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Three-Dimensional Modeling of Maize Canopies Based on Computational Intelligence

Plant Phenomics 2024年第2期6卷 349-363页

作者： Yandong Wu Weiliang Wen Shenghao Gu Guanmin Huang Chuanyu Wang Xianju Lu Pengliang Xiao Xinyu Guo Linsheng Huang National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefei 230601China Information Technology Research Center Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China Beijing Key Lab of Digital Plant National Engineering Research Center for Information Technology in AgricultureBeijing 100097China Nongxin Science&Technology(Beijing)Co. LtdBeijing 100097China

The 3-dimensional(3D)modeling of crop canopies is fundamental for studying functional-structural plant *** studies often fail to capture the structural characteristics of crop canopies,such as organ overlapping and resource *** address this issue,we propose a 3D maize modeling method based on computational *** initial 3D maize canopy is created using the t-distribution method to reflect characteristics of the plant architecture.

关键词： intelligence modeling based canopies computational dimensional maize three

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Recent advances in one-dimensional alkali-metal hexatitanate photocatalysts for environmental remediation and solar fuel production

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Journal of Materials science & technology 2024年第35期202卷 201-239页

作者： Qiang Wang Xiaofan Yang Zhao Jing Hong Liu Pengyi Tang Hongmin Zhu Bing Li National Key Laboratory of Materials for Integrated Circuits Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China 2020 X-Lab Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China School of Mechanical and Power Engineering East China University of Science and TechnologyShanghai 200237China Department of Metallurgy Graduate School of EngineeringTohoku UniversitySendai 980-8579Japan

The global energy crisis and environmental problems have become two unprecedented ***-conductor photocatalysis offers a promising strategy to solve them,while its practical application requires advanced photocatalytic *** recent years,one-dimensional(1D)alkali-metal hexatitanate(AHT)photocatalysts have attracted considerable attention in energy and environmental fields due to their high chemical stability,excellent photoactivity,unique ion-exchange,environment-friendly,and cost-effective *** this review,we firstly introduce the basic properties of AHT including crystal and electronic band structure,photoactivity,and structure-property-performance ***,the recent ad-vances in synthesis and modification strategies of 1D AHT photocatalysts are summarized thoughtfully,followed by a comprehensive discussion on their various environmental and energy applications,includ-ing pollutant degradation,H2 generation,and CO_(2)***,the key challenges and prospects are also highlighted for the development of high-performance 1D AHT-based photocatalysts for practi-cal *** hope that this review will shed some light on the rational design of 1D Ti-O-based nanomaterials for efficient environmental remediation and solar fuel production.

关键词： Alkali-metal hexatitanates One-dimensional nanomaterials Photocatalysis Pollutant degradation Solar fuels

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Sentimental Analysis of COVID-19 Twitter Data Using Machine Learning 8th

Sentimental Analysis of COVID-19 Twitter Data Using Machine ...

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8th International Conference on Emerging Research in Computing, information, Communication and Applications, ERCICA 2023

作者： Likhith, S.R. Pooja Ahuja, S. Prathibha, B.N. Uma Shankari, B. Department of School of Computer Science and Engineering and Information Science Bio-Intelligence Lab Presidency University Bengaluru India Nagarjuna College of Engineering and Technology Bengaluru India Nagarjuna College of Engineering and Technology Bengaluru India

ISBN: (纸本)9789819976218

Corona virus is considered as a scourge all over world by which most of the people got infected. Since the virus was spreading very quickly governments had to bring in very tough rules such as lock down. Lock down disrupted almost all sector like education, business etc.… During lock down and after the lock down people have used social media as their platform to express the opining regarding the pandemic. Tweeter is one such social media where people had shared their thoughts on the pandemic. In this study tweets which are made by the public is considered to analyses the sentiments. And in this research machine learning models are used to classify the data into five different classes namely positive, negative, neutral, extremely positive, and extremely negative. Decision Tree, Random Forest, Support Vector Machine, Logistic Regression, and Naïve Bayes are the ML models used to classify the sentiment and are achieving on accuracy of 99%, 99%, 97%, 94%, and 73%, respectively. Further precision, recall, F1-score, and world clod are calculated for each and every class. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19 Decision tree Logistic regression ML Naïve Bayes Random forest Sentiment analysis SVM Tweets

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Through-polymer,via technology-enabled,flexible,lightweight,and integrated devices for implantable neural probes

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Microsystems & Nanoengineering 2024年第2期10卷 279-291页

作者： Cunkai Zhou Ye Tian Gen Li Yifei Ye Lusha Gao Jiazhi Li Ziwei Liu Haoyang Su Yunxiao Lu Meng Li Zhitao Zhou Xiaoling Wei Lunming Qin Tiger H.Tao Liuyang Sun College of Electronics and Information Engineering Shanghai University of Electric PowerShanghaiChina 2020 X-Lab Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaiChina School of Graduate Study University of Chinese Academy of SciencesBeijingChina State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaiChina Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijingChina School of Physical Science and Technology ShanghaiTech UniversityShanghaiChina Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghaiChina Neuroxess Co. Ltd.(Jiangxi)NanchangJiangxiChina Guangdong Institute of Intelligence Science and Technology HengqinZhuhaiGuangdongChina Tianqiao and Chrissy Chen Institute for Translational Research ShanghaiChina

In implantable electrophysiological recording systems,the headstage typically comprises neural probes that interface with brain tissue and integrated circuit chips for signal *** advancements in MEMS and CMOS technology have significantly improved these components,their interconnection still relies on conventional printed circuit boards and sophisticated *** conventional approach adds considerable weight and volume to the package,especially for high channel count *** address this issue,we developed a through-polymer via(TPV)method inspired by the through-silicon via(TSV)technique in advanced three-dimensional *** innovation enables the vertical integration of flexible probes,amplifier chips,and PCBs,realizing a flexible,lightweight,and integrated device(FLID).The total weight of the FLIDis only 25%that of its conventional counterparts relying on adapters,which significantly increased the activity levels of animals wearing the FLIDs to nearly match the levels of control animals without ***,by incorporating a platinum-iridium alloy as the top layer material for electrical contact,the FLID realizes exceptional electrical performance,enabling in vivo measurements of both local field potentials and individual neuron action *** findings showcase the potential of FLIDs in scaling up implantable neural recording systems and mark a significant advancement in the field of neurotechnology.

关键词： alloy neural recording

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Introduction of information Security Fatigue Scale for Teleworking and its Effectiveness 9

Introduction of Information Security Fatigue Scale for Telew...

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9th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data science, BCD 2024

作者： Koyama, Hiroki Tanimoto, Shigeaki Shimoda, Atsushi Taki, Seiko Kanai, Atsushi Chiba Institute of Technology Faculty of Social System Science Chiba Japan Japan International University Faculty of Management and Information Studies Ibaraki Japan Chiba Institute of Technology Faculty of Information and Transformation Science Chiba Japan Hosei University Faculty of Science and Engineering Tokyo Japan

ISBN: (纸本)9798350394191

In recent years, government-led 'work style reform' has been promoted, and the teleworking style of work has been attracting attention. In particular, the spread of COVID-19 infection in 2020 has led to the rapid spread of telework. The spread of teleworking has led to a shift to paperless and web conferencing, and the risk of information security has increased due to the location-independent work style. In particular, unlike the face-to-face environment of an office, the telework environment poses psychological risks such as loneliness due to lack of communication. This paper clarifies information security fatigue in a telework environment based on previous research on security fatigue in a face-to-face environment that also considers such psychological aspects, and proposes countermeasures against it. First, we designed a questionnaire that took into account the telework environment based on the questionnaire survey of a previous study, and conducted a questionnaire survey using a web-based questionnaire. Considering the impact of COVID-19, a questionnaire survey was conducted twice, once in December 2020 at the early stage of COVID-19 expansion and once in January 2023 after COVID-19 establishment, both times targeting approximately 500 Japanese teleworkers. The results of these surveys showed that the security fatigue scale in the telework environment was similar to the information security fatigue results in the face-to-face environment of the previous study, with approximately 20% in the ideal state. In other words, security fatigue was found to be the same in a telework environment as in a face-to-face environment. Furthermore, the results of the analysis of the open-ended responses to the questionnaire survey showed similar trends to those indicated in previous studies. As a result of these findings, it was clarified that countermeasures such as 'implementation of education to arouse awareness of the concerned parties' and 'interviews regarding information s

关键词： information security fatigue latent rank theory security telework work style reform

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MACLSTM: A Weather Attributes Enabled Recurrent Approach to Appliance-Level Energy Consumption Forecasting

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Computers, Materials & Continua 2025年第2期82卷 2969-2984页

作者： Ruoxin Li Shaoxiong Wu Fengping Deng Zhongli Tian Hua Cai Xiang Li Xu Xu Qi Liu NARI-TECH Nanjing Control System Co. Ltd.Nanjing211106China School of Software Nanjing University of Information Science&TechnologyNanjing210044China Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services Nanjing210044China

Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.

关键词： Electrical load forecasting cloud computing smart grid weather attributes energy consumption time-series analysis

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VPFL:A verifiable privacy-preserving federated learning scheme for edge computing systems

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Digital Communications and Networks 2023年第4期9卷 981-989页

作者： Jiale Zhang Yue Liu Di Wu Shuai Lou Bing Chen Shui Yu School of Information Engineering Yangzhou UniversityYangzhou225009China Water Conservancy and Civil Engineering College Inner Mongolia Agricultural UniversityHohhot010018China Deakin Blockchain Innovation Lab School of Information TechnologyDeakin UniversityMelbourneVIC3125Australia College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing211106China School of Computer Science University of Technology SydneySydney2007Australia

Federated learning for edge computing is a promising solution in the data booming era,which leverages the computation ability of each edge device to train local models and only shares the model gradients to the central ***,the frequently transmitted local gradients could also leak the participants’private *** protect the privacy of local training data,lots of cryptographic-based Privacy-Preserving Federated Learning(PPFL)schemes have been ***,due to the constrained resource nature of mobile devices and complex cryptographic operations,traditional PPFL schemes fail to provide efficient data confidentiality and lightweight integrity verification *** tackle this problem,we propose a Verifiable Privacypreserving Federated Learning scheme(VPFL)for edge computing systems to prevent local gradients from leaking over the transmission ***,we combine the Distributed Selective Stochastic Gradient Descent(DSSGD)method with Paillier homomorphic cryptosystem to achieve the distributed encryption functionality,so as to reduce the computation cost of the complex ***,we further present an online/offline signature method to realize the lightweight gradients integrity verification,where the offline part can be securely outsourced to the edge *** security analysis demonstrates the proposed VPFL can achieve data confidentiality,authentication,and *** last,we evaluate both communication overhead and computation cost of the proposed VPFL scheme,the experimental results have shown VPFL has low computation costs and communication overheads while maintaining high training accuracy.

关键词： Federated learning Edge computing Privacy-preserving Verifiable aggregation Homomorphic cryptosystem

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AIR-PV: a benchmark dataset for photovoltaic panel extraction in optical remote sensing imagery

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science China(information sciences) 2023年第4期66卷 122-123页

作者： Zhiyuan YAN Peijin WANG Feng XU Xian SUN Wenhui DIAO Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology(NIST) Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory for Information Science of Electromagnetic Waves(MoE) Fudan University

The energy crisis has been a hot topic of global *** devices, a typical new energy source, have progressed rapidly and become among the main sources of power generation in the world [1]. Most photovoltaic fields are often constructed in large areas, making it difficult to monitor photovoltaic panel situations. Combining remote sensing(RS) and deep learning [2],

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An Efficient Graph Accelerator with Distributed On-Chip Memory Hierarchy 22nd

An Efficient Graph Accelerator with Distributed On-Chip Mem...

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22nd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Zheng, Ran Jiang, Yingxin Wang, Yibo Su, Yongbo Zheng, Long Yao, Pengcheng Liao, Xiaofei Jin, Hai National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Zhejiang Lab Hangzhou311121 China

ISBN: (纸本)9783031226762

Graph processing has evolved and expanded swiftly with artificial intelligence and big data technology. High-Bandwidth Memory (HBM), which delivers terabyte-level memory bandwidth, has opened up new development possibilities for FPGA-based graph accelerators. However, despite the tremendous expansion of underlying hardware capabilities, existing graph accelerators have not benefited too much. In this paper, we observe that the uniformed on-chip memory hierarchy is the key to the low scalability of existing graph accelerators. We present a novel graph accelerator with a distributed on-chip memory hierarchy called GraphS. The on-chip memory of GraphS is divided into numerous tiny blocks, each of which is assigned to only one Processing Element (PE). Different PEs are connected through a scalable network-on-chip (NoC). For realistic graphs with power-law properties, a degree-aware preprocessing method is designed to balance the workload among different PEs. Our results with various graph algorithms demonstrate that GraphS can outperform state-of-the-art ForeGraph by up to 21.84 ×. © 2023, Springer Nature Switzerland AG.

关键词： Network-on-chip

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A novel myocarditis detection combining deep reinforcement learning and an improved differential evolution algorithm

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CAAI Transactions on Intelligence technology 2024年第6期9卷 1347-1360页

作者： Jing Yang Touseef Sadiq Jiale Xiong Muhammad Awais Uzair Aslam Bhatti Roohallah Alizadehsani Juan Manuel Gorriz Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia Centre for Artificial Intelligence Research(CAIR) Department of Information and Communication TechnologyUniversity of AgderGrimstadNorway Department of Creative Technologies Air UniversityIslamabadPakistan School of Information and Communication Engineering Hainan UniversityHaikouHainanChina Institute for Intelligent Systems Research and Innovation(IISRI) Deakin UniversityWaurn PondsVictoriaAustralia Data Science and Computational Intelligence Institute University of GranadaGranadaSpain

Myocarditis is a serious cardiovascular ailment that can lead to severe consequences if not promptly *** is triggered by viral infections and presents symptoms such as chest pain and heart *** detection is crucial for successful treatment,and cardiac magnetic resonance imaging(CMR)is a valuable tool for identifying this ***,the detection of myocarditis using CMR images can be challenging due to low contrast,variable noise,and the presence of multiple high CMR slices per *** overcome these challenges,the approach proposed incorporates advanced techniques such as convolutional neural networks(CNNs),an improved differential evolution(DE)algorithm for pre-training,and a reinforcement learning(RL)-based model for *** this method presented a significant challenge due to the imbalanced classification of the Z-Alizadeh Sani myocarditis dataset from Omid Hospital in *** address this,the training process is framed as a sequential decision-making process,where the agent receives higher rewards/penalties for correctly/incorrectly classifying the minority/majority ***,the authors suggest an enhanced DE algorithm to initiate the backpropagation(BP)process,overcoming the initialisation sensitivity issue of gradient-based methods like back-propagation during the training *** effectiveness of the proposed model in diagnosing myocarditis is demonstrated through experimental results based on standard performance ***,this method shows promise in expediting the triage of CMR images for automatic screening,facilitating early detection and successful treatment of myocarditis.

关键词： classification differential evolution myocarditis reinforcement learning

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