• Journal of KIISE:Databases
• /
• v.28 no.3
• /
• pp.279-300
• /
• 2001

Data mining plays an important role in knowledge discovery process and usually various existing algorithms are selected for the specific purpose of the mining. Currently, data mining techniques are actively to the statistics, business, electronic commerce, biology, and medical area and currently numerous algorithms are being researched and developed for these applications. However, in a long run, only a few algorithms, which are well-suited to specific applications with excellent performance in large database, will survive. So it is reasonable to focus our effort on those selected algorithms in the future. This paper classifies about 30 existing algorithms into 7 categories - association rule, clustering, neural network, decision tree, genetic algorithm, memory-based reasoning, and bayesian network. First of all, this work analyzes systematic hierarchy and characteristics of algorithms and we present 14 criteria for classifying the algorithms and the results based on this criteria. Finally, we propose the best algorithms among some comparable algorithms with different features and performances. The result of this paper can be used as a guideline for data mining researches as well as field applications of data mining.

• The Journal of Korean Medicine
• /
• v.44 no.2
• /
• pp.106-118
• /
• 2023

Objectives: Network pharmacology is a method of constructing and analyzing a drug-compound-target network to predict potential efficacy and mechanisms related to drug targets. In that large-scale analysis can be performed in a short time, it is considered a suitable tool to explore the function and role of herbal medicine. Thus, we investigated the potential functions and pathways of Chongmyunggongjin-dan (CMGJD) on Alzheimer's disease (AD) via network pharmacology analysis. Methods: Using public databases and PubChem database, compounds of CMGJD and their target genes were collected. The putative target genes of CMGJD and known target genes of AD were compared and found the correlation. Then, the network was constructed using Cytoscape 3.9.1. and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results: The result showed that total 104 compounds and 1157 related genes were gathered from CMGJD. The network consisted of 1157nodes and 10034 edges. 859 genes were interacted with AD gene set, suggesting that the effects of CMGJD are closely related to AD. Target genes of CMGJD are considerably associated with various pathways including 'Positive regulation of chemokine production', 'Cellular response to toxic substance', 'Arachidonic acid metabolic process', 'PI3K-Akt signaling pathway', 'Metabolic pathways', 'IL-17 signaling pathway' and 'Neuroactive ligand-receptor interaction'. Conclusion: Through a network pharmacological method, CMGJD was predicted to have high relevance with AD by regulating inflammation. This study could be used as a basis for effects of CMGJD on AD.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.3C
• /
• pp.115-125
• /
• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• Journal of KIISE:Information Networking
• /
• v.32 no.3
• /
• pp.279-290
• /
• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.

• (The) Research of the performance art and culture
• /
• no.40
• /
• pp.193-222
• /
• 2020

In this study, the development of traditional contents is to be enabled to succeed the values of the heritage on the song sang during dry-field farming of Bongpyeong Memil-dorikkaejil-sori. In addition, the identity on the heritage of songs sang during farming were diagnosed, and their value in context with the history and the value as the community for succession are emphasized as the value of cultural asset to expand the discussion up to the level of traditional cultural industry works. In the Bongpyeong Memil-dorikkaejil-sori, the intrinsic artistic value, the excellence of value as the educational experience, factor for overcoming the extinction of farming songs, and the promotion direction of the storytelling on buckwheat were provided. This is breaking from the formalization and being old-fashioned on the Bongpyeong Memil-dorikkaejil-sori to focus on the symbolization of the agricultural heritage in the modern context, habituating and spreading the gene of slash-and-burn field (hwajeon or budaeki). In terms of methodology on awareness, historicity or creativity, alternative method on the folk songs in labor was provided by having critical mind on the Bongpyeong Memil-dorikkaejil-sori and buckwheat songs. By reviewing the field contextualization of designating the intangible cultural asset, suggestions were made on activating the succession, and even the method of symbolic registration on the heritage of buckwheat farming was mentioned. Heritage on agricultural culture that can represent Pyeongchang and Gangwon must be discovered to be made into a brand. In addition, the uniqueness in the Madang 'Song Madaengi Traditional Music' must be found to apply as the brand on the point in which the people around the world can have consensus for utilization. As the farming song, rediscovery of the Bongpyeong Memil-dorikkaejil-sori is required to create the sustainable status as the multi-purpose cultural contents and provide the network of professionals for activating the folk songs to enable the opportunity of qualitative substantiality and spread instead of quantitative growth. In addition, festivals for each region, especially the festival for Pyeongchang area must be utilized centrally on the development of farming songs to organize the storytelling actively.