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4D-printed intelligent reflecting surface with improved beam resolution via both phase modulation and space modulation

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Microsystems & Nanoengineering 2024年第5期10卷 407-415页

作者： Kyounghwan Kim Ratanak Phon Eiyong Park Sungjoon Lim Department of Intelligent Semiconductor Engineering Chung-Ang UniversitySeoul 06974Republic of Korea Department of Electrical and Computer Engineering Stevens Institute of TechnologyHoboken NJ 07030USA School of Electrical and Electronic Engineering Chung-Ang UniversitySeoul 06974Republic of Korea

Recently,intelligent reflecting surfaces(IRSs)have emerged as potential candidates for overcoming the line-of-sight issue in 5 G/6 G wireless *** IRSs can manipulate the direction of reflected beams,enabling efficient beam steering to enhance the performance of wireless *** unit cell(or unit structure)of an IRS commonly consists of electrical elements for phase ***,by employing phase modulation alone,an IRS can steer the reflected electromagnetic waves toward only discrete and specific angles,leaving a wide range of out-of-beam *** this work,an IRS that uses both phase modulation and space modulation is presented to improve the beam resolution and continuously cover out-of-beam areas that phase modulation alone cannot address.A positive-intrinsic-negative diode is mounted on a unit cell for phase modulation,and a 4D-printed reconfigured structure is fabricated to demonstrate space *** beam-steering function is achieved by alternating the states of the diodes in the same columns,while the beam resolution is improved by controlling the gaps between the *** functions are frst theoretically and numerically analyzed and then experimentally verified,demonstrating that additional angles of-46°/+50°,-22°/+14°,and -16°/+12°are achieved with space modulation and -60°/+62°,-30°/+22°,and±16°are achieved by phase modulation *** proposed IRS offers the possibility of functional integration in a variety of indoor applications within the wireless communication field.

关键词： alone beam columns

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A Modified 2:1 Multiplexer-Based Low Power Ternary ALU for IoT Applications

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Journal of engineering Science and Technology Review 2024年第5期17卷 104-109页

作者： Allwin Devaraj, S. Magdalin Mary, D. Kannan, P. Esakki Rajavel, S. Thangaraj, Cynthia Anbuselvi Gurumoorthy, K.B. William, Blanie Scrimshaw Department of Electronics and Communication Engineering Francis Xavier Engineering College Tamilnadu Tirunelveli627003 India Department of Electrical and Electronics Engineering Sri Krishna College of Technology Tamilnadu Coimbatore641042 India Department of Electronics and Communication Engineering Karpagam Academy of Higher Education Tamilnadu Coimbatore641021 India Department of Electronics and Communication Engineering SEA College of Engineering and Technology Karnataka Bengaluru560049 India Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology Tamilnadu Coimbatore641407 India Department of Computer Science and Engineering Rohini College of Engineering and Technology Tamilnadu Kanyakumari629401 India

The ternary logic has a benefit over the binary logic which provides a secured solution to achieve a trade-off between the area and power of the design. However, from the structure of the ternary Aritmetic Logic Unit (ALU), it is clear that its architecture increases the area, propagation delay, and power consumption. To overcome this drawback, a loopback algorithm is proposed to achieve low power and high throughput Internet of Things (IoT) processors. The loopback algorithm reduces the number of processing stages in multipliers and adders which can significantly reduce area and power dissipation. The proposed 2:1 multiplexer-based approach reduces the need for a decoder and results in low power consumption. The proposed design will be implemented in Xilinx ISE 13.0 and simulation will be done in Modelsim. The modified Ternary ALU (TALU) performs finer than the previous TALU method. The number of registers used in this architecture is reduced by up to 25% than the existing system therefore there is a reduction in power dissipation. © (2024), (International Hellenic University - School of Science). All rights reserved.

关键词： Logic design

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A Coupled Inductor-Based SSCB With Reduced Components for DC Microgrid Protection

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IEEE Transactions on Power Electronics 2025年第8期40卷 11428-11441页

作者： Pithanisetty, Prasanth Dsa, Daniel Banavath, Satish Naik Carvalho, Edivan Laercio De Carne, Giovanni Vinnikov, Dmitri Department of Electrical Electronics and Communication Engineering Dharwad580007 India Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn19086 Estonia Karlsruhe Institute of Technology Institute for Technical Physics Karlsruhe76344 Germany

DC microgrids have gained importance for their high efficiency, no need for synchronization, high power quality, and potential to reduce greenhouse gas emissions. Ensuring reliable and fast protection against over current and short-circuit faults is considered to be a challenge even to date. Solid-state circuit breakers (SSCBs) offer a promising solution, providing rapid and arc-less fault clearing. However, SSCBs employing fully controlled devices lead to higher costs and conduction losses. This article discusses a cost effective circuit breaker, using a semi-controlled switch based on a coupled inductor. The proposed SSCB has reduced overall components, a discharged capacitor and also allows the option to trip manually for maintenance. A detailed analysis and design methodology for component selection is presented in the later sections. The SSCB is experimentally validated by developing a laboratory prototype for a voltage rating of 400 V and at a nominal current of 15 and 20 A with a short circuit fault current of 60 A. © 1986-2012 IEEE.

关键词： DC distribution systems

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Hot Deformation Characteristics and Tool Wear Morphology of GH4169 Super Alloy: A Frugal Usage of Cryogenic Cooling During Turning Process

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Journal of The Institution of Engineers (India): Series D 2025年 1-13页

作者： Vinod, B. Sudhakiran, P. Reddy, S. Sunil Kumar Pasupulati, Baburao Department of Mechanical Engineering Siddharth Institute of Engineering & Technology Puttur India Department of Electronics and Communication Engineering New Horizon College of Engineering Bangalore India Department of Electrical and Electronics Engineering Veltech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Avadi India

Demand for nickel-based superalloys has increased significantly in the automotive industry because of their great potential to reduce the weight of components and improve efficiency. The present study aims to improve the tribological performance and tool lifespan of the GH4169 alloy through machining, focusing specifically on the potential benefits of using cryogenic cooling. It has better wear and mechanical properties to make this alloy more competitive and viable. Hence, the experiments are conducted under liquid nitrogen (LN2), carbon dioxide (CO2), and minimum quantity lubrication (MQL) conditions. The critical tool wear factors have been investigated. The test results proved that cryogenic cooling with the inclusion of MQL helps improve tool life with better tribological characteristics. Furthermore, a hot deformation test was also performed to identify the material’s behavior. The results indicate that flow curves led to smooth regions controlled at low-temperature and high-strain rates. The formation of DRX structures in the processing map is crucial to improving the mechanical properties of these cast components. The Brinell hardness of nickel-based alloys improved after using cooling conditions. Applying the minimum quantity of lubrication cooling conditions exhibits a high hardness of 498 BHN, a 41% increase compared to other conditions. © The Institution of Engineers (India) 2025.

关键词： Strain rate

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Mitigation of Uncertainty in an Islanded Microgrid Using Robust Voltage Controller

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Distributed Generation and Alternative Energy Journal 2023年第2期38卷 611-640页

作者： Singh, Ishika Prasad, Sheetla Pal, Vipin Chandra Department of Electrical Electronics and Communication Engineering Galgotias University Greater Noida India Department of Electrical Engineering National Institute of Technology Silchar India

In microgrid, a severe problem occurs in terms of voltage oscillations due to mismatch between synchronizing and damping torque. In this study, a centralized nonlinear sliding mode voltage controller proposes to minimize the rotor and DC voltage oscillations issue in an islanded microgrid. The linear matrix inequality (LMI) technique has been applied for bounding the state error. Lyapunov criteria is utilized for assurance of asymptotic convergence and LMI optimization approach is used for obtaining the controller parameters. The proposed controller is able to tackle the parametric uncertainties of diesel generator, oscillations of rotor and voltage fluctuation as well as the closed-loop system responses also improves both transient responses and steady state responses simultaneously. The simulation results authenticate that the proposed controller confirms speedy recovery of nominal frequency without any oscillations and reduced the limitation of chattering notably without any loss in control accuracy. The performance and robustness of the proposed controller is also compared with conventional controllers. © 2023 River Publishers.

关键词： Controllers

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Falcon Optimization Algorithm-Based Energy Efficient communication Protocol for Cluster-Based Vehicular Networks

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computers, Materials & Continua 2024年第3期78卷 4243-4262页

作者： Youseef Alotaibi B.Rajasekar R.Jayalakshmi Surendran Rajendran Department of Software Engineering College of ComputingUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Electronics and Communication Engineering Sathyabama Institute of Science and TechnologyChennai600119India Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennai602105India

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)*** networks give a safe and more effective driving experience by presenting time-sensitive and location-aware *** communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with ***,the scheme of an effectual routing protocol for reliable and stable communications is *** research demonstrates that clustering is an intelligent method for effectual routing in a mobile ***,this article presents a Falcon Optimization Algorithm-based Energy Efficient communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in *** FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the *** accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust *** the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR *** experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

关键词： Vehicular networks communication protocol clustering falcon optimization algorithm routing

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A 28.8-mW Accelerator IC for Dark Channel Prior-Based Blind Image Deblurring

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IEEE Journal of Solid-State Circuits 2024年第6期59卷 1899-1911页

作者： Chen, Po-Shao Chen, Yen-Lung Lee, Yu-Chi Fu, Zih-Sing Yang, Chia-Hsiang Graduate Institute of Electronics Engineering National Taiwan University Taipei10617 Taiwan University of Michigan Department of Electrical Engineering and Computer Science Ann ArborMI48109 United States Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA02139 United States National Taiwan University Department of Electrical Engineering Graduate Institute of Electronics Engineering Taipei10617 Taiwan

This work presents an accelerator that performs blind deblurring based on the dark channel prior. The alternating minimization algorithm is leveraged for latent image and blur kernel estimation. A 2-D Laplace equation solver is embedded to reduce the latency by 56% for boundary wrapping. For latent image estimation, gradient data locality is employed to reduce the latency by 57%. A sorting engine is designed to reduce the latency in data access by 96% for calculating the dark channel. A pipelined mixed-radix 1-D fast Fourier transform (FFT) engine is used for efficient latent image estimation and blur kernel estimation. By employing image size approximation, 85% of additions and 97% of multiplications for FFT can further be saved. In the blur kernel estimator, a 2-D convolution engine with a parallel architecture is implemented, reducing the latency by 79%. The accelerator supports blur kernels of 25times 25 and 49times 49 pixels for blurred images of 129times 129 and 257times 257 pixels, respectively. Fabricated in 40-nm CMOS, the accelerator's core area is 3.98 mm2. The chip dissipates 28.8 mW at 65 MHz from a 0.65-V supply. It can estimate a blur kernel of 25times 25 pixels for an image patch with 129times 129 pixels for deblurring a full-HD image in 1.7 s, achieving a 2562times shorter latency than a high-end CPU. Compared with the state-of-the-art design, the chip achieves a four times higher normalized area efficiency and a 7.5times higher normalized energy efficiency. © 1966-2012 IEEE.

关键词： CMOS integrated circuits

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Stability Investigation and Improvement for DC Cascade Systems with Simplified Impedance-based Stability Criterion

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1044-1052页

作者： Junbin Fang Zhikang Shuai Yang Li Zhibing Wang Xiangyang Wu Xia Shen Z.John Shen College of Electrical and Information Engineering Hunan UniversityChangsha 410082China Renewable Energy Department of China Electric Power Research Institute Beijing 100192China Department of Electrical and Computer Engineering Illinois Institute of TechnologyChicagoIL 60616USA IEEE

In DC distributed power systems(DPSs),the complex impedance interactions possibly lead to DC bus voltage oscillation or *** previous research,the stability analysis of DPSs is implemented based on mathematical analysis in control *** specific mechanisms of the instability of the cascade system have not been intuitively *** this paper,the stability analysis of DPSs based on the traditional Nyquist criterion is simplified to the resonance analysis of the seriesconnected port impedance(Z=R+jX)of source and load *** reveals that the essential reason for impedance instability of a DC cascade system is that the negative damping characteristic(R<0)of the port the overall impedance amplifies the internal resonance source at reactance zero-crossing *** simplified stability criterion for DC cascade systems can be concluded as:in the negative damping frequency ranges(R<0),there exists no zero-crossing point of the reactance component(i.e.,X=0).According to the proposed stability criterion,the oscillation modes of cascade systems are classified.A typical one is the internal impedance instability excited by the negative damping,and the other one is that the external disturbance amplified by negativity in a low stability ***,the impedance reshaping method for stability improvement of the system can be further *** validity of the simplified criterion is verified theoretically and experimentally by a positive damping reshaping method.

关键词： DC cascaded system,impedance model impedance reconstruction stability criterion

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Developed a Machine Learning and Deep Learning Model for 5G MIMO Data Based Beam Selection and Intelligent Network Analytics

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SN computer Science 2025年第3期6卷 1-21页

作者： Ashok, P. Suganya, R. Lekha, P. Pandian, Poornima Subashini, M. Nithya, M. Department of Computer Science and Engineering Sri Sai Ram Institute of Technology Tamilnadu India Department of Computer and Communication Engineering Sri Sai Ram Institute of Technology Tamilnadu India Department of Electronics and Communication Engineering Sri Sairam Engineering College Tamilnadu India Department of Computer Science and Engineering Sri Sairam Engineering College Tamilnadu India

Introduces an innovative application of 5G MIMO data in singular value decomposition (SVD) focusing on deep learning beam-selection and intelligent network analytics. This research explores the potential of leveraging 5G MIMO data to enhance network performance and efficiency through advanced ML techniques. Deep learning algorithms are employed for beam-selection, optimizing the transmission of data in 5G networks to improve throughput and reliability. Intelligent network analytics are applied to extract valuable insights from the vast amount of data generated by 5G MIMO systems, enabling proactive network management and optimization. By harnessing the capabilities of deep learning and intelligent analytics, this research aims to address key challenges in 5G network optimization and management. The integration of SVD techniques with 5G MIMO data offers a novel approach to enhancing network performance, enabling more efficient utilization of resources and improved quality of service for users. The insights gained from intelligent network analytics facilitate informed decision-making and proactive maintenance leading to greater reliability and resilience in 5G networks. This research contributes to the advancement of 5G technology by leveraging ML to unlock the full potential of MIMO data for optimizing network performance and enabling intelligent network management. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： 5G Beam-selection Deep learning Intelligent management MIMO Network analytics Network performance Optimization Proactive maintenance Singular value decomposition

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A hybrid feature weighting and selection-based strategy to classify the high-dimensional and imbalanced medical data

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Neural Computing and Applications 2024年第20期36卷 12299-12316页

作者： Singh, Harpreet Kaur, Manpreet Singh, Birmohan Department of Computer Science and Engineering Sant Longowal Institute of Engineering and Technology Longowal Sangrur148106 India Department of Electrical and Instrumentation Engineering Sant Longowal Institute of Engineering and Technology Longowal Sangrur148106 India

Machine learning algorithms generally assume that the data are balanced in nature. However, medical datasets suffer from the curse of dimensionality and class imbalance problems. The medical datasets are obtained from the patient information which creates an imbalance in class distribution as the number of normal persons is more than the number of patients and contains a large number of features to represent a sample. It tends to the machine learning algorithms biased toward the majority class which degrades their classification performance for minority class samples and increases the computation overhead. Therefore, oversampling, feature selection and feature weighting-based four strategies are proposed to deal with the problems of class imbalance and high dimensionality. The key idea behind the proposed strategies is to generate a balanced sample space along with the optimal weighted feature space of the most relevant and discriminative features. The Synthetic Minority Oversampling Technique is utilized to generate the synthetic minority class samples and reduce the bias toward the majority class. An Improved Elephant Herding Optimization algorithm is applied to select the optimal features and weights for reducing the computation overhead and improving the interpretation ability of the learning algorithms by providing weights to relevant features. In addition, thirteen methods are developed from the proposed strategies to deal with the problems of high-dimensionality and imbalanced data. The optimized k-Nearest Neighbor (k-NN) learning algorithm is utilized to perform classification. The performance of the proposed methods is evaluated and compared for sixteen high-dimensional imbalanced medical datasets. Further, Freidman’s mean rank test is applied to show the statistical difference between the proposed methods. Experimental and statistical results show that the proposed Feature Weighting followed by the Feature Selection (FW–FS) method performed significantly b

关键词： Feature Selection

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