• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.1080-1083
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• 2005

Can speak that DTD is meta data that define meaning of expressed data on XML document. Therefore, in case DTD information is damaged this information to base security of XML document dangerous. Not that attach digital signature on XML document at send-receive process of XML document in this research, proposed method to attach digital signature to DTD. As reading DTD file to end first, do parsing, and store abstracted element or attribute entitys in hash table. Read hash table and achieve message digest if parsing is ended. Compose and create digital signature with individual key after achievement. When sign digital, problem that create entirely other digest cost because do not examine about order that change at message digest process is happened. This solved by method to create DTD's digital signature using DOM that can embody tree structure for standard structure and document.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1851-1856
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• 2013

An XML is widely used for web services, such as SOAP(Simple Object Access Protocol) and REST (Representational State Transfer), and also de facto standard for representing data. Since the XML parser using DOM(Document Object Model) requires a preprocessing task creating a DOM-tree, and then storing it into memory, embedded systems with limited resources typically employ a streaming XML parser without preprocessing. In this paper, we propose a new architecture for the streaming XML parser using an APSearch(Adaptive Parallel Search) on FPGA(Field Programmable Gate Array). Compared to other approaches, the proposed APSearch parser dramatically reduces overhead on the software side and achieves about 2.55 and 2.96 times improvement in the time needed for an XML parsing. Therefore, our APSearch parser is suitable for systems to speed up XML parsing.

• Journal of KIISE:Databases
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• v.32 no.6
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• pp.650-661
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• 2005

As the Internet is growing, the use of XML which is a standard of semi-structured document is increasing. Therefore, there are on going works about integration and retrieval of XML documents. However, the basis of efficient integration and retrieval of documents is to cluster XML documents with similar structure. The conventional XML clustering approaches use the hierarchical clustering algorithm that produces the demanded number of clusters through repeated merge, but it have some problems that it is difficult to compute the similarity between XML documents and it costs much time to compare similarity repeatedly. In order to address this problem, we use clustering algorithm for transactional data that is scale for large size of data. In this paper we use common structures from XML documents that don't have DTD or schema. In order to use common structures of XML document, we extract representative structures by decomposing the structure from a tree model expressing the XML document, and we perform clustering with the extracted structure. Besides, we show efficiency of proposed method by comparing and analyzing with the previous method.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.5
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• pp.520-529
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• 2002

Though BIFS is a complex description language that represents MPEG-4 content as text or bit streams, most traditional MPEG-4 content authoring tools are developed for a BIFS expert. Before using these tools, many authors must invest much time and energy in acquiring knowledge of BIFS. In this paper, we suggest a new manner for saving these efforts. Our proposal supplies the convenient user interface of traditional multimedia authoring tools for MPEG-4 authors and interprets the authored information and transforms it into BIFS. In our user interface, the author generates the minimal authoring information requested for generating BIFS; the BIFS generation module then transforms the information into BIFS format using predefined BIFS construction rules. The resulting BIFS consists of the Scene Tree and the Object Descriptor and Route; they are used for constructing MP4 standard files by mixing with the Elementary Stream.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.150-167
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• 2009

XML has become the new standard for storing, exchanging, and publishing of data over both the internet and the ubiquitous data stream environment. As demand for efficiency in handling XML document grows, labeling scheme has become an important topic in data storage. Recently proposed labeling schemes reflect the dynamic XML environment, which itself provides motivation for the discovery of an efficient labeling scheme. However, previous proposed labeling schemes have several problems: 1) An insertion of a new node into the XML document triggers re-labeling of pre-existing nodes. 2) They need larger memory space to store total label. etc. In this paper, we introduce a new labeling scheme called a Circle Labeling Scheme. In CLS, XML documents are represented in a circular form, and efficient storage of labels is supported by the use of concepts Rotation Number and Parent Circle/Child Circle. The concept of Radius is applied to support inclusion of new nodes at arbitrary positions in the tree. This eliminates the need for re-labeling existing nodes and the need to increase label length, and mitigates conflict with existing labels. A detailed experimental study demonstrates efficiency of CLS.

• Current Research on Agriculture and Life Sciences
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• v.20
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• pp.77-82
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• 2002

This study was carried out in order to produce useful material for the forest multiple use and forest protection by physico-chemical soil analysis of studied area in Sokwang-ri Forest Genetic Resource Protection Forest which was divided into in standard plots include Tricholoma matsutake and Sarcodon aspratus production forest. The result of physico-chemical soil analysis represented as following. The soil type of T. matsutake production forest was Dry brown forest soil(B1), while on the other hand the soil type of S. aspratus production forest was Moderately moist brown forest soil(B3). Between T. matsutake and S. aspratus production forest did not result in significant changes in soil pH(5.22-5.60) and soil depth(47cm), but available phosphorus, carbon, and nitrogen contents were different results. CN ratio of the fairy ring of T. matsutake was quite lower than that in S. aspratus production forests, which indicated that T. matsutake production forest was built up in the relatively immature soils which contain little organic matter. Generally, it was predicted that Pinus densiflora for. erecta forest succeeded to deciduous tree forest in stable soil environments. To conserve these T. matsutake and S. aspratus production forest, the contents of available phosphorous and exchangeable cation should be increased by continuous soil environment management and it should be established the secondary growth forests of old aged Pinus densiflora for. erecta trees as soon as possible.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.959-974
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• 2020

High efficiency video coding (HEVC) employs quadtree coding tree unit (CTU) structure to improve its coding efficiency, but at the same time, it also requires a very high computational complexity due to its exhaustive search processes for an optimal coding unit (CU) partition. With the aim of solving the problem, a fast CU size decision optimal algorithm based on neighborhood prediction is presented for HEVC in this paper. The contribution of this paper lies in the fact that we successfully use the partition information of neighborhood CUs in different depth to quickly determine the optimal partition mode for the current CU by neighborhood prediction technology, which can save much computational complexity for HEVC with negligible RD-rate (rate-distortion rate) performance loss. Specifically, in our scheme, we use the partition information of left, up, and left-up CUs to quickly predict the optimal partition mode for the current CU by neighborhood prediction technology, as a result, our proposed algorithm can effectively solve the problem above by reducing many unnecessary prediction and partition operations for HEVC. The simulation results show that our proposed fast CU size decision algorithm based on neighborhood prediction in this paper can reduce about 19.0% coding time, and only increase 0.102% BD-rate (Bjontegaard delta rate) compared with the standard reference software of HM16.1, thus improving the coding performance of HEVC.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.1
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• pp.83-91
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• 2021

The increased turbidity in rivers during flood events has various effects on water environmental management, including drinking water supply systems. Thus, prediction of turbid water is essential for water environmental management. Recently, various advanced machine learning algorithms have been increasingly used in water environmental management. Ensemble machine learning algorithms such as random forest (RF) and gradient boosting decision tree (GBDT) are some of the most popular machine learning algorithms used for water environmental management, along with deep learning algorithms such as recurrent neural networks. In this study GBDT, an ensemble machine learning algorithm, and gated recurrent unit (GRU), a recurrent neural networks algorithm, are used for model development to predict turbidity in a river. The observation frequencies of input data used for the model were 2, 4, 8, 24, 48, 120 and 168 h. The root-mean-square error-observations standard deviation ratio (RSR) of GRU and GBDT ranges between 0.182~0.766 and 0.400~0.683, respectively. Both models show similar prediction accuracy with RSR of 0.682 for GRU and 0.683 for GBDT. The GRU shows better prediction accuracy when the observation frequency is relatively short (i.e., 2, 4, and 8 h) where GBDT shows better prediction accuracy when the observation frequency is relatively long (i.e. 48, 120, 160 h). The results suggest that the characteristics of input data should be considered to develop an appropriate model to predict turbidity.

• Journal of Creative Information Culture
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• v.7 no.3
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• pp.157-165
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• 2021

As the use of various application services utilizing Web and IoT and the need for large amounts of data management expand accordingly, the importance of efficient data expression and exchange scheme and data query processing is increasing. JSON, characterized by its simplicity, is being used in various fields as a format for data exchange and data storage instead of XML, which is a standard data expression and exchange language on the Web. This means that it is important to develop indexing and query processing techniques to effectively access and search large amounts of data expressed in JSON. Therefore, in this paper, we modeled JSON data with a hierarchical structure in a tree form, and proposed indexing and query processing using the path concept. In particular, we designed an index structure using a suffix array widely used in text search and introduced simple and complex path-based JSON data query processing methods.

• Physical Therapy Korea
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• v.28 no.2
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• pp.123-131
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• 2021

Background: Only 2% of falls in older adults result in serious injuries (i.e., hip fracture). Therefore, it is important to differentiate injurious versus non-injurious falls, which is critical to develop effective interventions for injury prevention. Objects: The purpose of this study was to a. extract the best features of surface electromyography (sEMG) for classification of injurious falls, and b. find a best model provided by data mining techniques using the extracted features. Methods: Twenty young adults self-initiated falls and landed sideways. Falling trials were consisted of three initial fall directions (forward, sideways, or backward) and three knee positions at the time of hip impact (the impacting-side knee contacted the other knee ("knee together") or the mat ("knee on mat"), or neither the other knee nor the mat was contacted by the impacting-side knee ("free knee"). Falls involved "backward initial fall direction" or "free knee" were defined as "injurious falls" as suggested from previous studies. Nine features were extracted from sEMG signals of four hip muscles during a fall, including integral of absolute value (IAV), Wilson amplitude (WAMP), zero crossing (ZC), number of turns (NT), mean of amplitude (MA), root mean square (RMS), average amplitude change (AAC), difference absolute standard deviation value (DASDV). The decision tree and support vector machine (SVM) were used to classify the injurious falls. Results: For the initial fall direction, accuracy of the best model (SVM with a DASDV) was 48%. For the knee position, accuracy of the best model (SVM with an AAC) was 49%. Furthermore, there was no model that has sensitivity and specificity of 80% or greater. Conclusion: Our results suggest that the classification model built upon the sEMG features of the four hip muscles are not effective to classify injurious falls. Future studies should consider other data mining techniques with different muscles.