• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.27-32
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• 2004

A XML Document has a structure which may be irregular The irregular document structure is difficult for users to know exactly. In this paper, we propose the XML document model and the structure retrieval method for efficient management and structure retrieval of XML documents. So we use fixed-sized LETID having the information of element, describe the structured information retrieval algorithm for parent and child element to represent the structured information of XML documents. Using this method, we represent the structured information of XML document efficiently. We can directly access to specific clement by simple operation, and process various queries. We expect the method to support various structured retrieval of specific element such as parent, child. and sibling elements.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.51-54
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• 2005

This paper proposes an index structure which is used to process X-Path on S-XML data. There are many previous index structures based on tree structure for X-Path processing. Because of general tree index's top-down query fashion, the unnecessary node traversal makes heavy access and decreases the query processing performance. And both of the two query types for X-Path called single-path query and branching query need to be supported in proposed index structure. This method uses a combination of path summary and the node indexing. First, it manages hashing on hierarchy elements which are presented in tag in S-XML. Second, array blocks named path summary array is created in each node of hashing to store the path information. The X-Path processing finds the tag element using hashing and checks array blocks in each node to determine the path of query's result. Based on this structure, it supports both single-path query and branching path query and improves the X-Path processing performance.

• The Korean Journal of Community Living Science
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• v.28 no.2
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• pp.191-201
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• 2017

This study compared and analyzed the structures of cooking recipes in order to identify the overall cooking method and develop an efficient method for analyzing cooking recipes. We present procedural texts using a flow graph, which can be referred to as a recipe tree, to represent cooking recipes and the database. A total of 110 kimchi jjigae recipes were identified and classified as 'portion', 'kinds of ingredients', and 'number of cooking deployment'. Recipes for two persons were the most common (43.6%), and 7-13 kinds of ingredients accounted for 50% of kimchi jjigae recipes. Kimchi presented the highest frequency at 78 cases, and pork showed the high frequency at 30 cases. To identify cooking deployment, step 6 was the highest, followed by step 5 (17.3%), step 7 (17.3%), step 4 (11.8%), and step 3 (9.1%). When analyzing the frequency of the relationship between ingredients and action in a recipe expression, Food (F) and Action by the chef (Ac) showed the highest rates at 11.29 and 12.30, respectively, in the cooking process. For frequencies of dependency relation expression in recipes, d-obj (direct object) was the highest at 13.56. The proposed method provides users more efficient and easier access to recipes suitable for their cooking skills.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.422-433
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• 2015

In this paper, we demonstrate inter-layer prediction tools for scalable video coders. The proposed scalable coder is designed to support not only spatial, quality and temporal scalabilities, but also view scalability. In addition, we propose quad-tree inter-layer prediction tools to improve coding efficiency at enhancement layers. The proposed inter-layer prediction tools generate texture prediction signal with exploiting texture, syntaxes, and residual information from a reference layer. Furthermore, the tools can be used with inter and intra prediction blocks within a large coding unit. The proposed framework guarantees the rate distortion performance for a base layer because it does not have any compulsion such as constraint intra prediction. According to experiments, the framework supports the spatial scalable functionality with about 18.6%, 18.5% and 25.2% overhead bits against to the single layer coding. The proposed inter-layer prediction tool in multi-loop decoding design framework enables to achieve coding gains of 14.0%, 5.1%, and 12.1% in BD-Bitrate at the enhancement layer, compared to a single layer HEVC for all-intra, low-delay, and random access cases, respectively. For the single-loop decoding design, the proposed quad-tree inter-layer prediction can achieve 14.0%, 3.7%, and 9.8% bit saving.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.31-33
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• 2005

GPS및 PDA의 발달로 인해서 위치 기반 서비스(LBS), 차량항법장치(CNS), 지리정보시스템(GIS)등 공간 데이터를 다루는 응용프로그램들이 급속하게 보급되었다. 이러한 응용프로그램은 높이 균등 색인 기법을 사용하여 원하는 데이터에 대한 색인을 제공하였다. 그러나 모든 공간 객체는 서로 상이한 접근 빈도를 가지고 있음에도 불구하고 기존의 공간색인 기법은 접근 빈도를 고려하지 못하는 단점을 가지고 있었다. 또한 기존의 빈도수만을 고려한 공간 객체의 색인 방법은 접근 빈도에 따른 편향성(skewed)은 제공하지만 공간 객체에 대한 지역성을 반영하지 못한다. 본 논문에서는 밀집되어 있는 공간 객체의 접근 빈도를 반영해서 편향된 색인 트리를 생성하는 기법을 제안한다. 이형 클러스터링으로 분포되어 있는 전체 영역에 대해서 Zahn의 클러스터링 알고리즘을 변형시켜서 다단계 세부영역을 구분한다. 이렇게 구간된 세부영역에 대해서 거리적 인접성과 접근 빈도수의 합을 이용해서 색인 트리를 생성한다. 다단계로 구성된 전체영역에 대해서 하향식 방식으로 편향된 색인 트리를 생성함으로써, 접근 빈도가 높은 공간 객체에 대해서 빠른 탐색이 가능하게 한다.

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.147-158
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• 2021

Versatile Video Coding (VVC) is the latest video coding standard developed by Joint Video Exploration Team (JVET). In VVC, the quadtree plus multi-type tree (QT+MTT) structure of coding unit (CU) partition is adopted, and its computational complexity is considerably high due to the brute-force search for recursive rate-distortion (RD) optimization. In this paper, we aim to reduce the time complexity of inter-picture prediction mode since the inter prediction accounts for a large portion of the total encoding time. The problem can be defined as classifying the split mode of each CU. To classify the split mode effectively, a novel convolutional neural network (CNN) called multi-level tree (MLT-CNN) architecture is introduced. For boosting classification performance, we utilize additional information including inter-picture information while training the CNN. The overall algorithm including the MLT-CNN inference process is implemented on VVC Test Model (VTM) 11.0. The CUs of size 128×128 can be the inputs of the CNN. The sequences are encoded at the random access (RA) configuration with five QP values {22, 27, 32, 37, 42}. The experimental results show that the proposed algorithm can reduce the computational complexity by 11.53% on average, and 26.14% for the maximum with an average 1.01% of the increase in Bjøntegaard delta bit rate (BDBR). Especially, the proposed method shows higher performance on the sequences of the A and B classes, reducing 9.81%~26.14% of encoding time with 0.95%~3.28% of the BDBR increase.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.32-42
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• 2023

There are serious problems worldwide, such as a pandemic due to an unprecedented infection caused by COVID-19. On previous approaches, they invented medical vaccines and preemptive testing tools for medical engineering. However, it is difficult to access poor medical systems and medical institutions due to disparities between countries and regions. In advanced nations, the damage was even greater due to high medical and examination costs because they did not go to the hospital. Therefore, from a software engineering-based perspective, we propose a learning model for determining coronavirus infection through symptom data-based software prediction models and tools. After a comparative analysis of various models (decision tree, Naive Bayes, KNN, multi-perceptron neural network), we decide to choose an appropriate decision tree model. Due to a lack of data, additional survey data and overseas symptom data are applied and built into the judgment model. To protect from thiswe also adapt human normalization approach with traditional Korean medicin approach. We expect to be possible to determine coronavirus, flu, allergy, and cold without medical examination and diagnosis tools through data collection and analysis by applying decision trees.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1483-1495
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• 2007

Thanks to IEEE 802.11 technique, accessing Internet through a wireless LAN(Local Area Network) is possible in the most of the places including university campuses, shopping malls, offices, hospitals, stations, and so on. Most of the APs(access points) for wireless LAN are supporting 2.4 GHz band 802.11b and 802.11g protocols. This paper is introducing a C# library function which can be used to read RSSIs(Received Signal Strength Indicator) from APs. An LBS(Location Based Service) estimates the current location of the user and provides useful user's location-based services such as navigation, points of interest, and so on. Therefore, indoor, LBS is very desirable. However, an indoor LBS cannot be realized unless indoor position ing is possible. For indoor positioning, techniques of using infrared, ultrasound, signal strength of UDP packet have been proposed. One of the disadvantages of these techniques is that they require special equipments dedicated for positioning. On the other hand, wireless LAN-based indoor positioning does not require any special equipments and more economical. A wireless LAN-based positioning cannot be realized without reading RSSIs from APs. Therefore, our C# library function will be widely used in the field of indoor positioning. In addition to providing a C# library function of reading RSSI, this paper introduces implementation of indoor positioning modules making use of the library function. The methods used in the implementation are K-NN(K Nearest Neighbors), Bayesian and trilateration. K-NN and Bayesian are kind of fingerprinting method. A fingerprint method consists of off-line phase and realtime phase. The process time of realtime phase must be fast. This paper proposes a decision tree method in order to improve the process time of realtime phase. Experimental results of comparing performances of these methods are also discussed.

• The Journal of the Acoustical Society of Korea
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• v.32 no.1
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• pp.86-94
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• 2013

In this paper, we propose a network coding scheme that is one of the most promising techniques for overcoming transmission errors in underwater acoustic communications. It is assumed that the proposed scheme operates in a Code Division Multiple Access (CDMA) network where multiple sensor nodes share the underwater acoustic channel in both the frequency and the time domains by means of orthogonal codes. The network topology deploys multi-hop transmission with relaying between multiple source nodes and one destination node via multiple relay nodes. The proposed scheme is evaluated in terms of the successful packet delivery ratio of end-to-end transactions under varying packet loss rates. A computer simulation shows that the successful delivery ratio is maintained at over 95% even when the packet loss rate reaches 50%.