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High performance computing: a brief review and prospects

National Science Review 2016年第1期3卷 16-16页

作者： Depei Qian School of Computer Science and Engineering Beihang University Guest Editor of Special Topic & Editorial Board Member of NSR

Because of its strategic importance in solution of grand challenge problems and in the promotion of social and economic development,high performance computing(HPC)has been one of the most active research areas in both... 详细信息

关键词： HPC this High performance computing a brief review and prospects

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Erosive burning correlations: Scaling hydraulic diameter

Erosive burning correlations: Scaling hydraulic diameter

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43rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference

作者： Glick, Robert L. Glick, Marilyn P. 1159 S 525 E Rensselaer IN 47978 AIAA Engineering Advisory Board Computer Simulation of Advanced Rockets Program University ot Illinois-Champaign Urbana Purdue University W. Lafayette IN 47904

ISBN: (纸本)1563479036

Lenoir & Robillard's hydraulic diameter (Dh) scaling deficiencies are eliminated with generalized Prandtl number (Pr) scaling. Parameter perturbations about TitanIIIc's aft end port state at ignition reveal this result agrees with Lenoir & Robillard and SPP's empirical modification for small motors but can differ significantly for larger motors depending on the environments' position in the parameter space. Homogeneous and heterogeneous propellant internal ballistic applications are briefly discussed: the former is nearly operational but heterogeneous propellants dominate;the latter is not robust and much work is required. Paths to improved ballistic predictions are sketched.

关键词： Prandtl number

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Perfect-balance planar clock routing with minimal path-length 92

Perfect-balance planar clock routing with minimal path-lengt...

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Proceedings of the 1992 IEEE/ACM international conference on computer-aided design

作者： Qing Zhu Wayne Wei-Ming Dai Computer Engineering Board of Studies University of California Santa Cruz Santa Cruz CA

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Image segmentation method based on fisher criterion and genetic algorithm

Image segmentation method based on fisher criterion and gene...

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2011 International Conference on Advanced Materials and computer Science(ICAMCS 2011)

作者： Fu xian-xiang Chen zu-jue Zhao yong-fu Department of Computer Science and Telecommunications Engineering of Jiangsu University Local Marine Board of Zhenjiang

Precise recognition of the weed by computer vision, furthermore raising the weeding efficiency, reducing the use of herbicide, and decreasing the pollution to the environment is one of the key technologies in the field of precision agriculture. To determine the optimal threshold in image automatic segmentation and solve one-dimensional histogram without obvious peak and valley distribution, image segmentation method based on fisher criterion and improved adaptive genetic algorithm is proposedThis method can preserve the multifamily of population and the astringency of the algorithm, and can overcome the problems of poor astringency and premature occurrence. The result shows that the proposed approach has better immunity to Salt and Pepper Noise and greatly shortens the time of image segmentation.

关键词： 2-D histogram Adaptive Genetic Algorithm fisher criterion Image Segmentation

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Facial expression recognition based on a weighted local binary pattern

Facial expression recognition based on a weighted local bina...

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2010 13th International Conference on computer and Information Technology, ICCIT 2010

作者： Shoyaib, Mohammad Abdullah-Al-Wadud, M. Youl, Jo Moo Alam, Muhammad Mahbub Chae, Oksam Department of Computer Engineering Kyung Hee University Yongin Gyonggi Korea Republic of Dept. of Industrial and Management Engineering Hankuk University of Foreign Studies Yongin Korea Republic of Dept. of CIT Islamic University of Technology Board Bazar Gazipur Bangladesh

ISBN: (纸本)9781424484973

We introduce a facial expression recognition method, which incorporates a weight to the Local Binary Pattern (LBP), and generates solid expression features. Furthermore, we use Adaboost to select a small set of prominent features, which is used by the Support Vector Machine (SVM) to classify facial expressions efficiently. Experimental results demonstrate that our method outperforms the state-of-the-art methods in terms of both accuracy and complexities. ©2010 IEEE.

关键词： Local binary pattern

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Foliar Chlorophyll Monitoring to Enhance Palm Oil Plant Productivity 9th

Foliar Chlorophyll Monitoring to Enhance Palm Oil Plant Prod...

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9th Future Technologies Conference, FTC 2024

作者： Adnan, Nur Damia Kassim, Mohd Sallehin Mohd Dao, Hassan Mohamed, Maizatul Suriza Sajak, Aznida Abu Bakar Computer Engineering Section Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur50250 Malaysia Faculty of Engineering Princess of Naradhiwas University Narathiwat96000 Thailand Malaysian Palm Oil Board Selangor Bandar Baru Bangi43650 Malaysia

ISBN: (纸本)9783031731211

In the modern agricultural landscape, enhancing productivity stands as a central objective. The monitoring system of palm oil plant health development based on Foliar Chlorophyll Leaves with IoT, presents an innovative approach to improve palm oil plantation management. Utilizing the ESP32 microcontroller, data from the color sensor is processed, with integrated Wi-Fi capabilities enabling seamless connectivity to the platform. These readings are subject to storage, analysis, and comparison against predefined ranges to ascertain the distinct health status of the plants. Collaboration with the Malaysian Palm Oil board ensures alignment with user requirements and demands, strengthening the system’s efficacy and reliability. The paper provides a detailed overview of the plant health monitoring process, outlining various treatments and their corresponding RGB color sensor readings. Each treatment, representing a specific plant type, is accompanied by the date of leaf testing, offering a comprehensive insight into the monitoring procedure. Results indicate the system’s effectiveness in detecting stress-induced physiological changes and early signs of diseases, equipping farmers and plantation managers with actionable data for informed decision-making. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Decision making

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Multi-class multi-object detection and tracking system in 3 dimensions using YOLOv5 3

Multi-class multi-object detection and tracking system in 3 ...

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3rd International Conference on Range Technology, ICORT 2023

作者： Bhateja, Aditi Sharma, Sanyam Krishna, Abhishek Chaudhary, Himanshu Lall, Brejesh Kalra, Prem K Computer Science Indian Institute of Technology Delhi India Delhi Technological University Software Engineering Delhi India Delhi Technological University Information Technology Delhi India Securities and Exchange Board of India India Electrical Engineering Indian Institute of Technology Delhi India

ISBN: (纸本)9781665493314

It is of great significance to detect and track multiple objects belonging to multiple classes in 3 dimensions and the same can be applied to various research domains. One such application pertains to multi-fish detection and tracking The problem is of significance to marine researchers who want to study the behaviour of fish in a constrained environment i.e. in an aquarium, using different sensors. For this study, a data set consisting of different fishes in an aquarium was constructed and Microsoft Kinect was used to capture the movements in 3 dimensions. The data set was cleaned, aligned, and calibration was done to make it suitable for object detection and tracking In this paper, YOLOv5s model was improvised, hereafter referred as YOLOv5-With Attention Mechanism (YOLOv5-WAM), and an object detection and tracking pipeline was designed to detect and track underwater objects (fishes in our work) belonging to multiple classes in 3D. YOLOv5-WAM can be adapted for use on devices having low compute availability, making it suitable for real time object detection and tracking using low cost experimental setup. YOLOv5-WAM showed about 1% improvement in mAP for our custom dataset while for Fish4Knowkdge and COCO dataset, the improvements were to the tune of 7% when compared to YOLOv5s. The results and analysis of the approach are presented in this paper. © 2023 IEEE.

关键词： Fish

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On the effectiveness of simultaneous self-test techniques

On the effectiveness of simultaneous self-test techniques

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1992 IEEE VLSI Test Symposium, VLSI 1992

作者： Johnson, P.A. Ferguson, F.J. Sequoia Semiconductor Inc. 940 Disc Drive Scotts ValleyCA95066 United States Board of Studies in Computer Engineering University of California Santa Cruz Santa CruzCA95064 United States

ISBN: (纸本)0780306236

Describes a built-in self-test (BIST) technique for general sequential circuits in which storage elements in a circuit are replaced with self-test elements. These elements are connected as a feedback shift register, and used to both generate test patterns and compress test responses. Benchmarks were run on a number of standard sequential benchmark circuits to determine single stuck-at fault coverage. The results of these tests indicate that the self-test techniques presented obtain fault coverage similar to that of random test techniques. © 1992 IEEE.

关键词： Built-in self test

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A Deep reinforcement Learning Approach for Early Detection of tomato plant disease using CNNs and machine learning Techniques 4

A Deep reinforcement Learning Approach for Early Detection o...

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4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Kumar, Amit Ekvitayavetchanukul, Pongkit Donda, Prashanth Gupta, Anurag Sachdeva, Vrinda Singh, Bakshish Ajay Kumar Garg Engineering College Department of Information Technology Ghaziabad India The Board of Khonkaen University Affairs Khonkaen University Thailand CVR College of Engineering Department of Csit Hyderabad India Abes Engineering College Department of Computer Engineering Ghaziabad India G.L Bajaj Institute of Technology and Management Department of Computer Science and Engineering Greater Noida India Raj Kumar Goel Institute of Technology Department of Information Technology Ghaziabad India

ISBN: (纸本)9798350364729

The present research attempts to improve tomato plant disease early detection strategies by using a variety of machine learning models, such as Recurrent Neural Networks (RNN), K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and Convolutional Neural Networks (CNN). Using the special advantages of these models, the major objective is to correctly diagnose diseases like Early blight, Bacterial leaf spot, Bacterial wilt, and Leaf curl. The work expands the foundation for disease detection by careful dataset construction, feature extraction, and preprocessing. The accuracy of CNN is the greatest at 97.5%, followed by SVM at 92.2%), KNN at 88.4%), and RNN at 86.2%. The results show remarkable accuracy. Our research demonstrates the promise of machine learning in precision agriculture by providing a useful tool for managing and diagnosing diseases early on, increasing crop output, and encouraging environmentally friendly farming methods. © 2024 IEEE.

关键词： Deep reinforcement learning

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Bounds on signal delay in RC mesh networks

Bounds on signal delay in RC mesh networks

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： P.K. Chan Computer Engineering Board of Studies University of California Santa Cruz Santa Cruz CA USA

The author addresses the problem of estimating the inverse of the node-conductance matrix R of a resistive network as in MOS LSI. The main result is the definition of two bounding matrices. Since the derivation of these matrices depends solely on Tellegen's theorem, the result is therefore applicable to all resistive networks that obey Kirchoff's laws, whether the networks are linear or nonlinear, time-invariant or time-varying, reciprocal or nonreciprocal. It is observed that the upper bound matrix tends to be closer to R if the resistive network is tree-like. Likewise, the lower bound matrix tends to be closer to R if the resistive network consists mainly of parallel connections of identical resistors. From the bounding matrices, bounds on the delays can be obtained.< >

关键词： Intelligent networks Mesh networks Tree graphs Computational modeling Circuit simulation Delay estimation Capacitors Classification tree analysis Resistors Voltage

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