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Wide bandgap tunnel layer at Sb2Se3/CdS heterojunction solar cells for lowering interface recombination

Optical and Quantum electronics 2024年第10期56卷 1-15页

作者： Niranjana, S. Kumar, Atul Kumar, S. Hari Ramkumar, G. Department of AI & amp DS Rajalakshmi Institute of Technology Chennai India Department of Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Greenfields Vaddeswaram Andhra Pradesh Guntur522502 India Department of Electronics and Communication Engineering Kongunadu College of Engineering and Technology Trichy India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences SIMATS Saveetha University Tamil Nadu Chennai India

Significantly high voltage deficit and high diode ideality factor in Sb2Se3 solar cells due to space-charge region recombination, conduction band offset, and interface defects at the Sb2Se3/CdS heterojunction prompting elevated interfacial recombination. We proposed and theoretically analyzed an ultrathin tunnel layer to address the interfacial issues. An investigation is conducted into the function of the tunnel layer (ultrathin, wide band gap insulating layer) in mitigating the interface trap states and reducing interface recombination. The tunnel layer at the Sb2Se3/CdS junction has demonstrated a lower recombination current. The performance of devices demonstrated a sustained level of stability with an increase in defects when equipped with a tunnel layer, contrasting the continuous performance degradation observed in devices without a tunnel layer. The device incorporating a tunnel layer achieved an efficiency (η) of 13.9%, VOC of 0.74 V, JSC of 32.7 mA/cm2, and FF values, of 57.2%, respectively. Conversely, the device lacking a tunnel layer at the interface exhibited efficiency parameters of 9.2%, with VOC at 0.4 V, JSC at 32.7 mA/cm2, and a fill factor of 70.5%. The results pertaining to the optimized device with interface passivation through a tunnel layer are anticipated to serve as a catalyst for experimentation within the field. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Selenium compounds

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Disease Diagnosis and Sustainable Prevention in Arecanut Farming 3

Disease Diagnosis and Sustainable Prevention in Arecanut Far...

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3rd International Conference on electronics and Renewable Systems, ICEARS 2025

作者： Siddalingadevaru, Sneha Chikkanayakanahalli Ravindra, Poojitha Devarahalli Gangadhar, Vanitha Srinivas, Srija Basavapatna Singh, Vivek Dwivedi, Ajay Kumar Nagarjuna College of Engineering and Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798331509675

One of India's main crops is arecanut. It is grown more in India and other subtropical climates due to its higher market value. Numerous diseases that affect this plant might result in significant losses for farmers. These illnesses are brought on by abrupt changes in temperature and other meteorological factors;early disease identification is crucial. In order to minimize losses for farmers, this work focuses on early and precise disease diagnosis. A Convolutional Neural Network is a Deep Learning technique that uses an image as input, gives different features in the image learnable weights and biases, and then uses the results to determine which features are different. This method improves process efficiency and drastically lowers the amount of manual labor needed for illness diagnosis. To train and assess the CNN with Extension model, a dataset including several images of both healthy and diseased areca nut leaves is created. It was found that the recommended approach to areca nut illness diagnosis was accurate and effective. This study supports further initiatives to use technology in agriculture to increase crop productivity and health. According to this study, the suggested approach is the most reliable for identifying illnesses in areca nut leaves. In addition to providing suitable treatments for any diseases it identified, the system was able to differentiate between healthy and sick leaves. These results highlight the potential use of deep learning techniques and convolutional neural networks in agriculture, specifically in the control of plant diseases. One of the diseases of areca nuts that the suggested system can identify and cure is yellow leaf spot. The experimental results demonstrate different levels of disease identification accuracy depending on the stage of the disease and the quality of the input image. The system's overall accuracy is estimated to be 98.9%. © 2025 IEEE.

关键词： Convolutional neural networks

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Area Efficient R adix-2kR econfigurable SF F Pipeline FFT Using Constant Multiplier 6

Area Efficient R adix-2kR econfigurable SF F Pipeline FFT Us...

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6th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2024

作者： Chen, Xuanzhang Zhou, Ying Wang, Wei Zou, Xiaohai School of Electronics and Communication Engineering Guangdong China

ISBN: (纸本)9798350316520

This paper presents a serial pipeline FFT circuit that employs a processing unit with a single-path FPGA-optimized feedforward (SFF) structure and a constant multiplier rotator for the R-2k FFT algorithm. It further achieves the length-reconfigurable feature of the FFT circuit through the use of multiplexers and rotator control. Addressing the issue of resource consumption in the processing units of FFT circuits, this study introduces SFF processing units into the previously established single-path delay feedback (SDF) pipeline structure. This approach provides an effective method of reducing the number of complex adders by opting for a higher consumption of short shift registers. By exchanging resources between short shift registers and adders, an overall optimization is achieved, leading to a reduction in the resource consumption of the circuit's processing units. Regarding the consumption issue of Rotators in FFT circuits, this paper introduces a binary tree-based FFT decomposition method to obtain an optimal distribution of Rotators. By converting some Rotators into a form that can be implemented through Constant Multipliers, the multiplication resource consumption of the structure is reduced. Finally, through theoretical analysis and comparative experiments on FPGA, the resource consumption advantages of the proposed structure are demonstrated. © 2024 IEEE.

关键词： Fast Fourier transforms

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A Hybrid Machine Learning Approach for Top-N Bike Recommendations

A Hybrid Machine Learning Approach for Top-N Bike Recommenda...

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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Kumar, V. Vinoth Raj, T. Selvin Retna Raj, J. Relin Francis Sornavalli, M. Krishnan, R. Santhana Soundiraraj, N. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Avadi Chennai India Dmi College of Engineering Department of Electronics and Communication Engineering Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India Velammal College of Engineering and Technology Department of Mathematics Madurai India Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Psna College of Engineering and Technology Department of Electrical and Electronics Engineering Dindigul India

ISBN: (纸本)9798331509828

This research introduces a bike recommendation system aimed at providing personalized suggestions by integrating diverse data sources. The system leverages information from social media, user reviews, and product specifications to generate a comprehensive dataset. Social media interactions, such as likes, shares, and comments, offer valuable insights into the popularity and user engagement of various bike models. E-commerce platforms contribute detailed information regarding bike features, including price, brand, type, and user ratings, enhancing the dataset's depth. The data undergoes preprocessing to ensure consistency and relevance, which allows for effective feature extraction and the handling of missing values. This step is crucial in ensuring the quality of the dataset, which is then used to train the recommendation models. The system combines multiple recommendation techniques to tailor suggestions based on individual user preferences and behavior. By integrating content-based filtering and collaborative filtering, the model generates highly relevant recommendations suited to each user's specific needs. The models are evaluated using key performance metrics, such as accuracy, precision, recall, and F1 score, to ensure the most effective algorithms are selected for the task. This evaluation process guarantees that the system delivers high-quality recommendations. Once trained, the recommendation models are deployed via an efficient API, enabling real-time, personalized bike suggestions to users. The system's web interface allows users to input their preferences, such as budget, bike type, and other specifications, further enhancing the personalization of recommendations. Overall, this research demonstrates the value of integrating multiple data sources to create an advanced, personalized bike recommendation system capable of meeting diverse user needs. © 2025 IEEE.

关键词： Bike recommendation system data integration e-commerce data personalized suggestions social media data user reviews

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An integrated PHM framework for radar systems through system structural decomposition

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Journal of Systems engineering and electronics 2025年第1期36卷 95-107页

作者： WANG Hong KULEVOME Delanyo Kwame Bensah ZHAO Zi’an School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Implementing an efficient real-time prognostics and health management (PHM) framework improves safety and reduces maintenance costs in complex engineering ***, research on PHM framework development for radar systems is limited. Furthermore, typical PHM approaches are centralized, do not scale well, and are challenging to *** paper proposes an integrated PHM framework for radar systems based on system structural decomposition to enhance reliability and support maintenance actions. The complexity challenge associated with implementing PHM at the system level is addressed by dividing the radar system into subsystems. Subsequently, optimal measurement point selection and sensor placement algorithms are formulated for effective data acquisition. Local modules are developed for each subsystem health assessment, fault diagnosis, and fault prediction without a centralized controller. Maintenance decisions are based on each local module’s fault diagnosis and prediction results. To further improve the effectiveness of the prognostics stage, the feasibility of integrating deep learning (DL) models is also *** experiments with different degradation patterns are performed to evaluate the effectiveness of the framework’s DLbased prognostics model. The proposed framework facilitates transitioning from traditional reactive maintenance practices to a predictive maintenance approach, thereby reducing downtime and improving the overall availability of radar systems.

关键词： deep learning prognostics and health management(PHM) radar systems remaining useful life(RUL)

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Guaranteeing Wireless communication Reliability via an Extended Hybrid Carrier System

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China communications 2023年第7期20卷 192-202页

作者： Ge Song Xiaojie Fang Xuejun Sha School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China Engineering Research Center for Dedicated Communication System Ministry of EducationHarbin 150080China

In this paper,we propose an extended hybrid carrier system based on the weighted fractional Fourier transform to ensure the reliability of wireless *** proposed scheme improves the dispersion and compensation capabilities of the hybrid carrier system for channel fading through the design of the signal power distribution,which has greatly reduced the probability of high-power distortion of the signal and improved the bit error rate performance as a *** analysis has shown the superiority of the extended hybrid carrier *** a lower cost of computational complexity increment,the proposed scheme obtains a performance improvement without occupying additional time-frequency physical *** with the existing hybrid carrier scheme,numerical simulation results have shown that the proposed extended hybrid carrier scheme has better anti-fading performance under the doubly-selective channel and improves the reliability of the wireless communication system effectively.

关键词： extended hybrid carrier weighted frac-tional Fourier transform bit error rate doubly-selective channel

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Adaptive Dwell Scheduling Based on Dual-Side Time Pointers for Simultaneous Multi-Beam Radar

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1190-1200页

作者： Siyu Heng Ting Cheng Jiaming Song Zishu He Luqing Liu Yuanqing Wang School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Adaptive dwell scheduling is essential to achieve full performance for a simultaneous multi-beam radar *** dwell scheduling for such a radar system considering desired execution time criterion is studied in this *** primary objective of this model is to achieve maximum scheduling gain and minimum scheduling cost while adhering to not only time,aperture,and frequency constraints,but also electromagnetic compatibility(EMC)*** dwell scheduling algorithm is proposed to solve the above optimization problem,where several separation points are set on the timeline,so that each separator divides the scheduling interval into two *** the two sides,the dual-side time pointers are introduced,which move from the separator to both ends of the scheduling *** dwell tasks are analyzed in sequence at each analysis point based on their two-level synthetical *** tasks are then executed simultaneously by sharing the whole aperture under various constraints to accomplish multiple tasks *** above process is respectively conducted at each separator,and the final scheduling result is the one with the minimal cost among *** results prove that the proposed algorithm can achieve real-time dwell scheduling and outperform the existing algorithms in terms of scheduling performance.

关键词： multifunctional radar resource management scheduling algorithms simultaneous multi-beam

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Multi Slot Wearable Patch Antenna for Wireless Applications

Multi Slot Wearable Patch Antenna for Wireless Applications

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2024 IEEE Wireless Antenna and Microwave Symposium, WAMS 2024

作者： Srinivas, M.S.S.S. Gupta, Akash Kumar Babu, Bssv Ramesh Swathi, A.V.S. Chowdary, P.S.R. Ramkrishna, T.V. Raghu Engineering College Department of Electronics and Communication Engineering Visakapatnam India Bharathi Institute of Engineering and Technology Department of Electronics Communication Engineering Hyderabad India

ISBN: (纸本)9798350358926

This paper presents a Wearable Rectangular Patch Antenna (WRAP) for 6.1GHz wireless communications applications. The cotton is employed as substrate to be easily integrated with wearable clothes like baggage, dress, belt hand strips etc. The antenna is Compact in size with a dimensions of 32mm × 42mm slotted rectangular geometry. The designed antenna has an operating frequency of 6.1GHz. The antenna has gain of 6.7dBi and 0.3GHz bandwidth with good radiation pattern. The designed antenna has medical, IoT and 5G applications. © 2024 IEEE.

关键词： Cotton

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EMG-based prosthetic arm 1st

EMG-based prosthetic arm

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1st International Conference on Applications of AI in 5G and IOT, ICAAI5GI 2024

作者： Kumar, Nishit Ranjan, Ravi Singh, Sachin Pal, Purnima Department of Electronics & Communication Engineering Noida Institute of Engineering and Technology Noida India

ISBN: (纸本)9781032874036

Advancements in electromyography (EMG) technology have open the wayfor the development of advanced prosthetic arms aimed at providing enhanced functionality and more natural control for individuals with upper limb amputations. This paper provides an overview of an EMG-based prosthetic arm system designed to improve the interaction between users and their prosthetic limbs. The proposed system relies on surface EMG signals produced from muscles in the user’s remaining limb. These signals are captured by a set of electrodes were placed on the skin surface and processed using machine learning algorithms to interpret the user’s intended movements. Through analysis of EMG signal patterns and amplitudes, the system can accurately identify desired actions such as grasping, releasing, and manipulating objects. Incorporating state of art actuation mechanisms and sensory feedback systems, the EMG-based prosthetic arm aims to deliver a more experienced and knowledgeable user. By employing advanced motor control algorithms, the prosthetic armcan replicate human limb movements and exert appropriate forces." Moreover, sensoryfeedback components such as pressure sensors and tactile interfaces allow users to perceive forces and textures during object manipulation, thereby enhancing dexterity and overall functionality. Extensive user trials involving individuals with upper limb amputations have been conducted to evaluate the effectiveness of the EMG-based prosthetic arm system. The results demonstrate notable enhancements in users’ ability to control the prosthetic arm, carry out daily tasks, and experience a sense of embodiment. © 2025 the Author(s).

关键词： Sensory feedback

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AskMe - A Customer Service Chatbot 3

AskMe - A Customer Service Chatbot

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3rd International Conference on electronics and Renewable Systems, ICEARS 2025

作者： Kashif, M.D. Dsouza, Bryan James Nagesh, K.N. Nagarjuna College of Engineering and Technology Department of Electronics and Communication Engineering Bangalore India

ISBN: (纸本)9798331509675

This paper introduces a chatbot system specifically designed to assist students transitioning into higher education by providing them with comprehensive and instant access to departmental information. The primary objective is to support students, faculties, and visitors by addressing their queries and concerns about the department. Utilizing advanced Natural Language Processing (NLP) techniques, the chatbot interprets user intents and delivers accurate responses. Developed using BotPress and seamlessly integrated into a WordPress-based platform via the "Header and Footer Scripts"plugin, the system ensures round-the-clock accessibility without human dependency. The chatbot provides insights into faculty, facilities, and academic resources, fostering a more informed and confident onboarding experience for new students. Performance evaluation demonstrates a high degree of accuracy of generating the answers. This work emphasizes the role of AI-driven solutions in enhancing student engagement and improving the efficiency of information dissemination. © 2025 IEEE.

关键词： AI Botpress Chatbot Natural Language Processing (NLP)

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