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HORIZONTAL LOADING TEST OF ULTRA-HIGH STRENGTH WOODEN GLUED PANEL CONSIDERING INFLUENCE OF VERTICAL LOAD

AIJ Journal of Technology and Design 2024年第75期30卷 733-738页

作者： Hisamitsu, Kajikawa Haruhiko, Ogawa Jiei, Shibata Dept. of Arch. School of Science and Technology Meiji Univ. Dr.Eng. Japan School of Science and Technology Meiji Univ Japan Misawa Homes Institute of Research and Development Co. Ltd. Dr.Eng. Japan

woodenglued Intended conducted for under high-rise paan ppel liedtimber Additionally, vertical buildings, loadselastoplastic usin horizontal g the ultra-hi loading analysis ghtests strength .using were deformation modal theory was conducted. Experimental results showed vertical load affects the skeleton curve of the bearing wall, with stiffness wa of enhancedandsrotationalexperimental largel increasing y unaffected deformationresultsvertical .Furthermore indicatedat load. the This wall ，the comparative was baseanalysisattributed *** validation Maximum to the suppressionreplicated ana1 strength ytical experimental values. In summary, the feasibility of the bearing wall with an independent vertical and horizont l resistance system was demonstrated. © 2024 Architectural institute of Japan. All rights reserved.

关键词： Walls (structural partitions)

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Transformer-Enhanced U-Net with Transfer Learning for Accurate Detection of Eye Coloboma 4

Transformer-Enhanced U-Net with Transfer Learning for Accura...

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4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Dhayanithi, A. Bala, K. Bharath Institute of Higher Education and Research School of Computing Department of Computer Science and Engineering Tamil Nadu Chennai600073 India Bharath Institute of Higher Education and Research School of Computing Department of Computer Science and Engineering Tamil Nadu Chennai600073 India

ISBN: (纸本)9798331508845

Eye coloboma is a type of congenital eye abnormality that causes developmental abnormalities of the eye which may culminate in eye disorders that fundamentally derange eyesight. Fractional and timely diagnosis remains highly important to its proper managing and treating. This work proposes a model with a Transformer-Enhanced U-Net design implemented with Transfer Learning to enhance the ability of the model to detect and segment eye coloboma from medical imaging data. This work builds upon the benefits of U-Net which has shown promising results especially in the biomedical image segmentation problem through addition of transformer modules that introduce long range dependencies and contextual information. This enhancement makes helps the model to pay more attention to such minor aspects as coloboma and general diagnostic accuracy consequently. Thanks to Transfer Learning with a pretrained backbone, for example Efficient Net the system is provided with Feature Representations recovered from large datasets that are already available and training time is drastically cut short while the performance of the system is not compromised at *** approach includes fine-tuning of Transformer-Enhanced U-Net model using a selected set of eye images, labelled for coloboma existence. By including the self-attention mechanism, the model is capable of focusing on the critical regions in the image, increasing its responsiveness to any form of coloboma. Preliminary tests show that this scheme performs better than the standard convolutional networks for segmenting complex regions by minimizing false negatives. Further, the model's flexibility to different imaging conditions demonstrates its suitability in realistic clinical applications. The objective of this research is to come up with a dependable, Auto-Generated diagnostic tool that will help the ophthalmologists in the early diagnosis of the eye related illnesses hence making increased positive outcomes for eye patients. The Transf

关键词： Image segmentation

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A Tutorial on Federated Learning from Theory to Practice:Foundations,Software Frameworks,Exemplary Use Cases,and Selected Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 824-850页

作者： M.Victoria Luzón Nuria Rodríguez-Barroso Alberto Argente-Garrido Daniel Jiménez-López Jose M.Moyano Javier Del Ser Weiping Ding Francisco Herrera Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain Department of Communications Engineering University of the Basque Country(UPV/EHU)and also with TECNALIABasque Research&Technology Alliance(BRTA)Spain School of Information Science and Technology Nantong UniversityNantong 226019China

When data privacy is imposed as a necessity,Federated learning(FL)emerges as a relevant artificial intelligence field for developing machine learning(ML)models in a distributed and decentralized *** allows ML models to be trained on local devices without any need for centralized data transfer,thereby reducing both the exposure of sensitive data and the possibility of data interception by malicious third *** paradigm has gained momentum in the last few years,spurred by the plethora of real-world applications that have leveraged its ability to improve the efficiency of distributed learning and to accommodate numerous participants with their data *** virtue of FL,models can be learned from all such distributed data sources while preserving data *** aim of this paper is to provide a practical tutorial on FL,including a short methodology and a systematic analysis of existing software ***,our tutorial provides exemplary cases of study from three complementary perspectives:i)Foundations of FL,describing the main components of FL,from key elements to FL categories;ii)Implementation guidelines and exemplary cases of study,by systematically examining the functionalities provided by existing software frameworks for FL deployment,devising a methodology to design a FL scenario,and providing exemplary cases of study with source code for different ML approaches;and iii)Trends,shortly reviewing a non-exhaustive list of research directions that are under active investigation in the current FL *** ultimate purpose of this work is to establish itself as a referential work for researchers,developers,and data scientists willing to explore the capabilities of FL in practical applications.

关键词： Data privacy distributed machine learning federated learning software frameworks

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Zero Trust Networks: Evolution and Application from Concept to Practice

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computers, Materials & Continua 2025年第2期82卷 1593-1613页

作者： Yongjun Ren Zhiming Wang Pradip Kumar Sharma Fayez Alqahtani Amr Tolba Jin Wang School of Computer Science School of Cyber Science and EngineeringEngineering Research Center of Digital ForensicsMinistry of EducationNanjing University of Information Science and TechnologyNanjing210044China Department of Computing Science University of AberdeenAberdeenAB243FXUK Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Sanya Institute of Hunan University of Science and Technology Sanya572024China

In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defen-sive techniques,Zero Trust Networks(ZTN)have emerged as a widely recognized *** Trust not only addresses the shortcomings of traditional perimeter security models but also consistently follows the fundamental principle of“never trust,always verify.”Initially proposed by John Cortez in 2010 and subsequently promoted by Google,the Zero Trust model has become a key approach to addressing the ever-growing security threats in complex network *** paper systematically compares the current mainstream cybersecurity models,thoroughly explores the advantages and limitations of the Zero Trust model,and provides an in-depth review of its components and key ***,it analyzes the latest research achievements in the application of Zero Trust technology across various fields,including network security,6G networks,the Internet of Things(IoT),and cloud computing,in the context of specific use *** paper also discusses the innovative contributions of the Zero Trust model in these fields,the challenges it faces,and proposes corresponding solutions and future research directions.

关键词： Zero trust cybersecurity software-defined perimeter micro-segmentation internet of things

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ConvKyber: Unleashing the Power of AI Accelerators for Faster Kyber with Novel Iteration-based Approaches

IACR Transactions on Cryptographic Hardware and Embedded Sys...

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IACR Transactions on Cryptographic Hardware and Embedded Systems 2024年第2期2024卷 25-63页

作者： Zhou, Tian Zheng, Fangyu Fan, Guang Wan, Lipeng Tang, Wenxu Song, Yixuan Bian, Yi Lin, Jingqiang School of Cyber Security University of Science and Technology of China Heifei China School of CryptologyUniversity of Chinese Academy of Sciences Beijing China Ant Group Hangzhou China School of Computer Science and TechnologyUniversity of Chinese Academy of Sciences Beijing China Beijing Research Institute University of Science and Technology of China Beijing China

The remarkable performance capabilities of AI accelerators offer promising opportunities for accelerating cryptographic algorithms, particularly in the context of lattice-based cryptography. However, current approaches to leveraging AI accelerators often remain at a rudimentary level of implementation, overlooking the intricate internal mechanisms of these devices. Consequently, a significant number of computational resources is underutilized. In this paper, we present a comprehensive exploration of NVIDIA Tensor Cores and introduce a novel framework tailored specifically for Kyber. Firstly, we propose two innovative approaches that efficiently break down Kyber’s NTT into iterative matrix multiplications, resulting in approximately a 75% reduction in costs compared to the state-of-the-art scanning-based methods. Secondly, by reversing the internal mechanisms, we precisely manipulate the internal resources of Tensor Cores using assembly-level code instead of inefficient standard interfaces, eliminating memory accesses and redundant function calls. Finally, building upon our highly optimized NTT, we provide a complete implementation for all parameter sets of Kyber. Our implementation surpasses the state-of-the-art Tensor Core based work, achieving remarkable speed-ups of 1.93x, 1.65x, 1.22x and 3.55x for polyvec_ntt, KeyGen, Enc and Dec in Kyber-1024, respectively. Even when considering execution latency, our throughput-oriented full Kyber implementation maintains an acceptable execution latency. For instance, the execution latency ranges from 1.02 to 5.68 milliseconds for Kyber-1024 on R3080 when achieving the peak throughput. © 2024, Ruhr-University of Bochum. All rights reserved.

关键词： Tensors

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Angle-uniform parallel coordinates

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Computational Visual Media 2023年第3期9卷 495-512页

作者： Kaiyi Zhang Liang Zhou Lu Chen Shitong He Daniel Weiskopf Yunhai Wang School of Computer Science and Technology Shandong UniversityQingdao 266237China National Institute of Health Data Science Peking UniversityBeijing 100191China Visualization Research Center(VISUS) University of Stuttgart70569 StuttgartGermany

We present angle-uniform parallel coordinates,a data-independent technique that deforms the image plane of parallel coordinates so that the angles of linear relationships between two variables are linearly mapped along the horizontal axis of the parallel coordinates *** being a common method for visualizing multidimensional data,parallel coordinates are ineffective for revealing positive correlations since the associated parallel coordinates points of such structures may be located at infinity in the image plane and the asymmetric encoding of negative and positive correlations may lead to unreliable *** address this issue,we introduce a transformation that bounds all points horizontally using an angleuniform mapping and shrinks them vertically in a structure-preserving fashion;polygonal lines become smooth curves and a symmetric representation of data correlations is *** further propose a combined subsampling and density visualization approach to reduce visual clutter caused by *** method enables accurate visual pattern interpretation of data correlations,and its data-independent nature makes it applicable to all multidimensional *** usefulness of our method is demonstrated using examples of synthetic and real-world datasets.

关键词： parallel coordinates multidimensional data deformation correlations

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Critical Relation Path Aggregation-Based Industrial Control Component Exploitable Vulnerability Reasoning

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computers, Materials & Continua 2023年第5期75卷 2957-2979页

作者： Zibo Wang Chaobin Huo Yaofang Zhang Shengtao Cheng Yilu Chen Xiaojie Wei Chao Li Bailing Wang School of Computer Science and Technology Harbin Institute of TechnologyWeihai264209China National Computer System Engineering Research Institute of China Beijing100083China School of Cyber Science and Technology Harbin Institute of TechnologyHarbin150001China Weihai Cyberguard Technologies Co.Ltd. Weihai264209China Faculty of Science Vrije Universiteit AmsterdamAmsterdam1081HVNetherlands

With the growing discovery of exposed vulnerabilities in the Industrial Control Components(ICCs),identification of the exploitable ones is urgent for Industrial Control System(ICS)administrators to proactively forecast potential ***,it is not a trivial task due to the complexity of the multi-source heterogeneous data and the lack of automatic analysis *** address these challenges,we propose an exploitability reasoning method based on the ICC-Vulnerability Knowledge Graph(KG)in which relation paths contain abundant potential evidence to support the *** reasoning task in this work refers to determining whether a specific relation is valid between an attacker entity and a possible exploitable vulnerability entity with the help of a collective of the critical *** proposed method consists of three primary building blocks:KG construction,relation path representation,and query relation reasoning.A security-oriented ontology combines exploit modeling,which provides a guideline for the integration of the scattered knowledge while constructing the *** emphasize the role of the aggregation of the attention mechanism in representation learning and ultimate *** order to acquire a high-quality representation,the entity and relation embeddings take advantage of their local structure and related *** critical paths are assigned corresponding attentive weights and then they are aggregated for the determination of the query relation *** particular,similarity calculation is introduced into a critical path selection algorithm,which improves search and reasoning ***,the proposed algorithm avoids redundant paths between the given pairs of *** results show that the proposed method outperforms the state-of-the-art ones in the aspects of embedding quality and query relation reasoning accuracy.

关键词： Path-based reasoning representation learning attention mechanism vulnerability knowledge graph industrial control component

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Hydrogen Energy Demand Management in China:A Department Scenario Analysis Method

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Energy Engineering 2025年第3期122卷 971-983页

作者： Zhongxun Li Bing Wang Xiaolin Liu Center for Sustainable Development and Energy Policy Research School of Energy and Mining EngineeringChina University of Mining and Technology-BeijingBeijing100083China Research Institute of Decision-Making Science and Big Data School of ManagementChina University of Mining and Technology-BeijingBeijing100083China

The proposal of carbon neutrality target makes decarbonization and hydrogenation typical features of future energy development in *** a wide range of application scenarios,hydrogen energy will experience rapid growth in production and *** formulate an effective hydrogen energy development strategy for the future of China,this study employs the departmental scenario analysis method to calculate and evaluate the future consumption of hydrogen energy in China’s heavy industry,transportation,electricity,and other related *** technical parameters are selected and predicted accurately and reliably in combination with different development *** findings indicate that the period from 2030 to 2050 will enjoy rapid development of hydrogen energy,having an average annual growth rate of 2%to 4%.The technological progress and breakthroughs scenario has the greatest potential for hydrogen demand scale among the four development *** this scenario,the total demand for hydrogen energy is expected to reach 446.37Mt in *** sector will be the sector with the greatest potential for hydrogen deployment growth from 2023 to 2060,which is expected to rise from 0.038Mt to about 163.18Mt,with the ambitious growth in the ***,hydrogen energy has a considerable development potential in the steel sector,and the trend of de-refueling coke by hydrogenation in this sector will be imperative for this energy-intensive industries.

关键词： Hydrogen demand management department scenario analysis carbon neutrality

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Toward a QoS-Guaranteed Cloud Through Elastic Resource Scaling and Request Updating 24th

Toward a QoS-Guaranteed Cloud Through Elastic Resource Scal...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Shen, Bingchen Liu, Jiawei Zhao, Gongming Xu, Hongli Bao, Jianfeng School of Computer Science and Technology University of Science and Technology of China Hefei China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou China

ISBN: (纸本)9789819615414

In multi-tenant clouds, service providers offer services to tenants and generate profits by deploying network function (e.g., NAT, VPN) instances. Tenants access services by forwarding their requests to corresponding instances. In practice, traffic dynamics typically result in load imbalances and overloads among instances, severely impacting QoS. Existing works primarily address these issues through request updating and elastic resource scaling. Request updating is a fast and feasible method but may incur significant costs since these methods need prepurchasing enough servers. Elastic resource scaling is an approach to save infrastructure costs but may degrade user QoS when adjusting the number of instances. This paper presents a problem called ESRU, aimed at providing a QoS-guaranteed and cost-effective elastic resource scaling and request updating in clouds. Furthermore, we propose the ESRU-A algorithm, which features a bounded approximation factor based on randomized rounding and a greedy strategy. Performance analysis indicates our algorithm can achieve optimal value with high certainty. Experiments conducted across various topologies and traffic dynamic scenarios have demonstrated that our proposed algorithm reduces infrastructure costs by up to 45.17% while increasing throughput by 58.17%, compared to state-of-the-art benchmarks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud platforms

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A hybrid CNN-LSTM model for diagnosing rice nutrient levels at the rice panicle initiation stage

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Journal of Integrative Agriculture 2024年第2期23卷 711-723页

作者： Fubing Liao Xiangqian Feng Ziqiu Li Danying Wang Chunmei Xu Guang Chu Hengyu Ma Qing Yao Song Chen School of Computer Science and Technology Zhejiang Sci-Tech UniversityHangzhou 310018China China National Rice Research Institute Chinese Academy of Agricultural SciencesHangzhou 310006China School of Agriculture Yangtze UniversityJingzhou 434025China

Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice *** diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth ***,we propose a hybrid model for diagnosing rice nutrient levels at the early panicle initiation stage(EPIS),which combines a convolutional neural network(CNN)with an attention mechanism and a long short-term memory network(LSTM).The model was validated on a large set of sequential images collected by an unmanned aerial vehicle(UAV)from rice canopies at different growth stages during a two-year *** with VGG16,AlexNet,GoogleNet,DenseNet,and inceptionV3,ResNet101 combined with LSTM obtained the highest average accuracy of 83.81%on the dataset of Huanghuazhan(HHZ,an indica cultivar).When tested on the datasets of HHZ and Xiushui 134(XS134,a japonica rice variety)in 2021,the ResNet101-LSTM model enhanced with the squeeze-and-excitation(SE)block achieved the highest accuracies of 85.38 and 88.38%,*** the cross-dataset method,the average accuracies on the HHZ and XS134 datasets tested in 2022 were 81.25 and 82.50%,respectively,showing a good *** proposed model works with the dynamic information of different rice growth stages and can efficiently diagnose different rice nutrient status levels at EPIS,which are helpful for making practical decisions regarding rational fertilization treatments at the panicle initiation stage.

关键词： dynamic model of deep learning UAV rice panicle initiation nutrient level diagnosis image classification

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