检索结果-内蒙古大学图书馆

Multiscale analysis of fine slag from pulverized coal gasification in entrained-flow bed

International Journal of Coal science & technology 2024年第1期11卷 119-132页

作者： Lirui Mao Mingdong Zheng Baoliang Xia Facun Jiao Tao Liu Yuanchun Zhang Shengtao Gao Hanxu Li School of Chemical Engineering Anhui University of Science and TechnologyHuainan232001China School of Earth and Environment Anhui University of Science and TechnologyHuainan232001China Insititute of Energy Hefei Comprehensive National Science CenterHefei230031China

Fine slag(FS)is an unavoidable by-product of coal ***,which is a simple heap of solid waste left in the open air,easily causes environmental pollution and has a low resource utilization rate,thereby restricting the development of energy-saving coal gasification *** multiscale analysis of FS performed in this study indicates typical grain size distribution,composition,crystalline structure,and chemical bonding *** FS primarily contained inorganic and carbon components(dry bases)and exhibited a"three-peak distribution"of the grain size and regular spheroidal as well as irregular *** irregular particles were mainly adsorbed onto the structure and had a dense distribution and multiple pores and *** carbon constituents were primarily amorphous in structure,with a certain degree of order and active sites.C 1s XPS spectrum indicated the presence of C–C and C–H bonds and numerous aromatic *** inorganic components,constituting 90%of the total sample,were primarily silicon,aluminum,iron,and *** inorganic components contained Si–O-Si,Si–O–Al,Si–O,SO_(4)^(2−),and Fe–O *** 2p XPS spectrum could be deconvoluted into Fe 2p_(1/2) and Fe 2p_(3/2) peaks and satellite peaks,while Fe existed mainly in the form of Fe(III).The findings of this study will be beneficial in resource utilization and formation mechanism of fine slag in future.

关键词： Coal gasification Fine slag Multiscale analysis Carbon components Inorganic components

来源：评论

学校读者我要写书评

暂无评论

Improving UAV Image Target Detection: A Novel Approach Using OptiDETR with Swin Transformer

IAENG International Journal of Computer Science

引用

IAENG International Journal of computer science 2025年第3期52卷 771-780页

作者： Ma, Wenlong Liu, Weisheng School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China

In the analysis of drone aerial images, object detection tasks are particularly challenging, especially in the presence of complex terrain structures, extreme differences in target sizes, suboptimal shooting angles, and varying lighting conditions, all of which exacerbate the difficulty of recognition. In recent years, the DETR model based on the Transformer architecture has eliminated traditional post-processing steps such as NMS(Non-Maximum Suppression), thereby simplifying the object detection process and improving detection accuracy, which has garnered widespread attention in the academic community. However, DETR has limitations such as slow training convergence, difficulty in query optimization, and high computational costs, which hinder its application in practical fields. To address these issues, this paper proposes a new object detection model called OptiDETR. This model first employs a more efficient hybrid encoder to replace the traditional Transformer encoder. The new encoder significantly enhances feature processing capabilities through internal and cross-scale feature interaction and fusion logic. Secondly, an IoU (Intersection over Union) aware query selection mechanism is introduced. This mechanism adds IoU constraints during the training phase to provide higher-quality initial object queries for the decoder, significantly improving the decoding performance. Additionally, the OptiDETR model integrates SW-Block into the DETR decoder, leveraging the advantages of Swin Transformer in global context modeling and feature representation to further enhance the performance and efficiency of object detection. To tackle the problem of small object detection, this study innovatively employs the SAHI algorithm for data augmentation. Through a series of experiments, It achieved a significant performance improvement of more than two percentage points in the mAP (mean Average Precision) metric compared to current mainstream object detection models. Furthermore, ther

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

A wearable adaptive penile rigidity monitoring system for assessment of erectile dysfunction

引用

Microsystems & Nanoengineering 2024年第5期10卷 133-145页

作者： Xiangyang Wang Rujang Wang Yuyang Zhang You Wu Xu Wu Zihao Luo Yu Chang Xiansheng Zhang Tingrui Pan School of Biomedical Engineering Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhui 230026China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhouJiangsu 215123China School of Engineering Science University of Science and Technology of ChinaHefeiAnhui 230026China Department of Urology the First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui 230031China

Erectile dysfunction(ED)is a prevalent type of sexual dysfunction,and continuous monitoring of penile tumescence and rigidity during spontaneous nocturnal erections is crucial for its diagnosis and ***,the current clinical standard device,limited by its active mechanical load,is bulky and nonwearable and strongly interferes with erections,which compromises both monitoring reliability and patient ***,we report a wearable adaptive rigidity monitoring(WARM)system that employs a measurement principle without active loads,allowing for the assessment of penile tumescence and rigidity through a specifically designed elastic dual-ring *** dual-ring sensor,comprising two strain-sensing rings with distinct elastic moduli,provides high resolution(0.1%),robust mechanical and electrical stability(sustaining over 1000 cycles),and strong interference *** integrated flexible printed circuit(FPC)collects and processes sensing signals,which are then transmitted to the host computer via Bluetooth for ED ***,we validated the WARM system against the clinical standard device using both a penile model and healthy volunteers,achieving high ***,the system facilitates the continuous evaluation of penile erections during nocturnal tumescence tests with concurrent sleep monitoring,demonstrating its ability to minimize interference with nocturnal *** conclusion,the WARM system offers a fully integrated,wearable solution for continuous,precise,and patient-friendly measurement of penile tumescence and rigidity,potentially providing more reliable and accessible outcomes than existing technologies.

关键词： wear rigidity system

来源：评论

学校读者我要写书评

暂无评论

Molybdenum disulfide@nickel phyllosilicate hybrid for improving the flame retardancy and wear resistance of epoxy composites

引用

Frontiers of Chemical science and engineering 2023年第12期17卷 2114-2126页

作者： Shibin Nie Wei He Yuxuan Xu Wenli Zhai Hong Zhang Jinian Yang School of Public Security and Emergency Management Anhui University of Science and TechnologyHefei 231131China Institute of Energy Hefei Comprehensive National Science Center(Anhui Energy Laboratory)Hefei 230000China School of Safety Science and Engineering Anhui University of Science and TechnologyHuainan 232001China School of Materials Science and Engineering Anhui University of Science and TechnologyHuainan 232001China

In this study,nickel phyllosilicate was synthesized based on molybdenum disulfide(MoS2@NiPS)by the sol-gel method,and then MoS2@NiPS was used to prepare epoxy *** thermal stability,flame retardancy,and frictional performances of epoxy composites were *** the addition of 3 wt%MoS2@NiPS,the epoxy composite increased the limiting oxygen index from 23.8%to 26.1%and reduced the vertical burning time from 166 s for epoxy resin to 35 *** residual char of the epoxy composite increased from 11.8 to 20.2 wt%.MoS2@NiPS promoted the graphitization of the residual char,and facilitated the formation of a dense and continuous char layer,thereby improving the fire safety of epoxy *** epoxy composite with 3 wt%MoS2@NiPS had excellent wear resistance property with a wear rate of 2.19×10^(‒5) mm^(3)·N^(-1)·m^(-1),which was 68.8%lower than that of epoxy *** study presented a practical approach to improve the frictional and fire resistance of epoxy composites.

关键词： molybdenum disulfide nickel phyllosilicate epoxy resin flame retardancy

来源：评论

学校读者我要写书评

暂无评论

Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

引用

Energy engineering 2024年第12期121卷 3953-3979页

作者： Li Wang Xiaoyong Wang School of Computer Science and Engineering Anhui University of Science&TechnologyHuainan232001China School of Information Engineering Huainan Union UniversityHuainan232001China

Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced *** management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle *** study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power *** DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action *** often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing ***,these algorithms suffer from low sample ***,these factors contribute to convergence difficulties,low learning efficiency,and *** address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience ***,the correspondingMarkovDecision Process(MDP)is ***,an EMSbased on the improvedDRLmodel is *** simulation experiments are conducted against rule-based,optimization-based,andDRL-based *** proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global *** the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 *** to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%

关键词： Plug-in hybrid electric vehicles deep reinforcement learning energy management strategy deep deterministic policy gradient entropy regularization prioritized experience replay

来源：评论

学校读者我要写书评

暂无评论

Self-supervised Hypergraph Transformer with Alignment and Uniformity for Recommendation

IAENG International Journal of Computer Science

引用

IAENG International Journal of computer science 2024年第3期51卷 292-300页

作者： Yang, XianFeng Liu, Yang School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan China School of computer Science and Software Engineering University of Science and Technology Liaoning Anshan China

Graph neural networks have proven their effectiveness for user-item interaction graph collaborative filtering. However, most of the existing recommendation models highly depended on abundant and high-quality datasets and neglected the alignment and uniformity of embedding representation. The noisy and skewed distribution of data from real-world applications is ubiquitous. The alignment and uniformity are crucial for representation learning. In this paper, we propose SHTAU (self-supervised hypergraph transformer with alignment and uniformity for the recommendation) to address the problem. Specifically, we first perform a graph neural network on the user-item interaction graph, then captures the global collaboration relationship between users and items through the hypergraph transformer structure, and use the extracted global information to generate self-supervised signals for data enhancement on the user-item interaction graph to enhance the robustness of the recommendation algorithm. Simultaneously, alignment and uniformity auxiliary task update embeddings from different angles to improve performance. Extensive experiments are conducted on Yelp, Gowalla, MovieLens, Amazon-book and Tmall datasets. The experimental results show that SHTAU has obvious advantages over the baseline methods. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Alignment

来源：评论

学校读者我要写书评

暂无评论

Feature-Grounded Single-Stage Text-to-Image Generation

引用

Tsinghua science and technology 2024年第2期29卷 469-480页

作者： Yuan Zhou Peng Wang Lei Xiang Haofeng Zhang School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing 210044China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China

Recently,Generative Adversarial Networks(GANs)have become the mainstream text-to-image(T2I)***,a standard normal distribution noise of inputs cannot provide sufficient information to synthesize an image that approaches the ground-truth image ***,the multistage generation strategy results in complex T2I ***,this study proposes a novel feature-grounded single-stage T2I model,which considers the“real”distribution learned from training images as one input and introduces a worst-case-optimized similarity measure into the loss function to enhance the model's generation *** results on two benchmark datasets demonstrate the competitive performance of the proposed model in terms of the Frechet inception distance and inception score compared to those of some classical and state-of-the-art models,showing the improved similarities among the generated image,text,and ground truth.

关键词： text-to-image(T2I) feature-grounded single-stage generation Generative Adversarial Network(GAN)

来源：评论

学校读者我要写书评

暂无评论

Mixed Control for 2-D Markov Jump Systems with Multiaccess Stochastic Communication Protocol

引用

IAENG International Journal of Applied Mathematics 2024年第11期54卷 2379-2387页

作者： Zhang, Yu Chen, Qing Han, Chengyi Jiang, Taiping Chen, Yebin School of Computer Science and Technology Anhui University of Technology Ma’anshan243032 China

This paper addresses the mixed H∞/L2−L∞ control problem for two-dimensional (2-D) Markov jump systems using a multiaccess stochastic communication protocol (MSCP). The actuators are randomly selected, allowing only some of the actuator nodes to access the communication network channels. Two independent Markov chains govern the switching of plant modes and actuator access states. A state-feedback controller is formulated based on the MSCP and a hidden Markov model. We derive a sufficient condition such that the closed-loop 2-D system is stochastically stable and satisfies H∞/L2 − L∞ mixed performance employing Lyapunov’s direct method and Schur’s complement. Then, we develop a numerically efficient strategy to determine the desired controller gains of the state-feedback controller. Finally, we demonstrate the effectiveness of the proposed controller through a numerical example based on the Darboux equation. © (2024), (International Association of Engineers). All rights reserved.

关键词： State feedback

来源：评论

学校读者我要写书评

暂无评论

Minimal Context-Switching Data Race Detection with Dataflow Tracking

引用

Journal of computer science & technology 2024年第1期39卷 211-226页

作者：郑龙李洋辛杰刘海峰郑然廖小飞金海 National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services Computing Technology and System Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Data race is one of the most important concurrent anomalies in multi-threaded *** con-straint-based techniques are leveraged into race detection,which is able to find all the races that can be found by any oth-er sound race ***,this constraint-based approach has serious limitations on helping programmers analyze and understand data ***,it may report a large number of false positives due to the unrecognized dataflow propa-gation of the ***,it recommends a wide range of thread context switches to schedule the reported race(in-cluding the false one)whenever this race is exposed during the constraint-solving *** ad hoc recommendation imposes too many context switches,which complicates the data race *** address these two limitations in the state-of-the-art constraint-based race detection,this paper proposes DFTracker,an improved constraint-based race detec-tor to recommend each data race with minimal thread context ***,we reduce the false positives by ana-lyzing and tracking the dataflow in the *** this means,DFTracker thus reduces the unnecessary analysis of false race *** further propose a novel algorithm to recommend an effective race schedule with minimal thread con-text switches for each data *** experimental results on the real applications demonstrate that 1)without removing any true data race,DFTracker effectively prunes false positives by 68%in comparison with the state-of-the-art constraint-based race detector;2)DFTracker recommends as low as 2.6-8.3(4.7 on average)thread context switches per data race in the real world,which is 81.6%fewer context switches per data race than the state-of-the-art constraint based race ***,DFTracker can be used as an effective tool to understand the data race for programmers.

关键词： data race satisfiability modulo theory multi-threaded program dynamic detection

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based software engineering: progress,challenges, and opportunities

引用

science China(Information sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：