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Accurate structural descriptor enabled screening for nitrogen and oxygen vacancy codoped TiO_(2) with a large bandgap narrowing

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Journal of Materials science & technology 2022年第27期122卷 84-90页

作者： Kangyu Zhang Lichang Yin Gang Liu Hui-Ming Cheng Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China School of Materials Science and Engineering University of Science and Technology of ChinaShenyang 110016China Department of Physics and Electronic Information Huaibei Normal UniversityHuaibei 235000China

Nitrogen(N)doping has been widely adopted to improve the light absorption of TiO_(2).However,the newly introduced N-2p states are largely localized thus barely overlap with O-2p states in the valence band of TiO_(2),resulting in a shoulder-like absorption *** realize an apparent overlap between N-2p and O-2p states,charge compensation between N^(3-)and O^(2-)via electron transfer from oxygen vacancies(VO)to N dopants is one possible *** verify this,in numerous doping configurations of N/VO-codoped anatase TiO_(2),we identified two types of VOposition independent N-dopant spatial orderings by efficient screening enabled with a newly designed structural *** with others,these two types of the N-dopant spatial orderings are highly beneficial for charge compensation to produce an apparent overlap between N-2p and O-2p states,therefore achieving a large bandgap ***,the two types of the N-dopant spatial orderings can also be generalized to N/VO-codoped rutile TiO_(2)for bandgap narrowing.

关键词： Structural descriptor TiO_(2) Bandgap narrowing Doping Machine learning Density functional theory

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A Hybrid Eagle's Web Swarm Optimization (EWSO) technique for effective cloud resource management 12

A Hybrid Eagle's Web Swarm Optimization (EWSO) technique for...

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12th IEEE International Conference on Advanced Computing, ICoAC 2023

作者： Jagadish Kumar, N. Balasubramanian, C. Kumar, A. Naresh Kumar, G.Praveen Sree, S. Jindhiya Sri Sai Ram Engineering College Department of Computer Science and Business Systems West Tambaram Chennai India P.S.R Engineering College Department of Computer Science and Engineering Sivakasi India Velammal Institute of Technology Pancheti Department of Information Technology Chennai India

ISBN: (纸本)9798350318210

encompasses a range of tasks focused on the efficient allocation and administration of resources within a cloud computing environment, all in order to meet the requirements of cloud users. The key components of cloud computing resource management consist of resource allocation, task scheduling, load balancing, and data storage optimization. Cloud resource management poses several challenges, including the optimization of resource allocation, efficient task scheduling, and effective data storage management in distributed file systems like HDFS. These challenges require careful consideration and strategic approaches to ensure optimal utilization of resources, timely execution of tasks, and efficient handling of large-scale data. This paper introduces a novel approach for optimizing cloud resources using Eagle's Web Swarm Optimization (EWSO). The EWSO technique integrates three distinct algorithms, namely the Black Widow optimizer, Golden Eagle optimizer, and Chaotic Leader & Salp optimizer, to address specific aspects of resource optimization in the cloud. By combining these algorithms, the proposed approach aims to enhance the efficiency and the reliability of resource allocation, task scheduling, and HDFS optimization in the cloud environment. To evaluate the effectiveness of the proposed EWSO technique, its efficiency is compared to several other bio-inspired optimization techniques commonly used in cloud resource management. These include WARMS, AARP, ILPEPS and BFDHP. Through this comparison, the performance, and capabilities of the EWSO technique can be assessed in the context of cloud resource management. The findings from experiments prove the effectiveness of the proposed EWSO technique compared to other bio-inspired mechanisms in terms of resource allocation, task scheduling, and HDFS optimization. These findings provide empirical evidence that the EWSO technique outperforms alternative approaches in managing and optimizing cloud resources, highlighting its

关键词： Resource allocation

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Effect of Boron Content on Microstructure and Electromagnetic Properties of SiBCN Ceramics

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Kuei Suan Jen Hsueh Pao/Journal of the Chinese Ceramic Society 2025年第3期53卷 607-619页

作者： Chen, Pingan Hong, Sizeng Li, Xiangcheng Zhu, Yingli Chen, Fu The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and Technology Wuhan430081 China Key Laboratory of High Temperature Electromagnetic Materials and Structure of MOE Wuhan University of Science and Technology Wuhan430081 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan430081 China

Introduction An issue of electromagnetic pollution has escalated with the proliferation of electronic devices, thus posing a significant threat to human health and electronic equipment. Consequently, there is an increasing interest in materials possessing robust electromagnetic wave absorption capabilities. Based on the absorption mechanisms of electromagnetic wave materials, they can be categorized into dielectric loss and magnetic loss types. The loss mechanisms of magnetic loss materials encompass damping and hysteresis losses. Dielectric loss materials absorb electromagnetic waves through polarization and electrical conductivity losses, typically having elevated dielectric constants. Such materials include ferroelectrics, metal oxides, and inorganic ceramics. Polymer-derived ceramics (PDCs) represent a pivotal technology for the design and fabrication of functional ceramics. This methodology effectively harnesses the advantages of both polymer and ceramic materials. In contrast to conventional ceramic preparation techniques that consume energy, PDCs enable the production of ceramic materials with tunable elemental compositions and controllable crystalline structures through meticulous design and synthesis of the molecular structures of polymer precursors, coupled with precise control in the pyrolysis process. In this paper, polyborosilazanes with different boron contents were synthesized via modulating the quantity of added boron source. The impact of boron content on the structure and properties of polyborosilazanes and the phase composition/microstructure of ceramics was investigated. Methods 20 g of n-hexane was added to a reaction flask in ice bath. Methyl dichlorosilane, vinylmethyl dichlorosilane, boron trichloride, and hexamethyldisilane were sequentially added to the reaction flask at different molar ratios. The mixture was stirred in an argon atmosphere for 24 h. The temperature was then raised to 100 ℃ and maintained for 3 h to remove n-hexane and othe

关键词： Signal receivers

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Semi-Global Robust Practical Output Voltage Tracking for Single-Phase UPS Inverters via Sampled-Data Control 42

Semi-Global Robust Practical Output Voltage Tracking for Sin...

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42nd Chinese Control Conference, CCC 2023

作者： Zeng, Kaiji Liu, Wei Sun, Weijie Liu, Weidong Ministry of Education School of Automation Science and Engineering South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Guangzhou510641 China

ISBN: (纸本)9789887581543

This paper deals with the sampled-data semi-global robust practical output voltage tracking problem for single-phase voltage source uninterruptible power supply inverters. We construct an aperiodic sampled-data state feedback control law in an internal model principle framework. Lyapunov analysis shows that as long as the upper bound of the sampling time interval of the controller is less than an explicitly computable threshold, our problem can be handled by the proposed sampled-data control law. And the tracking error is guaranteed to approach a given neighborhood of the origin asympotically. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Uninterruptible power systems

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Hybrid Convolutional Neural Networks for Enhanced Detection of Mango Leaf Diseases 6

Hybrid Convolutional Neural Networks for Enhanced Detection ...

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6th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024

作者： Porna, Shweta Bhattacharjee Kabir, Md. Firoz Rana, Md. Imran Chowdhury Sajol, Md. Saiful Islam Roy, Tonmoy Khan, Mohammad Aman Ullah Adnan, Md. Al Bhavani, Girigula Durga Ahsanullah University of Science and Technology Department of Computer Science and Engineering Dhaka Bangladesh Master's in Information Technology University of the Cumberlands United States Bachelor of Business Administration International American university Los Angeles CA United States Louisiana State University Department of Computer Science and Engineering LA United States Data Analytics & Information Systems Utah State University Logan United States Brac University School of Data and Sciences Department of Computer Science and Engineering Dhaka1212 Bangladesh Noakhali Science And Technology University Bsc in software engineering Bangladesh Andhra Pradesh Amaravati522237 India

ISBN: (纸本)9798331505790

The classification of mango leaf diseases is critical for effective disease management and ensuring high-quality yields in mango cultivation. This paper presents a comprehensive study on using deep learning techniques to classify various mango leaf diseases, leveraging convolutional neural networks (CNNs) and hybrid models. A total of 7,524 images were used in our study. These included 4,000 training samples and 3,524 testing samples. The images were split into eight groups, which were powdery mildew, cutting weevil, anthracnose, bacterial canker, sooty mold, gall midge, healthy, and die back. The suggested method starts with feature extraction using VGG19 and MobileNetB1, then classification using both standalone models (ResNet50V2 + EfficientNetB1 and VGG16 + MobileNetB1). We employed data augmentation techniques like random brightness adjustment, rotation, and flipping to enhance the robustness of the model. We conducted hyperparameter tuning using hyperband and Bayesian optimization to optimize the model's performance. Experimental results demonstrate that the hybrid models achieved superior performance, with ResNet50V2 and EfficientNetB1 attaining a perfect accuracy of 100 % on the test set. These findings highlight the potential of deep learning techniques to improve the accuracy and reliability of mango leaf disease diagnosis, contributing significantly to the advancement of precision agriculture. © 2024 IEEE.

关键词： Fruits

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Phenylethynyl-terminated Imide Oligomers Modified by Reactive Diluent for Resin Transfer Molding Application

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Chinese Journal of Polymer science 2022年第1期40卷 107-120页

作者： Wei-Jie Hong Li-Li Yuan Hao-Yang Zhang Chao Cui Wei Chen Shi-Yong Yang Key Laboratory of Science and Technology on High-tech Polymer Materials Chinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Astronautical Systems Engineering Technology Beijing 100076China Aerospace Research Institute of Materials&Processing Technology Beijing 100076China

To meet the processing requirements of resin transfer moulding(RTM)technology,reactive diluent containing m-phenylene moiety was synthesized to physically mixed with phenylethynyl terminated cooligoimides with well-designed molecular weights of 1500-2500 g/mol derived from 4,4’-(hexafluoroisopropylidene)diphthalic anhydride(6 FDA),3,4’-oxydianiline(3,4’-ODA)and m-phenylenediamine(m-PDA).This blend shows low minimum melting viscosity(<1 Pa·s)and enlarged processing temperature window(260–361℃).FPI-R-1 stays below 1 Pa·s for2 h at 270℃.The relationship between the molecular weight of the blend and its melting stability was first *** oligoimides with lower molecular weights exhibit better melting *** curing at 380℃for 2 h,the thermosetting polyimide resin demonstrates superior heat resistance(T_(g)=420-426℃).

关键词： Oligoimide Resin transfer molding Reactive diluent Melting stability

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Combined active and passive adaptive variable admittance compliant control for space robotic manipulators

Combined active and passive adaptive variable admittance com...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Gao, Hang Zhang, Xiaodong Ma, Chao Zhou, Cheng University of Science and Technology Beijing School of Mechanical Engineering Beijing100083 China Beijing Institute of Spacecraft System Engineering Cast Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Application China

ISBN: (纸本)9798350325706

This paper develops a combined active and passive adaptive variable admittance compliant control algorithm for space robotic manipulators. In fact, the assembly task for space robots requires compliance and precision while ensuring avoidance of any occurrences of rigid collision throughout the process. Therefore, we design a new combined active and passive variable admittance control structure combined with the following three parts to meet these acquirements. Firstly, we develop an active variable admittance algorithm to facilitate the space robot rapid movement, enabling it to achieve higher speeds while maintaining compliance. Then, to mitigate the occurrence of unforeseen rigid collisions during the robot motion, we devise a passive variable admittance control algorithm, which aims to minimize the impact of collision events and ensure the robot safe operation. Furthermore, by employing the Lyapunov theory, a new active adaptive variable admittance control algorithm is presented for robot constant force output. Consequently, through contrast experiments, we demonstrate the effectiveness and enhanced performance of the proposed algorithm. © 2023 IEEE.

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A Study of Cyber Bullying Classification Using Social Media and Texual Analysis Based on Machine Learning Approches 14

A Study of Cyber Bullying Classification Using Social Media ...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Rahman Aronno, Md. Shafiur Zumma, Md.Thoufiq Prodhan, Rashed Zohora, Fatema Tuz Sakib, Nazmus Tahmiduzzaman, K.B.M. Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh Wilmington University Department of Information Systems Technologies DE United States Bangladesh University of Business &technology Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350335095

In today's world, cyberbullying is a problem that is becoming more and more common, especially among teenagers and young people. The prevalence of social networking sites and other digital communication tools has made it simpler for offenders to harass their victims in secret and without repercussions. Natural language processing (NLP) methods have been used in recent years to categorize instances of cyberbullying and assist identify them. The language used in online conversations is examined using these approaches to look for trends and signs of cyberbullying behavior. The purpose of this study is to investigate how well NLP approaches can be used to recognize and categorize cyberbullying behavior. To provide a thorough knowledge of the many types of cyberbullying, the study will use a variety of data sources, including social media posts, chat logs, and other online conversations. Overall, this research will further our knowledge of the intricate nature of cyberbullying and shed light on the potential applications of NLP approaches to lessen its negative impacts. © 2023 IEEE.

关键词： Digital communication systems

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Sparsing and Smoothing for the seq2seq Models

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第3期4卷 464-472页

作者： Zhao, Shuai Liang, Zhuoqian Wen, Jinming Chen, Jie College of Information Science and Technology Jinan University Guangzhou511400 China Pazhou Lab Guangzhou510330 China Shanghai Key Laboratory of Trustworthy Computing School of Software Engineering East China Normal University Shanghai200062 China

Current neural language models are trained to minimize cross-entropy and use softmax to compute the locally normalized probabilities over the target. While this setup provides solid results in several natural language processing (NLP) tasks, one unsatisfying aspect is its dense output. This density is wasteful, making models hard to interpret and assigning probability mass to many implausible outputs. To overcome this problem, we propose T-softmax, a simple but effective method to draw considerably sparse probability out of neural language models than softmax. Our method avoids dense output by truncating the unreliable tail of the probability distribution to improve the model's performance. In addition, we generalize logits with temperature, a critical regularization technique, from the softmax to T-softmax. To show our approach as a drop-in replacement for softmax, we evaluate them on three NLP tasks: summary generation, question answer, and math word problem. Experimental results show that our proposed model significantly improves performance without sacrificing speed;notably, in all experiments, our method outperforms the softmax. © 2020 IEEE.

关键词： Probability distributions

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Research on Risk Analysis and Testing Method of the Data in Intelligent and Connected Vehicles 24

Research on Risk Analysis and Testing Method of the Data in ...

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24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Ji, Haojie Wang, Jingyan Wang, Liyong Chen, Yupeng He, Peng Jin, Long Fang, Junzhe State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology Univ. Beijing China China Automotive Engineering Research Institute Co. Ltd. Chongqing China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

With the increasing information interaction in intelligent and connected vehicles (ICVs), there are more and more security vulnerabilities in the exploitable data. These vulnerabilities may cause personal privacy leaks, property damage, etc. This paper analyzes the data security risks in the four basic functional areas of ICVs and introduces a novel desensitized data testing framework. This work will provide support for security testing methods for desensitized data in ICVs and provide effective security protection for sensitive personal information in ICVs. © ASCE.

关键词： information leakage

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