions. The alloy was prepared as amorphous ribbons (~25 μm thick) and amorphous rods (Ф3 mm), which were crushed and sieved to form powders with different shapes and particles smaller than 53 μm: amorphous flake powders made from crushed ribbons and amorphous irregular powders made from crushed rods. Additionally, the amorphous flake powder was coated with an amorphous SiO2 layer. Both powders were consolidated via spark plasma sintering into dense ring cores with a relative density exceeding 90%;this high density is attributed to the Newtonian flow within the temperature range of the amorphous powder’s supercooled liquid region. The ring cores remained amorphous even after spark plasma sintering. Excellent soft magnetic properties originating from the amorphous nature and high density of the ring cores were confirmed based on measurements using a vibrating sample magnetometer, a direct current B-H loop tracer, and an alternating current B-H analyzer. Additionally, due to electrical isolation between the powder particles, the eddy current loss of the amorphous ring cores made from the SiO2-coated amorphous flake powder was significantly reduced to 4.86 W/kg (at Bm = 100 mT, 100 kHz). The mechanical hardness of the amorphous ring cores (>690 Hv 0.5) was also observed to be considerably higher than that of commercially available ring cores. These findings verify that the ring cores prepared in this study can be reliable for practical applications involving harsh conditions. © 2024, The Authors. All rights reserved.

关键词： Spark plasma sintering

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Sparse Gaussian Gradient Code

Sparse Gaussian Gradient Code

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IEEE International Symposium on Information Theory

作者： Yuxin Jiang Wenqin Zhang Yuan Luo Lele Wang Department of Electrical and Computer Engineering University of British Columbia Canada Department of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

Gradient coding is a distributed computing technique aiming to provide robustness against slow or non-responsive computing nodes, known as stragglers, while balancing the computational load for responsive computing nodes. Among existing gradient codes, a construction based on combinatorial designs, called BIBD gradient code, achieves the best trade-off between robustness and computational load in the worst-case adversarial straggler setting. However, the range of system parameters for which BIBD gradient codes exist is limited. In this paper, we overcome this limitation and propose a new probabilistic gradient code, termed Sparse Gaussian (SG) gradient code. The encoding matrix of the proposed SG gradient code is generated from a carefully chosen correlated multivariate Gaussian distribution, masked by Bernoulli random variables to reduce computational load. With high probability, the proposed gradient code achieves a similar worst-case error performance compared to the BIBD gradient code (when such a code of the same parameters exists) and outperforms several other existing gradient codes, including Fractional Repetition gradient codes and Bernoulli gradient codes. Moreover, it further extends the range of system parameters over existing BIBD and soft BIBD gradient codes, making it a promising solution for distributed computing tasks.

关键词： Codes Gaussian distribution Probabilistic logic Robustness Encoding Random variables Sparse matrices

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