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The Development and Evaluation of Hybrid Solar Cells Based on Perovskites and CIGS with Different ETL for Increased Photovoltaic Efficiency Using SCAPS-1D

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Langmuir 2025年 2025 May 14页

作者： Monnaf, Md. Abdul Ghosh, Avijit Nabil, Saeed Hasan Islam, Md Baharul Rashid, Tamanna Al Fathah, Abdullah Alam, Khorshed Alturaifi, Huriyyah A. Awwad, Nasser S. Department of Electrical and Electronic Engineering Begum Rokeya University Rangpur5400 Bangladesh Department of Electrical and Computer Engineering Lamar University BeaumontTX77710 United States Department of Chemistry and Biochemistry Lamar University BeaumontTX77710 United States Department of Industrial and Systems Engineering Lamar University BeaumontTX77710 United States Department of Chemistry Faculty of Science King Khalid University P.O. Box 9004 Abha61413 Saudi Arabia

The SCAPS-1D method has been utilized to simulate a solar panel with two absorber layers computationally. Implementing the hole transporter in the current work is minimized by employing two absorber layers. Structure of lead-based perovskites Simulations are conducted using copper indium gallium selenide (CIGS) and strontium arsenide iodide (Sr3AsI3). By combining perovskites’ high absorption coefficient and tunable bandgap with the stability and improved charge transport capabilities of CIGS, these bilayer solar cells can overcome the limitations of each material. Several factors are considered to attain maximum and enhanced efficiency, including absorber thickness, series-shunt resistance, acceptor density, defect densities, J-V & Q-E, and operating temperature. The structure of the optimized device Al/Sr3AsI3/CIGS/SnS2/Ni produces excellent output with an efficiency of 35.91%, a voltage in the open circuit (VOC) of 0.998 V, a fill factor (FF) of 86.60%, and current in a short circuit (JSC) of 41.54 mA/cm2. This study demonstrates the promise of perovskite/CIGS double-layers as a means of achieving stable, scalable, and highly efficient thin-film photovoltaics. Comparing the results with previously published experimental data showed that the device might achieve excellent performance by fine-tuning various absorber layer settings. Therefore, this gadget structure is amenable to experimental modeling for future investigation. The simulation’s findings offer helpful suggestions for developing double-absorber solar panels. This paper examines the latest developments in perovskite/CIGS bilayers, addressing issues with scalability, long-term stability, and material compatibility. The findings show that, with further modification, perovskite/CIGS bilayer cells offer a lot of potential for next-generation solar power applications. © 2025 American Chemical Society.

关键词： Gallium arsenide

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Correction to: A comprehensive performance evaluation of container migration strategies

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Computing 2025年第4期107卷 1-2页

作者： Feitosa, Leonel Barbosa, Vandirleya Sabino, Arthur Lima, Luiz Nelson Fé, Iure Silva, Luis Guilherme Callou, Gustavo Carvalho, Juliana Leão, Erico Nguyen, Tuan Anh Rego, Paulo Silva, Francisco Airton Laboratory of Applied Research to Distributed Systems (PASID) Federal University of Piauí (UFPI) Picos Brazil Department of Computing Federal Rural University of Pernambuco (UFRPE) Recife Brazil Department of Software Engineering Faculty of Information Technology University of Industry and Trade (HUIT) Ho Chi Minh City Vietnam Department of Computer Science Federal University of Ceará (UFC) Fortaleza Brazil

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An anonymous and privacy-preserving lightweight authentication protocol for secure communication in UAV-assisted IoAV networks

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computer Communications 2025年 239卷

作者： Shariq, Mohd Jamil, Norziana Rawat, Gopal Singh Chaudhry, Shehzad Ashraf Masud, Mehedi Cangelosi, Angelo Department of Information Systems and Security College of IT UAE University P.O.Box 15551 Al Ain Abu Dhabi United Arab Emirates Bennett University Greater Noida201310 India Department of Computer Science and Information Technology College of Engineering Abu Dhabi University Abu Dhabi United Arab Emirates Department of Software Engineering Faculty of Engineering and Architecture Nisantasi University Istanbul34398 Turkey Department of Computer Science College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Manchester Centre for Robotics and AI University of Manchester United Kingdom

With the rapid proliferation of the Internet of Things (IoT), autonomous vehicles (AVs), or self-driving cars, rely heavily on real-time data sharing and message exchanges over wireless networks. AVs use sensors, artificial intelligence, machine learning, and advanced algorithms to perform various functions, enabling users to operate without human intervention. Owing to the flexibility and high mobility of drones, they could aid in the operations of AVs. However, the security and privacy are the main concerns;specifically, the threat of physical capture and violation of anonymity are the main hurdles for realization of secure communication among the AVs and drones. To address these challenges, we propose an anonymous and provably Secure Lightweight Authentication Protocol for unmanned-aerial-vehicle-assisted Internet of Autonomous Vehicles (SLAP-IoAV). The proposed protocol uses cryptographic primitives such as exclusive-OR operations, elliptic-curve cryptography, collision-resistant one-way hashing, and concatenation to ensure robust security. An informal security analysis found that SLAP-IoAV is secure against several known attacks, and a performance analysis established that the protocol has less computational and communication overhead than existing competitive protocols. Additionally, Scyther simulation results confirm that no security vulnerabilities are present. Overall, our protocol delivers superior security and performance, making it well-suited to real-world applications in the AV industry. © 2025 Elsevier B.V.

关键词： Authentication Protocol

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MemMIMO: A Simulation Framework for Memristor-Based Massive MIMO Acceleration

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IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2025年

作者： Xu, Jiawei Zheng, Yi Stathis, Dimitrios Wang, Ruijia Shen, Ruisi Zheng, Li-Rong Zou, Zhuo Hemani, Ahmed University of Macau State-Key Laboratory of Analog and Mixed-Signal VLSI Institute of Microelectronics Faculty of Science and Technology ECE Department China Fudan University State Key Laboratory of Integrated Chips and Systems School of Information Science and Technology Shanghai China KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden

Memristor-based crossbar architectures have proven highly effective for matrix vector multiplication (MVM) operations, making them a promising solution for accelerating the MVMs widely used in precoding algorithms for multiple input multiple output (MIMO) wireless communication systems. However, real-world implementation of memristor-based computing systems face challenges due to commonly observed non-idealities in both the devices themselves and the circuits they’re built into. To facilitate a rapid design flow and investigate the impact of non-idealities, an integrated open-source simulation framework MemMIMO is developed. The simulation framework estimates the accuracy and hardware performance of the computing system, offering a variety of flexible design options. MemMIMO integrates a behavioral model of the mix-signal architecture with a digital front-end. There are three major building blocks in MemMIMO: the device fitting block, the mapping block, and the performance estimation block. These blocks work together to map the complex MVMs in precoding algorithms for MIMO systems to crossbar-based architectures that incorporate memristor models characterized by physical device behavior. Using two typical use cases targeting six-generation (6G) massive MIMO communication as case studies, MemMIMO is used to model different memristor devices, explore the impact of non-idealities on system accuracy, and benchmark circuit-level performance metrics including area, speed, and power. © 1982-2012 IEEE.

关键词： System-on-chip

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ON 1-INKDOT ALTERNATING TURING-MACHINES WITH SMALL SPACE

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THEORETICAL computer science 1994年第1期127卷 171-179页

作者： INOUE, K ITO, A TAKANAMI, I Department of Computer Science and Systems Engineering Faculty of Engineering Yamaguchi University Ube 755 Japan

This paper investigates the accepting powers of nondeterministic and alternating 1-inkdot Turing machines using small space. Let NTM (ATM,UTM) denote a nondeterministic Turing machine (alternating Turing machine, alternating Turing machine with only universal states). For each X is-an-element-of {N,A,U}, let STRONG-XSPACE[L(n)] (STRONG-XSPACE*[L(n)]) denote the class of languages accepted by strongly L(n) space-bounded XTMs (1-inkdot XTMs), and let WEAK-XSPACE[L(n)] (WEAK-XSPACE*[L(n)]) denote the class of languages accepted by weakly L(n) space-bounded XTMs (1-inkdot XTMs). We show that (1) STRONG-ASPACE*[log log n]-WEAK-ASPACE[o(log n)] not-equal 0, (2) STRONG-USPACE*[log log n]-WEAK-USPACE[o(log n)] not-equal 0, (3) STRONG-ASPACE*[log log n]-WEAK-NSPACE*[o(log n)] not-equal 0, and (4) STRONG-ASPACE*[log log n]-WEAK-USPACE*[o(log n)] not-equal 0.

关键词： Turing machines

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A NOTE ON REAL-TIME ONE-WAY ALTERNATING MULTICOUNTER MACHINES

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THEORETICAL computer science 1991年第2期88卷 287-296页

作者： INOUE, K ITO, A TAKANAMI, I Department of Computer Science and Systems Engineering Faculty of Engineering Yamaguchi University Ube 755 Japan

This paper investigates several properties of one-way alternating multicounter machines which operate in real time, and shows that (1) for each k greater-than-or-equal-to 1, one-way alternating k-counter machines (1 acm(k)'s) which operate in real time are less powerful than 1acm(k + 1)'s which operate in real time, (2) for each k greater-than-or-equal-to 2, 1acm(k)'s which operate in real time are less powerful than 1acm(k)'s which operate in linear time, and (3) for each k greater-than-or-equal-to 1, the class of sets accepted by 1acm(k)'s which operate in real time is not closed under concatenation with regular sets, Kleene closure, reversal and length-preserving homomorphism.

关键词： Automata Theory

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An intelligent optimized object detection system for disabled people using advanced deep learning models with optimization algorithm

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Scientific Reports 2025年第1期15卷 1-19页

作者： Obayya, Marwa Al-Wesabi, Fahd N. Alshammeri, Menwa Iskandar, Huda G. Department of Biomedical Engineering College of Engineering Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Computer Science Applied College at Mahayil King Khalid University Mahayil Aseer Saudi Arabia Department of Information Systems Faculty of Computer and Information Technology Sana’a University Sana’a Yemen Department of Computer Science College of Computer and Information Sciences Jouf University Sakaka Saudi Arabia King Salman Center for Disability Research Riyadh 11614 Saudi Arabia

Visually impaired persons face several problems in their day-to-day lives, and technological intermediaries might help them encounter their challenges. Among other beneficial technologies, object detection (OD) is a computer technology related to image processing and computer vision (CV), which identifies and describes objects like vehicles, animals, and persons from digital videos and images. Visually impaired persons (VIPs) can utilize the OD approach for detecting problems and recognizing services to offer secure and informative navigation. Recently, machine learning (ML) and deep learning (DL) have been trained with numerous images of objects, which are highly related to people with disabilities. In this article, a novel Object Detection System for Disabled People Using Advanced Deep Learning Models and Sparrow Search Optimization (ODSDP-ADLMSSO) approach is proposed. The main aim of the ODSDP-ADLMSSO model is to enhance the OD method for visually challenged people. At first, the Gaussian filter (GF) is employed in the image pre-processing stage to remove noise and make the image input data more transparent. In addition, the YOLOv7 method is used for the process of OD to identify, locate, and classify objects within an image. Furthermore, the MobileNetV3 model is utilized for the feature extraction process. The temporal convolutional network (TCN) model is implemented for classification. Finally, the hyperparameter selection of the TCN model is implemented by the sparrow search optimization algorithm (SSOA) model. The efficiency of the ODSDP-ADLMSSO method is examined under the Indoor OD dataset. The comparison study of the ODSDP-ADLMSSO method demonstrated a superior accuracy value of 99.57% over existing techniques. © The Author(s) 2025.

关键词： Deep learning Disabled people MobileNetV3 Pathway Pedestrian Sparrow search optimization

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Interpretable inverse iteration mean shift networks for clustering tasks

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Neural Networks 2025年 189卷 107528页

作者： Zhang, Bingjie Yu, Zihan Wang, Jian Żelaszczyk, Maciej Zhang, Yaqian Mańdziuk, Jacek Zhang, Chao Pedrycz, Witold School of Mathematics and Statistics Weifang University Weifang261061 China College of Science Mathematics and Technology Wenzhou-Kean University Wenzhou325060 China Qingdao266580 China Faculty of Mathematics and Information Science Warsaw University of Technology Warsaw Poland Artificial Intelligence Institute University of Waikato Hamilton New Zealand Faculty of Computer Science AGH University of Krakow Cracow Poland School of Mathematical Sciences Dalian University of Technology Dalian116024 China Department of Electrical and Computer Engineering University of Alberta Edmonton ABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Sariyer/Istanbul Turkey

Neural networks have become the standard approach for tasks such as computer vision, machine translation and pattern recognition. While they exhibit significant feature representation capabilities, they often lack interpretability. This suggests that it might be beneficial to explore interpretable machine learning approaches in order to inform the neural network architectures. On the contrary, the mean shift algorithm (MS) has an unambiguous computational process, yet lacking in representation power. In order to draw on the advantages of both neural networks and the mean shift method, we propose the mean shift network (MS-Net) — a novel architecture, which is an inverse iteration fuzzy clustering network. Each layer of the proposed network possesses good interpretability, while the network as a whole is able to produce strong feature representations. To relax the limitations of the kernel function and ensure convergence, we design a continuously-differentiable Gaussian-inspired kernel as the activation function for the membership layer of MS-Net. Furthermore, we devise a weighted version of the architecture, called WMS-Net, to incorporate the importance of the training examples. We present theoretical results, with proofs of weak and strong convergence. We also consider two extensions to the proposed method, CB-MS-Net and CB-WMS-Net, which apply the curvature-based method to MS-Net and WMS-Net. Simulation results on 5 clustering tasks and 6 real-world datasets confirm the effectiveness of the proposed algorithms. © 2025

关键词： Fuzzy neural networks

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Interference-Aware Multipath Routing Protocol for QoS Improvement in Event-Driven Wireless Sensor Networks

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Tsinghua science and Technology 2011年第5期16卷 475-490页

作者： Marjan Radi Behnam Dezfouli Kamalrulnizam Abu Bakar Shukor Abd Razak Mohammad Ali Nematbakhsh Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia Faculty of Computer Engineering University of Isfahan

The existing multipath routing protocols for wireless sensor networks demonstrate the efficacy of traffic distribution over multiple paths to fulfill the Quality of Service （QoS） requirements of different applications. However, the performance of these protocols is highly affected by the characteristics of the wireless channel and may be even inferior to the performance of single-path approaches. Specifically, when multiple adjacent paths are being used concurrently, the broadcast nature of wireless channels results in inter-path interference which significantly degrades end-to-end throughput. In this paper, we propose a Low- Interference Energy-efficient Multipath Routing protocol （LIEMRO） to improve the QoS requirements of event-driven applications. In addition, in order to optimize resource utilization over the established paths, LIEMRO employs a quality-based load balancing algorithm to regulate the amount of traffic injected into the paths. The performance gain of LIEMRO compared to the ETX-based single-path routing protocol is 85%, 80%, and 25% in terms of data delivery ratio, end-to-end throughput, and network lifetime, respectively. Furthermore, the end-to-end latency is improved more than 60%.

关键词： LIEMRO QoS load balancing interference multipath routing event-driven

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Linearly and Quadratically Separable Classifiers Using Adaptive Approach

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Journal of computer science & Technology 2011年第5期26卷 908-918页

作者： Mohamed Abdel-Kawy Mohamed Ali Soliman Rasha M.Abo-Bakr Department of Computer and Systems Engineering Faculty of EngineeringZagazig UniversityZagazigEgypt Departement of Mathematics Faculty of ScienceZagazig UniversityZagazigEgypt

This paper presents a fast adaptive iterative algorithm to solve linearly separable classification problems in R *** each iteration,a subset of the sampling data （n-points,where n is the number of features） is adaptively chosen and a hyperplane is constructed such that it separates the chosen n-points at a margin and best classifies the remaining *** classification problem is formulated and the details of the algorithm are ***,the algorithm is extended to solving quadratically separable classification *** basic idea is based on mapping the physical space to another larger one where the problem becomes linearly *** illustrations show that few iteration steps are sufficient for convergence when classes are linearly *** nonlinearly separable data,given a specified maximum number of iteration steps,the algorithm returns the best hyperplane that minimizes the number of misclassified points occurring through these *** with other machine learning algorithms on practical and benchmark datasets are also presented,showing the performance of the proposed algorithm.

关键词： linear classification quadratic classification iterative approach adaptive technique

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