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Collect. of Pap. - 45th AIAA/ASME/ASCE/AHS/ASC Struct., Struct. Dyn. and Mater. Conf.;12th AIAA/ASME/AHS Adapt. Struct. Conf.;6th AIAA Non-Deterministic Approaches Forum;5th AIAA Gossamer Spacecraft Forum

作者： Liao, Li Talya, Shashishekara S. Kolonay, Raymond M. GE Global Research Center 1 Research Circle Schenectady NY 12301 Struct. Des. and Development Branch Air Force Research Laboratory Air Vehicles Directorate WPAFB OH 45433 Advanced Computing Technologies

In today's fast paced economy product design is becoming increasingly complex and requires tighter integration of the engineering and business processes not only within the individual businesses, but also across enterprises. This high demand for real-time business-to-business collaboration across enterprises requires a robust and secure channel not only for data exchange but also for process interaction. This paper presents a robust and secure collaborative environment to enable engineers to perform complex design analysis such as CAD, CAE, PDM, optimization, cost modeling, etc. across the network and Business firewalls. However, maintaining the secure communication protocol and close monitoring of the distributed computing process across network can present itself as a significant challenge. A multi-level security approach is developed to prevent any potential security and/or communication failure. This paper presents a typical engineering design scenario between General Electric (GE) and one of its vendors. In particular it will demonstrate how this environment can facilitate the communication of both data and applications across enterprise boundaries to tightly integrate a vendor into the GE's Design for Six Sigma process. Copyright © 2004 General Electric Company.

关键词： Distributed computer systems

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Vehicle re-identification with location and time stamps 32

Vehicle re-identification with location and time stamps

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32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019

作者： Lv, Kai Du, Heming Hou, Yunzhong Deng, Weijian Sheng, Hao Jiao, Jianbin Zheng, Liang Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University University of Chinese Academy of Sciences Australian National University

ISBN: (纸本)9781728125060

This paper focuses on the problem of vehicle re-identification (Re-ID). In our attempt, we propose a re-identification framework by exploiting vehicle location and time stamps. The location and time information have the potential to cover the shortage of appearance-based feature representations. First, we introduce an ensemble technique to combine the informative cues of multiple Re-ID models effectively. To further improve the accuracy, we then build up a system to acquire the vehicle location and time stamps. Specifically, we utilize the detected results to obtain the needed information. With the help of the proposed system, we can remove irrelevant images from a given ranking list. Our system finished 3rd place in the 2019 AI-City challenge for city-scale multi-camera vehicle re-identification. © 2019 IEEE Computer Society. All rights reserved.

关键词： Vehicles

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Hu-Fu: Efficient and Secure Spatial Queries over Data Federation 48th

Hu-Fu: Efficient and Secure Spatial Queries over Data Federa...

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48th International Conference on Very Large Data Bases, VLDB 2022

作者： Tong, Yongxin Pan, Xuchen Zeng, Yuxiang Shi, Yexuan Xue, Chunbo Zhou, Zimu Zhang, Xiaofei Chen, Lei Xu, Yi Xu, Ke Lv, Weifeng State Key Laboratory of Software Development Environment Beihang University China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University China The Hong Kong University of Science and Technology Singapore Management University University of Memphis

Data isolation has become an obstacle to scale up query processing over big data, since sharing raw data among data owners is often prohibitive due to security concerns. A promising solution is to perform secure queries over a federation of multiple data owners leveraging secure multi-party computation (SMC) techniques, as evidenced by recent federation work over relational data. However, existing solutions are highly inefficient on spatial queries due to excessive secure distance operations for query processing and their usage of general-purpose SMC libraries for secure operation implementation. In this paper, we propose Hu-Fu, the first system for efficient and secure spatial query processing on a data federation. The idea is to decompose the secure processing of a spatial query into as many plaintext operations and as few secure operations as possible, where fewer secure operators are involved and all secure operators are implemented dedicatedly. As a working system, Hu-Fu supports not only query input in native SQL, but also heterogeneous spatial databases (e.g., PostGIS, Simba, GeoMesa, and SpatialHadoop) at the backend. Extensive experiments show that Hu-Fu usually outperforms the state-of-the-arts in running time and communication cost while guaranteeing security. © 2022, American Mathematical Society. All rights reserved.

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Biogeography-based informative gene selection and cancer classification using SVM and Random Forests

Biogeography-based informative gene selection and cancer cla...

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Congress on Evolutionary Computation

作者： Sarvesh Nikumbh Shameek Ghosh V. K. Jayaraman Centre for Modeling and Simulation University of Pune Pune India Evolutionary Computing and Image Processing (ECIP) Center for Development of Advanced Computing Pune India

Microarray cancer gene expression data comprise of very high dimensions. Reducing the dimensions helps in improving the overall analysis and classification performance. We propose two hybrid techniques, Biogeography - based Optimization - Random Forests (BBO - RF) and BBO - SVM (Support Vector Machines) with gene ranking as a heuristic, for microarray gene expression analysis. This heuristic is obtained from information gain filter ranking procedure. The BBO algorithm generates a population of candidate subset of genes, as part of an ecosystem of habitats, and employs the migration and mutation processes across multiple generations of the population to improve the classification accuracy. The fitness of each gene subset is assessed by the classifiers - SVM and Random Forests. The performances of these hybrid techniques are evaluated on three cancer gene expression datasets retrieved from the Kent Ridge Biomedical datasets collection and the libSVM data repository. Our results demonstrate that genes selected by the proposed techniques yield classification accuracies comparable to previously reported algorithms.

关键词： Accuracy Support vector machines Cancer Radio frequency Ecosystems Optimization Vegetation

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Enhancing face matching in a suitable binary environment

Enhancing face matching in a suitable binary environment

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International Conference on Image Information Processing

作者： Apurba Das Kuntal Ghosh Advanced Image Processing Laboratory Centre for Development of Advanced Computing Kolkata India Machine Intelligence Unit and Center for Soft Computing Research Indian Statistical Institute Kolkata Kolkata India

Computerized human face recognition is a complex task of deformable pattern recognition. The principal source of complexities lies in the significant inter-class overlapping of faces due to the variations caused by different poses, illuminations, and expressions (PIE). The popularly used computerized face recognition algorithms like PCA, EBGM etc. are fairly reliable to determine facial attributes from an image. But, in most of the cases the features are extracted in terms of gray textures. When the database size is tuned to millions, then huge processing time is required, as each of the pixel must be represented using at least eight bits. In the present paper, our objective is to minimize the processing time by reducing the number of bits to represent each pixel. This we have done by combining two methods. The first one is a neuro-visually inspired method of figure-ground segregation (NFGS) which can convert the entire face image into a binary 2D array, efficiently. The second one is the scale invariant feature transform (SIFT) which extracts the scale invariant and rotation invariant features from the binarized face image and thereafter matches the features. The proposed algorithm is found successful in actually enhancing the performance of face matching. Psycho-visual experiments also corroborate the fact.

关键词： Face Face recognition Analysis of variance Information processing Databases Algorithm design and analysis Humans

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Discrimination of tea quality by polymer membrane electrode based potentiometric taste sensor

Discrimination of tea quality by polymer membrane electrode ...

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International Conference on Sensing Technology, ICST

作者： Tridib Sinha Arnab Halder Manmatha Mahato Basudam Adhikari Subrata Sarkar Nabarun Bhattacharyya Materials Science Centre Indian Institute of Technology Kharagpur India Center for Development of Advanced Computing Kolkata India

Tea is one of the most widely consumed beverages all over the world due to its delicate taste. It is, therefore, essential to establish a simple and reliable analytical tool for determination (or, discrimination) of tea quality. We have taken an attempt to discriminate the black tea of different qualities/grades by means of polymer membrane electrode based potentiometric taste sensor. Different types of phosphorylated and crosslinked polymer membranes were used to discriminate different grades of black tea by measuring the tastes in terms of membrane potential.

关键词： Electrodes Polymers Biomembranes Electric potential Sensors Principal component analysis

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An efficient FPGA implementation of Gaussian mixture models based classifier: Application to face recognition

An efficient FPGA implementation of Gaussian mixture models ...

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International Workshop on Systems, Signal Processing and their Applications (WOSSPA)

作者： Mehdi Neggazi Messaoud Bengherabi Z. Boulkenafet Abbes Amira Division of Architecture and multimedia Center of development of advanced technologies USA School of Computing University of the West of Scotland-á UK

This work aims to propose an efficient hardware/software system fo guassian mixture model (GMM) parts-based topology modeling for face identification and verification. Following its great success in speaker recognition, The GMM approach was extended to face recognition providing a good trade-off in terms of complexity, performance and robustness. Despite its reduced complexity compared to other statistical modeling techniques like hiden markov model (HMM) and its variants. The GMM scoring module still to be computationally intensive algorithm consisting of a series of complex tasks executed in sequential order. This constraint limits its suitability for real-time pattern recognition embedded applications. This paper presents an efficient hardware implementation of embedded GMM based classifier. Reconfigurable system in the form of field programmable gate arrays (FPGA) is deployed to embed the hardware part of the proposed system. Furthermore a design of exponential calculation circuit is proposed for the best compromise between effectiveness and complexity. Approximations are also developed to reduce the hardware complexity. The developed system performs the identification process of an unknown input pattern over 200 models in 2.3 seconds, our performance evaluation indicates that a speedup of around *** can be achieved over an optimized software implementation running on a 3.3GHz core i3 processor. A results precision of 10 -2 is obtained after performing the GMM calculation using the proposed hardware/software system.

关键词： Hardware Field programmable gate arrays Computer architecture Face Complexity theory Hidden Markov models Vectors

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A Bitcoin Address Multi-Classification Mechanism Based on Bipartite Graph-Based Maximization Consensus

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 783-800页

作者： Lejun Zhang Junjie Zhang Kentaroh Toyoda Yuan Liu Jing Qiu Zhihong Tian Ran Guo College of Information Engineering Yangzhou UniversityYangzhou225127China Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou510006China Research and Development Center for E-Learning Ministry of EducationBeijing100039China Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A∗STAR)Singapore138632Singapore School of Physics and Materials Science Guangzhou UniversityGuangzhou510006China

Bitcoin is widely used as the most classic electronic currency for various electronic services such as exchanges,gambling,marketplaces,and also scams such as high-yield investment *** the services operated by a Bitcoin address can help determine the risk level of that address and build an alert model *** engineering can also be used to flesh out labeled addresses and to analyze the current state of Bitcoin in a small *** this paper,we address the problem of identifying multiple classes of Bitcoin services,and for the poor classification of individual addresses that do not have significant features,we propose a Bitcoin address identification scheme based on joint multi-model prediction using the mapping relationship between addresses and *** innovation of the method is to(1)Extract as many valuable features as possible when an address is given to facilitate the multi-class service identification task.(2)Unlike the general supervised model approach,this paper proposes a joint prediction scheme for multiple learners based on address-entity mapping ***,after obtaining the overall features,the address classification and entity clustering tasks are performed separately,and the results are subjected to graph-basedmaximization *** final result ismade to baseline the individual address classification results while satisfying the constraint of having similarly behaving entities as far as *** testing and evaluating over 26,000 Bitcoin addresses,our feature extraction method captures more useful *** addition,the combined multi-learner model obtained results that exceeded the baseline classifier reaching an accuracy of 77.4%.

关键词： Bitcoin multi-service classification graph maximization consensus data security

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Two examples of GPGPU acceleration of memory-intensive algorithms

Two examples of GPGPU acceleration of memory-intensive algor...

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8th Eurographics Italian Chapter Conference 2010

作者： Marras, Stefano Mura, Claudio Gobbetti, Enrico Scateni, Riccardo Scopigno, Roberto University of Cagliari Dept. of Mathematics and Computer Science Italy Sardegna Ricerche DistrICT Lab. Italy CRS4 - Center for Advanced Studies Research and Development Sardinia Italy ISTI-CNR Visual Computing Lab. Italy

ISBN: (纸本)9783905673807

The advent of GPGPU technologies has allowed for sensible speed-ups in many high-dimension, memory-intensive computational problems. In this paper we demonstrate the effectiveness of such techniques by describing two applications of GPGPU computing to two different subfields of computer graphics, namely computer vision and mesh processing. In the first case, CUDA technology is employed to accelerate the computation of approximation of motion between two images, known also as optical flow. As for mesh processing, we exploit the massively-parallel architecture of CUDA devices to accelerate the face clustering procedure that is employed in many recent mesh segmentation algorithms. In both cases, the results obtained so far are presented and thoroughly discussed, along with the expected future development of the work. © The Eurographics Association 2010.

关键词： Parallel architectures

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Simulation and Operation Analysis of a Smart Grid Using Simulink 14th

Simulation and Operation Analysis of a Smart Grid Using Simu...

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14th International conference of the IMACS TC1 Committee, ELECTRIMACS 2022

作者： Van Waeyenberge, Alexander Canizes, Bruno Soares, João Ramos, Sérgio Ravyts, Simon Chavez, Juliana Vale, Zita GECAD Research Center Polytechnic of Porto Porto Portugal GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal ESAT ELECTA KU Leuven Ghent Belgium

ISBN: (纸本)9783031248368

Changes will be required to handle the increased power flow in the network as the distribution infrastructure ages and the number of EVs and renewable grows. Designing and operating an intelligent network that reacts to changing power flows to ensure the optimal operation is the most economical option than fortifying the network with heavier cables. This work aims to build a model of a 13 bus medium voltage distribution network with high penetration of distributed energy resources and use it to analyze network conditions. The MATLAB Simulink software is used to model and evaluate the network. The outcomes suggest the model is promising and valid even when renewable generation is at low levels. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smart power grids

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