• Journal of Information Processing Systems
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• v.17 no.2
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• pp.411-425
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• 2021

In this paper, a vehicle recognition algorithm based on deep convolutional neural network and compression dictionary is proposed. Firstly, the network structure of fine vehicle recognition based on convolutional neural network is introduced. Then, a vehicle recognition system based on multi-scale pyramid convolutional neural network is constructed. The contribution of different networks to the recognition results is adjusted by the adaptive fusion method that adjusts the network according to the recognition accuracy of a single network. The proportion of output in the network output of the entire multiscale network. Then, the compressed dictionary learning and the data dimension reduction are carried out using the effective block structure method combined with very sparse random projection matrix, which solves the computational complexity caused by high-dimensional features and shortens the dictionary learning time. Finally, the sparse representation classification method is used to realize vehicle type recognition. The experimental results show that the detection effect of the proposed algorithm is stable in sunny, cloudy and rainy weather, and it has strong adaptability to typical application scenarios such as occlusion and blurring, with an average recognition rate of more than 95%.

• The Journal of Society for e-Business Studies
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• v.8 no.3
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• pp.37-52
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• 2003

ISO 13584 Parts Library (PLIB) standard is making its way into e-business as a norm for classifying products and their characteristics. PLIB is a multi-parts standard, and the Part 42: Methodology for structuring Parts families Provides the information model and design Principles for the data dictionary of parts library or e-catalog. If e-catalog systems are built using a data dictionary that is constructed based on PLIB dictionary data model, many different e-catalog systems can be easily integrated and interoperated. This paper studies the roles and requirements of the data dictionary in e-catalog, and applies the data model and design principles of PLIB Part 42 to construct a data dictionary from the viewpoint of ontology Based on the analysis results, we propose a data dictionary of die and mold parts, and implementat the B2B e-catalog system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1597-1605
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• 2015

Password authenticated key exchange (PAKE) is a protocol that a client stores its password to a server, authenticates itself using its password and shares a session key with the server. In multi-server PAKE, a client splits its password and stores them to several servers separately. Unless all the servers are compromised, client's password will not be disclosed in the multi-server setting. In attribute-based encryption (ABE), a sender encrypts a message M using a set of attributes and then a receiver decrypts it using the same set of attributes. In this paper, we introduce multi-server PAKE protocol that utilizes a set of attributes of ABE as a client's password. In the protocol, the client and servers do not need to create additional public/private key pairs because the password is used as a set of public keys. Also, the client and the servers exchange only one round-trip message per server. The protocol is secure against dictionary attacks. We prove our system is secure in a proposed threat model. Finally we show feasibility through evaluating the execution time of the protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2590-2606
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• 2017

Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.39-48
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• 2002

long with the rapid spread of the Internet, a new class of commercial applications which process transactions with respect to electronic dictionaries become popular Typical examples are Internet search engines. In this paper, we present a new approach to achieving high performance electronic dictionaries. Different from the conventional approach which use Trie data structures for the implementation of electronic dictionaries, our approach used multi-dimensional binary trees. In this paper, we present the implementation of our electronic dictionary ED-MBT(Electronic Dictionary based on Multidimensional Binary Tree). Exhaustive performance study is also presented to assess the performance impact of ED-MBT on the real world applications.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.37-44
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• 2000

In this paper, an efficient hardware architecture of Lempel-Ziv compressor for real time data compression is proposed. The accumulated shift operations in the Lempel-Ziv algorithm are the major problem, because many shift operations are needed to prepare a dictionary buffer and matching symbols. A new efficient architecture for the fast processing of Lempel-Ziv algorithm is presented in this paper. In this architecture, the optimization technique for dictionary size, a new comparing method of multi symbol and a rotational FIFO structure are used to control shift operations easily. For the functional verification, this architecture was modeled by C programming language, and its operation was verified by running on commercial DSP processor. Also, the design of overall architecture in VHDL was synthesized on commercial FPGA chip. The result of critical path analysis shows that this architecture runs well at the input bit rate of 256kbps with 33MHz clock frequency.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.608-620
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• 2021

Recent deep learning-based face super-resolution (FSR) works showed significant performances by utilizing facial prior knowledge such as facial landmark and dictionary that reflects structural or semantic characteristics of the human face. However, most of these methods require additional processing time and memory. To solve this issue, this paper propose an efficient FSR models using knowledge distillation techniques. The intermediate features of teacher network which contains dictionary information based on major face regions are transferred to the student through adversarial multi-scale features distillation. Experimental results show that the proposed model is superior to other SR methods, and its effectiveness compare to teacher model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5015-5038
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• 2018

In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.129-132
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• 2003

The metathesaurus(UMLS, 2003AA edition) supports multi language and includes 875, 233 concepts, 2, 146, 897 concept names. It is impossible for PubMed or NLM serve searching of the metatheaurus to retrieval using a query that is not to be text, a fault sentence structure or a part of concept name. That means the user notice correctly suitable medical words in order to get correct answer, otherwise she or he can't find information that they want to find I propose that the method of searching unified medical language system using automatic modified a query for problem that I mentioned. This method use dictionary that is standard for automation of modified query gauge similarity between query and dictionary using string comparison algorithm. And then, the tested term converse the form of metathesaurus for optimized result. For the evaluation of method, I select some query and I contrast NLM method that renewed Aug. 2003.

• Korean Journal of Construction Engineering and Management
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• v.8 no.5
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• pp.152-160
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• 2007

Recently, the government is very active to secure the financial resources by inducement of the private investment in fulfilling an extension of the SOC facilities. One of the reasons that the private investors hesitate to put money into the private finance projects, however, is the lack of knowledges about various risks to be possibly incurred during the project execution. This research was performed as one of the preparation works in order for a A engineering company to act as a prime contractor of the project management service in the private finance project, and finally developed the risk factor dictionary as a new concept to satisfy the requirement of a A company and overcome a limit of the existing risk checklists. Although the risk factor dictionary looks like the only simplified table to be the risk factors identified in three dimensions, the impacts and response strategies expressed in narrative and multi-items, and the responsible parties indicated, it has great meanings to get a lot of direct and indirect accomplishments over the simplified table during the development process.