• Management & Information Systems Review
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• v.33 no.4
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• pp.39-48
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• 2014

In order that a company may reduce expense, according to companies' income statement, the largest amount of money is set to total sales amount, and the next is the sales cost. The method of reducing the sales cost is the common and it is important to take down a unit price at the time of purchase, or to reduce inventory cost. In this research, the cost reduction model for logistics cost reduction is built using the real data of P company, and in order to verify the validity of a model, logistics cost is calculated through a simulation. A real logistics cost is compared with the logistics cost through logistics route rearrange of the proposal model. It will become an opportunity which analyzes the logistics expense of P company through this research, and can be solved in search of the problem of logistics system.

• Journal of Broadcast Engineering
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• v.7 no.1
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• pp.45-54
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• 2002

This paper proposes a video compression algorithm using characteristics of wavelet coefficients. The proposed algorithm can provide lowed bit rate and faster running time while guaranteeing the reconstructed image qualify by the human virtual system. In this approach, each video sequence is decomposed into a pyramid structure of subimages with various resolution to use multiresolution capability of discrete wavelet transform. Then similarities between two neighboring frames are obtained from a low-frequency subband which Includes an important information of an image and motion informations are extracted from the similarity criteria. Four legion selection filters are designed according to the similarity criteria and compression processes are carried out by encoding the coefficients In preservation legions and replacement regions of high-frequency subbands. Region selection filters classify the high-frequency subbands Into preservation regions and replacement regions based on the similarity criteria and the coefficients In replacement regions are replaced by that of a reference frame or reduced to zero according to block-based similarities between a reference frame and successive frames. Encoding is carried out by quantizing and arithmetic encoding the wavelet coefficients in preservation regions and replacement regions separately. A reference frame is updated at the bottom point If the curve of similarity rates looks like concave pattern. Simulation results show that the proposed algorithm provides high compression ratio with proper Image quality. It also outperforms the previous Milton's algorithm in an Image quality, compression ratio and running time, leading to compression ratio less than 0.2bpp. PSNR of 32 dB and running tome of 10ms for a standard video image of size 352${\times}$240 pixels.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.1-13
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• 2022

As the information and communication environment develops, the environment of military facilities is also development remarkably. In proportion to this, cyber threats are also increasing, and in particular, APT attacks, which are difficult to prevent with existing signature-based cyber defense systems, are frequently targeting military and national infrastructure. It is important to identify attack groups for appropriate response, but it is very difficult to identify them due to the nature of cyber attacks conducted in secret using methods such as anti-forensics. In the past, after an attack was detected, a security expert had to perform high-level analysis for a long time based on the large amount of evidence collected to get a clue about the attack group. To solve this problem, in this paper, we proposed an automation technique that can classify an attack group within a short time after detection. In case of APT attacks, compared to general cyber attacks, the number of attacks is small, there is not much known data, and it is designed to bypass signature-based cyber defense techniques. As an attack model, we used MITRE ATT&CK® which modeled many parts of cyber attacks. We design an impact score considering the versatility of the attack techniques and proposed a group similarity score based on this. Experimental results show that the proposed method classified the attack group with a 72.62% probability based on Top-5 accuracy.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.48-57
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• 2005

A lot of manufacturing knowledge and method have applied to increase manufacturing efficiency in industry field. DES(Discrete Event Simulation) is one of solution to deal with manufacturing problems in factory. Beginning of research, old maintenance system of KNR ( Korea National Railroad) and its technical problems are basically investigated. KNR has maintained railway vehicle with their own solution based on experience. Very advanced railway vehicles such as KTX (Korea Train Express) and TTX(Tilting Train Express) will be difficult to maintain with their old maintenance method. In order to apply knowledge of DES, maintenance field of railway must be considered. Imaginary maintenance machine are selected to variable of DES. Maintenance capability of each machine will be evaluated base on imaginary data from imaginary machine. The machine could be very expensive as well as difficult to replace. Target of research is minimization of number of machine in railway workshop. So basic knowledge of discrete event simulation is introduced. Then five essential stages of discrete event simulation are provided. Each maintenance case defined as event. Each event is discrete and simulated base on different case such as one maintenance line with one machine and one maintenance line with two machines in railway workshop. simple maintenance method, discrete event simulation, will be come out very powerful in complicate maintenance system and will be helpful to reduce maintenance cost as well as maintenance labor.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.34-42
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• 2006

As art analytic method to uncover interesting patterns hidden under a large volume of data, data mining research has been actively done so far in various fields. However, current state-of-the-arts in data mining research have several challenging problems such as being too ad-hoc. The existing techniques are mostly the ones designed for individual problems, so there is no unifying theory applicable for more general data mining problems. In this paper, we address the problem of classification, which is one of significant data mining tasks. Specifically, our objective is to evaluate radial basis function (RBF) model for classification tasks and investigate its usefulness. For evaluation, we analyze the popular Monk's problems which are well-known datasets in data mining research. First, we develop RBF models by using the representational capacity based learning algorithm, and then perform a comparative assessment of the results with other models generated by the existing techniques. Through a variety of experiments, it is empirically shown that the RBF model has not only the superior performance on the Monk's problems but also its modeling process can be controlled in a systematic way, so the RBF model with RC-based algorithm might be a good candidate to handle the current ad-hoc problem.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.9-17
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• 2020

In this paper, we proposed an SNS review analysis method based on deep learning for user tendency. The existing SNS review analysis method has a problem that does not reflect a variety of opinions on various interests because most are processed based on the highest weight. To solve this problem, the proposed method is to extract the user's personal tendency from the SNS review for food. It performs classification using the YOLOv3 model, and after performing a sentiment analysis through the BiLSTM model, it extracts various personal tendencies through a set algorithm. Experiments showed that the performance of Top-1 accuracy 88.61% and Top-5 90.13% for the YOLOv3 model, and 90.99% accuracy for the BiLSTM model. Also, it was shown that diversity of the individual tendencies in the SNS review classification through the heat map. In the future, it is expected to extract personal tendencies from various fields and be used for customized service or marketing.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.200-208
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• 2022

In this study, an automatic information collection system and geographic information construction algorithm for the transportation disadvantaged using electric mobility aids are implemented using an object recognition model. Recognizes objects that the disabled person encounters while moving, and acquires coordinate information. It provides an improved route selection map compared to the existing geographic information for the disabled. Data collection consists of a total of four layers including the HW layer. It collects image information and location information, transmits them to the server, recognizes, and extracts data necessary for geographic information generation through the process of classification. A driving experiment is conducted in an actual barrier-free zone, and during this process, it is confirmed how efficiently the algorithm for collecting actual data and generating geographic information is generated.The geographic information processing performance was confirmed to be 70.92 EA/s in the first round, 70.69 EA/s in the second round, and 70.98 EA/s in the third round, with an average of 70.86 EA/s in three experiments, and it took about 4 seconds to be reflected in the actual geographic information. From the experimental results, it was confirmed that the walking weak using electric mobility aids can drive safely using new geographic information provided faster than now.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.476-486
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• 2003

There is no explicit spelling change information in part-of-speech tagged corpora of Korean. It causes some difficulties in acquiring the data to study Korean morphology, i.e. automatically in constructing a dictionary for morphological analysis and systematically in collecting the phenomena of the spelling changes from the corpora. To solve this problem, this paper presents a method to recognize spelling changes between morphemes of a Korean word in tagged corpora, only using a string matching, without using a dictionary and phonological rules. This method not only has an ability to robustly recognize the spelling changes because it doesn't use any phonological rules, but also can be implemented with few cost. This method has been experimented with a large tagged corpus of Korean, and recognized the 100% of spelling changes in the corpus with accuracy.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.365-374
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• 2005

The B2B electronic product commerce needs intermediary system to provide an integrated interface for the parts libraries of multiple suppliers. However, it is difficult to automatically integrate the parts libraries because they are heterogeneous. Existing ontology-based approaches show a limited functionality of automated integration of information because Dey can not prevent ontologies from being modeled in different ways, so that the inter-ontology mappings to resolve the heterogeneity become complicated and arbitrary. In order to overcome such problems this paper proposes an ontology modeling framework for parts libraries based on the Guarino's theory of upper ontology. The framework provides knowledge modeling primitives which have explicit formal meanings and modeling principles based on ontological natures. Using the framework, ontology developers can model the knowledge of parts libraries systematically and consistently, so that the resulting ontologies become comparable and uniform and the ontology merging algorithm for the automated information integration can be easily developed.

• Journal of Korean Society of Transportation
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• v.24 no.4 s.90
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• pp.81-91
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• 2006

As public transportation is significant mode to make sustainable urban transportation system, the importance of Public transportation has grown gradually. Nowadays the central and local government make various policies which help to raise modal sp)it of public transportation. To understand previous public transportation Policies and make more efficient policies, it is important to know the current level of public transportation exactly. The main aim of this study is assess the competitiveness of public transportation in world major cities We select assessment indexes and have grouping use factor analysis. Then we have 8 clusters of cities by cluster analysis, Also, we analyze the relationship between public transportation characteristics and modal split.