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Boosting efficiency and stability of 2D alternating cation perovskite solar cells via rational surface-modification: Marked passivation efficacy of anion

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Journal of Energy Chemistry 2023年第9期84卷 354-362页

作者： Hualin Zheng Xuefeng Peng Tingxi Chen Ting Zhang Shihao Yuan Lei Wang Feng Qian Jiang Huang Xiaodong Liu Zhi David Chen Yanning Zhang Shibin Li State Key Laboratory of Electronic Thin Films and Integrated Devices and School of Optoelectronic Science and EngineeringUniversity of Electronic Science and Technology of China(UESTC)Chengdu 610054SichuanChina Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China(UESTC)Chengdu 610054SichuanChina Department of Electrical&Computer Engineering and Center for Nanoscale Science&EngineeringUniversity of KentuckyLexingtonKY 40506USA Institute of Electronic and Information Engineering of UESTC in Guangdong Dongguan 523808GuangdongChina

Two-dimensional(2D) alternating cation(ACI) perovskite surface defects,especially dominant iodine vacancies(V_Ⅰ) and undercoordinated Pb^(2+),limit the performance of perovskite solar cells(PVSCs).To address the issue,1-butyl-3-methylimidazolium trifluoro-methane-sulfonate(BMIMOTF) and its iodide counterpart(BMIMI) are utilized to modify the perovskite surface *** find that BMIMI can change the perovskite surface,whereas BMIMOTF shows a nondestructive and more effective defect passivation,giving significantly reduced defect density and suppressed charge-carrier nonradiative *** mainly attributes to the marked passivation efficacy of OTF-anion on V_Ⅰ and undercoordinated Pb^(2+),rather than BMIMI^(+) *** from the rational surface-modification of BMMIMOTF,the films exhibit an optimized energy level alignment,enhanced hydrophobicity and suppressed ion ***,the BMIMOTF-modified devices achieve an impressive efficiency of 21.38% with a record open-circuit voltage of 1.195 V,which is among the best efficiencies reported for 2D PVSCs,and display greatly enhanced humidity and thermal stability.

关键词： 2D ACI perovskite solar cells Charge-carrier nonradiative recombination Surface defects passivation Energy level alignment Ionic migration Stability

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Securing the Future after Pager Bombs:Lifecycle Protection of Smart Devices via Blockchain Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2355-2358页

作者： Fei Lin Qinghua Ni Jing Yang Juanjuan Li Nan Zheng Levente Kovács Radu Prodan Mariagrazia Dotoli Qing-Long Han Fei-Yue Wang the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBei-jing 100049China IEEE Obuda University John von Neumann Faculty of InformaticsBecsi Str.96/bH-1034 BudapestHungary the Institute of Information Technology University of Klagenfurt9020 Klagenfurt am WortherseeAustria the Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190

THE Lebanese wireless device explosion incident has drawn widespread attention,involving devices such as pagers,walkie-talkies,and other common devices[1].This event has revealed and highlighted the security vulnerabilities in global supply chains from raw material manufacturing and distribution to the usage of devices and equipment,signaling the onset of a new wave of"supply chain warfare"[2].

关键词： Smart cycle chains

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The Performance of a Local Search based on Vertex Coloring for the Maximum Clique Problem 22

The Performance of a Local Search based on Vertex Coloring f...

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10th International Conference on computer and Communications Management, ICCCM 2022

作者： Kanahara, Kazuho Ito, Shun Katayama, Kengo School of Engineering Okayama University of Science Japan Department of Information and Computer Engineering Okayama University of Science Japan

ISBN: (纸本)9781450396349

The maximum clique problem (MCP) is a fundamental combinatorial optimization problem that has many practical applications. In the exact methods, the idea of approximate coloring of vertices has been employed in the one proposed by Tomita, et al. in 1970's in order to prune unnecessary searching, and it now has become the important idea in the field of developing efficient exact algorithms for solving MCP. On the other hand, in the heuristic and metaheuristic research fields, few heuristics have been presented for MCP that use vertex coloring, and the search performance of a local search using the degree of saturation based on vertex coloring information is not clear. In this paper, we investigate the performance of a Local Search based on vertex coloring for MCP. Experimental results on the benchmark graphs show that the proposed algorithm is more effective than other simple Local Search for several difficult graphs such as perfect graphs. © 2022 ACM.

关键词： Combinatorial optimization

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Deep Convolutional Neural Network based Wheat Leaf Disease Detection in Precision Agriculture 5

Deep Convolutional Neural Network based Wheat Leaf Disease D...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Dey, Sreyashi Naidu, Roshan Dey, Om Subrato Balasundaram, A. Shaik, Ayesha Vellore Institute of Technology Chennai School of Computer Science and Engineering Chennai India Vellore Institute of Technology Chennai Center for Cyber Physical Systems Chennai India

ISBN: (纸本)9798331504403

Wheat is one of the fundamental crops that sustains billions of people globally. Unfortunately its production faces major challenges from numerous plant based diseases which can drastically decrease yields as well as the economic returns. There exist a variety of frameworks utilising computer vision and deep learning techniques which can be invaluable for numerous tasks aiding the stakeholders in agriculture and crop management by identifying diseased sections of *** methods to detect the disease are prone to human errors and such limitations underscore the need for automated and reliable disease detection systems. Also AI is likely to predict a future outbreak of any such disease by analysing the historical and geographical data. In this paper, a novel technique have been proposed whose novelty lies in the result that has been achieved using the proposed algorithm which when compared to two other deep learning models that are ResNet50 and VGG16 achieved a higher accuracy. The deep learning approach for wheat leaf disease detection implemented in this paper is performed using a convolutional neural network (CNN) architecture implemented in Python, OpenCV, NumPy, and TensorFlow alongside implementing some data augmentation leveraging the power of deep learning to extract complex features from wheat leaf images enabling accurate classification between healthy and diseased leaves. The aforementioned algorithm has been trained using a default Crop Disease Dataset extracted from a Github repository which has been able to achieve an accuracy of 88.53% with one full cycle of 30 epochs recording its final epoch with 91.04% accuracy and the final K Fold procedure resulting in 91.42% accuracy. © 2024 IEEE.

关键词： Convolutional neural networks

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Cooperative MIMO Applied Null Beamforming to Self in Full-Duplex Wireless Communication System and Its Implementation 24

Cooperative MIMO Applied Null Beamforming to Self in Full-Du...

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24th International Conference on Advanced Communication Technology, ICACT 2022

作者： Kawano, Masahiro Nagao, Yuhei Lanante, Leonardo Kurosaki, Masayuki Ochi, Hiroshi Kyushu Institute of Technology Graduate School of Computer Science and Systems Engineering Japan

ISBN: (纸本)9791188428090

This paper proposes a full-duplex wireless communication system applying cooperative multiple-input multiple-output (Co-MIMO). This proposal solves self-interference (SI) in full-duplex wireless communication systems by applying the block diagonalization used in multi-user MIMO (MU-MIMO). Therefore, there is no need for a radio frequency (RF) canceller, which has a large hardware size and is difficult to extend to MIMO. Furthermore, higher throughput can be achieved by applying Co-MIMO, in which multiple access points work together to communicate. We also introduce the implementation of the proposed method using a field-programmable gate array (FPGA) and software-defined radio (SDR) in this paper. It shows that SI cancellation can be realized by using them. The proposed method is implemented based on the IEEE 802.11n frame format as an example. In the experiment, a total of 30 [dB] SI cancellation is confirmed with a transmission power of-12[dBm]. The SI cancellation amount can be further increased by increasing the transmission power. © 2022 Global IT Research Institute-GiRI.

关键词： MIMO systems

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VVNet:Underwater Object Detection Network Based on Vision Transformer and Vision Retnet for Underwater Robot Picking

VVNet:Underwater Object Detection Network Based on Vision Tr...

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2024 International Symposium on Digital Home, ISDH 2024

作者： Liu, Jiaji Liu, ZhiTao Wang, YePeng Li, Fang School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China College of Engineering and Computing University of South Carolina Columbia United States

ISBN: (纸本)9798331509873

Underwater object detection is an important task in computer vision, but it is usually difficult due to the complex underwater environment. In recent years, underwater object detection methods based on deep learning have been proposed and have achieved promising results. However, there still exist issues with weaker extraction of global features from images. To tackle this issue, we propose a novel neural network, VVNet, which incorporates the newly introduced RMTBFA and CVit modules, achieving superior performance in extracting global features. RMTBFA integrates the core module of the Vision Retinet model, the Manhattan Attention Mechanism, while CVit incorporates the Vision Transformer module, which facilitates the extraction of global features from images. Furthermore, we introduce Shape-IoU as a loss function for IoU, which further enhances the accuracy of our model. Finally, we tested on the two datasets of URPC2017 and URPC2018. The results showed that our network model improved the underwater object detection task indicators. © 2024 IEEE.

关键词： Deep learning

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An Efficient and Reliable Multicasting for Smart Cities

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computers, Materials & Continua 2022年第7期72卷 663-678页

作者： Faheem Khan Muhammad Zahid Hüseyin Gürüler Ilhan Tarimer Taegkeun Whangbo Department of Computer Engineering Artificial intelligence LabGachon UniversitySeongnam13120Korea Department of Computer Science Bacha Khan University CharsaddaCharsadda24450Pakistan Department of Information Systems Engineering Mugla Sitki Kocman UniversityMugla48000Turkey

The Internet of thing(IoT)is a growing concept for smart cities,and it is compulsory to communicate data between different networks and *** the IoT,communication should be rapid with less delay and *** this purpose,flooding is used for reliable data communication in a smart cities concept but at the cost of higher overhead,energy consumption and packet drop *** paper aims to increase the efficiency in term of overhead and reliability in term of delay by using multicasting and unicasting instead of flooding during packet forwarding in a smart city using the IoT *** this paper,multicasting and unicasting is used for IoT in smart cities within a receiver-initiated mesh-based topology to disseminate the data to the cluster *** cities networks are divided into cluster head,and each cluster head or core node will be responsible for transferring data to the desired *** protocol is a novel approach according to the best of our knowledge,and it proves to be very useful due to its efficiency and reliability in smart cities concept because IoT is a collection of devices and having a similar interest for transmission of *** results are implemented in Network simulator 2(NS-2).The result shows that the proposed protocol shows performance in overhead,throughput,packet drop,delay and energy consumption as compared to benchmark schemes.

关键词： Multicasting unicasting flooding network simulator-2 internet of thing smart cities

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An Extended NEH based Method for Permutation Flowshop Scheduling Problem 22

An Extended NEH based Method for Permutation Flowshop Schedu...

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10th International Conference on computer and Communications Management, ICCCM 2022

作者： Ito, Shun Kanahara, Kazuho Oda, Tetsuya Katayama, Kengo School of Engineering Okayama University of Science Japan Department of Information and Computer Engineering Okayama University of Science Japan

ISBN: (纸本)9781450396349

The Permutation Flowshop Scheduling Problem (PFSP) is an important manufacturing scheduling problem where jobs have to be processed on machines, with each job following the same order at the machines. Since the problem to minimize makespan has been proven NP-hard when the number of is larger than three, a number of heuristic methods have been developed for finding high quality solutions in a reasonable computation time. NEH heuristic is one of the most efficient and effective constructive heuristic methods for PFSP. NEH algorithm consists of two key steps 1) order jobs based on priority rule (the original one is the sum (average) processing times of each job);2) insert jobs one by one according to the initial job order to construct a sequence (solution) of jobs by testing all possible inserting positions for unscheduled jobs. Since the first step is crucial for the resulting solution quality, many different priority rules have been investigated. It is well known that the priority rule based on two moments of the average and standard deviation of processing times to order jobs is effective. Furthermore, a more effective priority rule including a third moment called skewness has been developed recently. In this paper, we present an extended NEH based method called Extended NEH (E-NEH) for PFSP in which the appropriate combination of moments is selected from the three moments step by step, depending on the search situation. Computational results on benchmark problem set showed that E-NEH obtained better results, or at least the competitive ones, than the original NEH and other NEH based methods including the rules based on the three moments although more computation times are required. © 2022 ACM.

关键词： Heuristic methods

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Energy-Efficient Multi-Trip Routing for Municipal Solid Waste Collection by Contribution-Based Adaptive Particle Swarm Optimization

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Complex System Modeling and Simulation 2023年第3期3卷 202-219页

作者： Xiaoning Shen Hongli Pan Zhongpei Ge Wenyan Chen Liyan Song Shuo Wang Collaborative Innovation Center of Atmospheric Environment and Equipment Technology and also with the Jiangsu Key Laboratory of Big Data Analysis TechnologySchool of AutomationNanjing University of Information Science and TechnologyNanjing 210044China School of Automation Nanjing University of Information Science and TechnologyNanjing 210044China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation the Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China School of Computer Science University of BirminghamBirminghamB152TTUK

Waste collection is an important part of waste management *** costs and carbon emissions can be greatly reduced by proper vehicle ***,each vehicle can work again after achieving its capacity limit and unloading the *** this,an energy-efficient multi-trip vehicle routing model is established for municipal solid waste collection,which incorporates practical factors like the limited capacity,maximum working hours,and multiple trips of each *** both economy and environment,fixed costs,fuel costs,and carbon emission costs are minimized *** solve the formulated model effectively,contribution-based adaptive particle swarm optimization is *** strategies named greedy learning,multi-operator learning,exploring learning,and exploiting learning are specifically designed with their own searching *** assessing the contribution of each learning strategy during the process of evolution,an appropriate one is selected and assigned to each individual adaptively to improve the searching efficiency of the ***,an improved local search operator is performed on the trips with the largest number of waste sites so that both the exploiting ability and the convergence accuracy of the algorithm are *** of the proposed algorithm is tested on ten waste collection instances,which include one real-world case derived from the Green Ring Company of Jiangbei New District,Nanjing,China,and nine synthetic instances with increasing scales generated from the commonly-used capacitated vehicle routing problem benchmark *** with five state-of-the-art algorithms show that the proposed algorithm can obtain a solution with a higher accuracy for the constructed model.

关键词： municipal solid waste collection energy conservation multi-trip contribution particle swarm optimization

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Pixelated Image Abstraction via Power Diagram 21st

Pixelated Image Abstraction via Power Diagram

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21st Asia Simulation Conference, AsiaSim 2022

作者： Li, Tao Yao, Yuyou Wu, Wenming Zheng, Liping School of Computer Science and Information Engineering Hefei University of Technology Hefei China

ISBN: (纸本)9789811991943

Image abstraction is increasingly used in the field of computer graphics and computer vision. Existing methods divide the input images into disjoint regions and generate the abstract images with a reduced color palette. However, the generated images are not satisfactory due to the presence of blurred and unsmooth boundaries, etc. To this end, a pixelated image abstraction method via power diagrams is introduced in this paper to generate high-quality abstract images. Firstly, a pre-processing step is used to capture the significant information in the input image, which is divided into core and non-core parts according to the importance of each pixel. Then, a density map is calculated on basis of the division and grayscale value of each pixel. Furthermore, the primal image is partitioned into polygonal subregions with equal area constraint based on power diagrams. Based on the average RGB color of the 3 × 3 grids centered at its centroid, the pixels in each polygonal subregion are colored to produce the output abstract image. Experimental results demonstrate that the proposed method could generate high-quality images with abstraction controllable and smooth boundaries. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Pixels

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