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4th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2000

作者： Huang, Fu Jie Zhou, Zhihua Zhang, Hong-Jiang Chen, Tsuhan Electrical and Computer Engineering Department Carnegie Mellon University United States State Key Lab for Novel Software Technology Nanjing University China Media Computing Group Microsoft Research China

ISBN: (纸本)0769505805

In this paper, we describe a novel neural network architecture, which can recognize human faces with any view in a certain viewing angle range (fromy left 30 degrees to right 30 degrees out of plane rotation). View-specific eigenface analysis is used as the frontend of the system to extract features, and the neural network ensemble is used for recognition. Experimental results show that the recognition accuracy of our network ensemble is higher than conventional methods such as using a single neural network to recognize faces of a specific view. © 2000 IEEE.

关键词： Neural networks

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Auto-generation and redundancy reduction of test cases for reactive systems

Auto-generation and redundancy reduction of test cases for r...

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2010 2nd International Conference on software technology and Engineering, ICSTE 2010

作者： Chen, Donghuo Li, Xuandong Zhao, Shizhong School of Computer Science and Technology Soochow University Suzhou China Key Lab. of Novel Software Technology Nanjing University Nanjing China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

ISBN: (纸本)9781424486656

Testing is the fundamental technique to assess the correctness of software systems, but it is cost-labored to generate test cases. One solution to change the situation is to automatize some parts of the testing process, especially the generation of test cases using formal theory and technology. The research work in the direction shows the good perspective. This paper targets on the automatic generation of test cases based on IOSTS, which is widely used to model reactive systems with data. When selecting test cases based on a set of test purposes specified by IOSTS or temporal logic, in general, the redundancy phenomena are unavoidable in the derived test suite. Hence, some strategies are presented for eliminating the redundancies in order to reduce the cost of implementing testing. More importantly, the strategies are directly applied to test cases in form of IOSTS, such that it can reduce not only the size of test suite, but also the cost of deriving test cases. © 2010 IEEE.

关键词： Redundancy

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A Code Search Method Incorporating Code Annotations 19th

A Code Search Method Incorporating Code Annotations

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19th EAI International Conference on Collaborative computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Li, Qi Liu, Jianxun Zhang, Xiangping School of Computer Science and Engineering Hunan University of Science and Technology Hunan Xiangtan411201 China Hunan Key Lab for Services Computing and Novel Software Technology Hunan University of Science and Technology Hunan Xiangtan411201 China

ISBN: (纸本)9783031545207

Code search is a technique for users to retrieve code snippets from the Code base using natural language, which is dedicated to retrieve the target code accurately and quickly to improve the efficiency of software development. The deep learning based code search technique greatly improves the accuracy of search by learning the relationship between code and query statements. Since it relies on the extracted code features, acquiring more code features is the key to quickly improve the search performance. However, most of the previous works have not taken code annotations into consideration. In this paper, we take code annotations as code features and apply them to code search, which is named ICA-CS (Code Search that Incorporates Code Annotations). In the method, firstly, the code features are embedded to get the corresponding vector representation. It is then processed by bidirectional LSTM (Long Short-Term Memory) network or multi-head attention respectively, followed by features fusion. And finally, the model is trained by joint embedding and using the minimised ranking loss function. As the experimental results show, on the evaluation metric MRR (mean reciprocal rank) compared to the state-of-the-art models DeepCS, SAN-CS, CARLCS-CNN and SelfAtt, the proposed model improves 48.96%, 17.11%, 41.01% and 13.07%, respectively. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Long short-term memory

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Container lifecycle-aware scheduling for serverless computing

Container lifecycle-aware scheduling for serverless computin...

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作者： Wu, Song Tao, Zhiheng Fan, Hao Huang, Zhuo Zhang, Xinmin Jin, Hai Yu, Chen Cao, Chun National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China

Elastic scaling in response to changes on demand is a main benefit of serverless computing. When bursty workloads arrive, a serverless platform launches many new containers and initializes function environments (known as cold starts), which incurs significant startup latency. To reduce cold starts, platforms usually pause a container after it serves a request, and reuse this container for subsequent requests. However, this reuse strategy cannot efficiently reduce cold starts because the schedulers are agnostic of container lifecycle. For example, it may ignore soon available containers or evict soon needed containers. We propose a container lifecycle-aware scheduling strategy for serverless computing, CAS. The key idea is to control distribution of requests and determine creation or eviction of containers according to different lifecycle phases of containers. We implement a prototype of CAS on OpenWhisk. Our evaluation shows that CAS reduces 81% cold starts and therefore brings a 63% reduction at 95th percentile latency compared with native scheduling strategy in OpenWhisk when there is worker contention between workloads, and does not add significant performance overhead. © 2021 John Wiley & Sons Ltd.

关键词： Containers

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Automated verification of the FreeRTOS scheduler in HIP/SLEEK

Automated verification of the FreeRTOS scheduler in HIP/SLEE...

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IEEE 6th International Symposium on Theoretical Aspects of software Engineering, TASE 2012

作者： Ferreira, João F. He, Guanhua Qin, Shengchao School of Computing Teesside University United Kingdom HASLab. INESC TEC Universidade Do Minho Portugal State Key Lab. for Novel Software Technology Nanjing University China

ISBN: (纸本)9780769547510

Automated verification of operating system kernels is a challenging problem, partly due to the use of shared mutable data structures. In this paper, we show how we can automatically verify memory safety and functional correctness of the task scheduler component of the Free RTOS kernel using the verification system Hip Sleek. We show how some of Hip Sleek features like user-defined predicates and lemmas make the specifications highly expressive and the verification process viable. To the best of our knowledge, this is the first code-level verification of memory safety and functional correctness properties of the Free RTOS scheduler. The outcome of our experiment confirms that Hip Sleek can indeed be used to verify code that is used in production. Moreover, since the properties that we verify are quite general, we envisage that the same approach can be adopted to verify the scheduler of other operating systems. © 2012 IEEE.

关键词： Embedded systems

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Accurate Recommendation Approach of Psychological Consultation Information Based on User Portrait and TAG_SVD_CF

Research Square

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Research Square 2021年

作者： Zhang, De-Gan Liu, Zi-Xian Fu, Tian-Zheng Zhang, Xin Wen, Kai-Yan Liu, Bing Ministry of Education 300384 China Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology 300384 China

A hybrid recommendation algorithm of psychological counseling information based on user profile and item tag attribute with singular value decomposition （SVD） technology is developed. To solve the problem of data sparsity of the recommendation algorithm, the SVD technology is applied to collaborative filtering algorithm for optimizing the user item rating matrix. The recommendation algorithm includes two parts: generating medical user profile in accurate recommendation of medical information, and realizing the storage, query and update of user profile, where the index system of medical portrait was established from demographic attribute, interest label dimension and business social dimension. The performances of the developed algorithm are investigated by compared with the traditional cosine similarity and Pearson similarity. The results show that the proposed similarity has a lower mean absolute error and significantly improves the accuracy of the system. © 2021, CC BY.

关键词： User profile

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A new method for image fusion based on fuzzy neural network

A new method for image fusion based on fuzzy neural network

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International Conference on Modelling, Identification and Control (ICMIC)

作者： De-gan Zhang Yuan-yuan Wang Wei-wei Liu Xiao-li Zhang Tianjin Key Lab of Intelligent Computing & Novel software Technology Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology China

In pervasive computing paradigm, the image data obtained by a variety of multimedia, information equipment. In order to make use of these information reasonably and efficiently, a new method for image fusion based on fuzzy neural network has presented in this paper. It can fuse massive data from the multi-sensor image. Here, fuzzy neural network is a parallel information processing model, there are more adaptive and self-organization, and can accomplish the complexity of real-time computing and mass data retrieval, it demonstrate its unique superiority of image understanding, pattern recognition and the handling of incomplete information. The fuzzy neural network system developed by us can be used in multi-sensor image fusion. Based on our experiments, it has been proved that the fusion is fast, effective, and can meet the real-time requirements of pervasive computing.

关键词： Image resolution Annealing Weight measurement Adaptation model Gain measurement

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A Code Completion Approach Combining Pointer Network and Transformer-XL Network 19th

A Code Completion Approach Combining Pointer Network and Tr...

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19th EAI International Conference on Collaborative computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Zhang, Xiangping Liu, Jianxun Long, Teng Hu, Haize School of Computer Science and Engineering Hunan University of Science and Technology Hunan Xiangtan411100 China Hunan Key Lab. for Services Computing and Novel Software Technology Hunan University of Science and Technology Hunan Xiangtan411100 China

ISBN: (纸本)9783031545207

Code completion is an integral component of modern integrated development environments, as it not only facilitates the software development process but also enhances the quality of software products. By leveraging large-scale codes to learn the probability distribution among code token units, deep learning methods have demonstrated significant improvements in the accuracy of token unit recommendations. However, the effectiveness of code completion with deep learning techniques is hindered by information loss. To alleviate the above problem, we proposed a code language model which combines the pointer network and Transformer-XL network to overcome the limitations of existing approaches in code completion. The proposed model takes as input the original code fragment and its corresponding abstract syntax tree and leverages the Transformer-XL model as the basis model for capturing long-term dependencies. Furthermore, we integrate a pointer network as a local component to predict the out-of-vocabulary words. The proposed method is evaluated on real PY150 and JS150 datasets. The comparative experimental results demonstrate the effectiveness of our model in improving the accuracy of the code completion task at the token unit level. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Probability distributions

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Semi-supervised learning with local and global consistency by geodesic distance and sparse representation 1

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3rd Sino-Foreign-Interchange Workshop on intelligent Science and intelligent Data Engineering, IScIDE 2012

作者： Gui, Jie Zhao, Zhongqiu Hu, Rongxiang Jia, Wei Intelligent Computing Lab. Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei Anhui 230031 China State Key Laboratory for Novel Software Technology Nanjing University China College of Computer Science and Information Engineering Hefei University of Technology China Institue of Energy Safety Chinese Academy of Sciences Hefei Anhui 230031 China

ISBN: (数字)9783642366697

ISBN: (纸本)9783642366680

In many practical data mining applications, such as web categorization, key gene selection, etc., generally, unlabeled training examples are readily available, but labeled ones are fairly expensive to obtain. Therefore, in recent years, semi-supervised learning algorithms such as graph-based methods have attracted much attention. However, most of these traditional methods adopted a Gaussian function to calculate the edge weights of the graph. In this paper, a novel weight for semi-supervised graph-based methods is proposed. The new method adds the label information from problem into the target function, and adopts the geodesic distance rather than Euclidean distance as the measure of the difference between two data points when conducting the calculation. In addition, we also add class prior knowledge from problem into semi-supervised learning algorithm. Here we address the problem of learning with local and global consistency (LGC). It was found that the effect of class prior knowledge was probably different between under high label rate and low label rate. Furthermore, we integrate sparse representation (SR) in LGC algorithm. Experiments on a UCI data set show that our proposed method outperforms the original algorithms. © Springer-Verlag 2013.

关键词： Learning algorithms

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A Method of Concept Similarity Computation Based on Semantic Distance

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Procedia Engineering 2011年 15卷 3854-3859页

作者： Wenjie Li Qiuxiang Xia Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of TechnologyTianjin 300384China Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education Tianjin 300384China

Calculating the similarity between the concepts is the key in the process of the ontology mapping. Based on the analysis of the traditional method of calculating semantic similarity, a semantic distance-based concept similarity computation method is proposed. In order to keep the effectiveness and comprehensiveness of this method, the main factors which impact the semantic distance are considered fully, the factors of concept semantic contact ratio and depth differences between concepts nodes are also taken into account. By calculating test data, the experiment result shows that the method can calculate concepts similarity effectively.

关键词： ontology semantic distance concept semantic similarity

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