• Information Systems Review
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• v.10 no.2
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• pp.195-209
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• 2008

Customers' needs change every moment. Profitability of stores can't be increased anymore with an existing standardized chain store management. Accordingly, a personalized store management tool needs through prediction of customers' preference. In this study, we propose a recommending procedure using dynamic customers' preference by analyzing the transaction database. We utilize self-organizing map algorithm and association rule mining which are applied to cluster the chain stores and explore purchase sequence of customers. We demonstrate that the proposed methodology makes an effect on recommendation of products in the market which is characterized by a fast fashion and a short product life cycle.

• Journal of Communications and Networks
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• v.7 no.2
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• pp.144-156
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• 2005

Video streaming over wireless networks is challenging due to node mobility and high channel error rate. In this paper, we propose a multi-source video streaming (MUVIS) system to support high quality video streaming service over IEEE 802.1l-based wireless networks. We begin by collocating a streaming proxy with the wireless access point to help leverage both the media server and peers in the WLAN. By tracking the peer mobility patterns and performing content discovery among peers, we construct a multi-source sender group and stream video using a rate-distortion optimized scheme. We formulate such a multi-source streaming scenario as a combinatorial packet scheduling problem and introduce the concept of asynchronous clocks to decouple the problem into three steps. First, we decide the membership of the multisource sender group based on the mobility pattern tracking, available video content in each peer and the bandwidth each peer allocates to the multi-source streaming service. Then, we select one sender from the sender group in each optimization instance using asynchronous clocks. Finally, we apply the point-to-point rate-distortion optimization framework between the selected sender-receiver pair. In addition, we implement two different caching strategies, simple caching simple fetching (SCSF) and distortion minimized smart caching (DMSC), in the proxy to investigate the effect of caching on the streaming performance. To design more realistic simulation models, we use the empirical results from corporate wireless networks to generate node mobility. Simulation results show that our proposed multi-source streaming scheme has better performance than the traditional server-only streaming scheme and that proxy-based caching can potentially improve video streaming performance.

• Journal of Life Science
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• v.11 no.6
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• pp.509-516
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• 2001

Enzymes and non-enzymatic antioxidants are involved in defense of oxgen free radical intermediates in all aerobic cells. The non -enzymatic antioxidants and antioxidant enzyme from the extracts of Solanum nigrum L. known to be anticancer medicinal plant were examined in other to utilize the discovery in natural products as cancer chem-opereventive agents. The DPPH(1,1-diphenyl-2-picryl-hydrazyl) free radical scavening activity on plant position of Solanum nigrum L. was the highest in root, with stem, whole plant, seed, leaf and flower, at higher activities respectively. In extraction methods, the DPPH free radical scavenging activity by circulating extraction with 80 % MeOH. The DPPH activity of L6 fraction by LH-20 column chromatography showed about 6.7 times higher than that of ethyl acetate-fraction. These were identified as phenolic compounds such as 2-6-methano-3-benzazocin-11-ol, 2[1H]-phyidinethione and 2-hydroxy -5-methyl-benzaldehyde. Peroxidase(POD) and superoxide dismutase(SOD) activities of stem and root were higher than that of other plant positions and those of plant positions according to growing stage were the highest in 60 days after seeding. The numbers of isozyme pattern of POD and SOD showed 10 hands and 5 bands, respectively, especially, 8 bands of POD and 3 bands of SOC showed a difference according to plant positions.

• Journal of Physiology & Pathology in Korean Medicine
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• v.31 no.4
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• pp.213-219
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• 2017

Atopic dermatitis (AD) is a common skin disease characterized by chronic and relapsing inflammatory dermatitis with immunological disturbances. Spleen deficiency (脾虛) is one of the major causes of AD, so development of animal model is required for AD research that reflects the pattern identification. The groups that we have used in this study included Senna folium extracts (SFE), 2,4-dinitrochlorobenzene (DNCB), and normal mice. Therefore, the present study was developed to atopic dermatitis mouse model with spleen deficiency in 2,4-dinitrochlorobenzene (DNCB) and senna leaves extracts induced AD in NC/Nga mice. The results demonstrated that senna leaves extract treatment significantly increased the dermatitis clinical score and epidermal thickness in AD-like skin lesions. We also proved beyond doubt that there was occurrence of erythema and skin moisture indices in the senna leaves extract groups. Further, we also found that the level of serum immunoglobulin E (IgE) in the senna leaves extract-treated group was increased. The amount of IL-4, IL-13, $TNF-{\alpha}$ and $TGF-{\beta}$ mRNA determined by real-time PCR was increased remarkably when senna leaves extract groups were treated on dorsal skin. Senna leaves extract groups significantly promoted the number of CD11B+/Gr-1 cell in skin, as well as the number of CD4+/CD8+ cell in dorsal skin compared with control. The review summarizes recent process in our understanding of the immunopathophysiology of spleen deficiency AD and the implications for spleen deficiency mouse models of AD on drug discovery from medical plants.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.121-128
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• 2010

Spatial data mining has been developed to support spatial association knowledge between spatial features or its non-spatial attributes for an application areas. At the present time, a number of researchers attempt to the data mining techniques apply to the several analysis areas, for examples, civil engineering, environmental, agricultural areas. Despite the efforts that, until such time as not existed practical systems for the gCRMDMs. gCRMDMs is merged with very large spatial database and CRM information system. Also, it is discovery the association rule for the predictions of customer's shopping pattern informations in a huge database consisted with spatial and non-spatial dataset. For this goal, gCRMDMs need spatial data mining techniques. But, nowadays, in a most case not exist utilizable model for the gCRMDMs. Therefore, in this paper, we proposed a practical gCRMDMs model to support a customer, store, street, building and geographical suited to the trade area.

• Journal of National Security and Military Science
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• s.8
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• pp.271-309
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• 2010

The main theme of this study is about North Korea's contemporary military strategy which remained a blind spot in the 21st century. Indeed, Pyongyang's contemporary military strategy is evolved from the logic of War. On the basis of this logic, this study examined North Korea's contemporary military strategy with three analytical frameworks. The first is the discovery of Clausewitz's dictums and application of the Trinitarian analysis on the Korean cases. During the course of applying Clausewitzian main dictum--War as continuation of politics, the methodological analysis on war played a important role generalizing the pattern and matrix of North Korea's strategic thinking and military strategy. In particular, Clausewitz's Trinitarian framework on war -Government (reason), Army (chance), People (passion)- was a universal framework to scrutinize the North Korean missile and nuclear strategy. The second is about the matrix of North Korea's military strategy, The study suggested the genealogical feature of Pyongyang's military strategy. In principle, the dictum of 'Military-First Politics' 1S the combination of the political philosophy, Chuch'e (self-reliance) of Kim Il Sung and Kin Jong Il reflected in the military readiness. As a result this analysis was able to equate Clausewitz's dictums to explain Pyongyang's idea of the nature of war in that North Korea's military strategy is the central instrument of delivery to achieve political objectives. The third is about the theoretical encounter of 'Clausewitz's Wonderful Trinity' and 'Remarkable Trinity on North Korea's contemporary strategy'. On the basis, three elements are connected to one of three groups in society; the people, the military, and the government. In order to apply the Clausewitz's Trinitarian analysis into Kim Jong Il's 'Military-First' strategy, two case studies (Missile and Nuclear strategy) were examined. The finding of this study is that Clausewitzian dictum in the 19th century is still valid in the 21st century as it provided plausible theoretical framework to explain the North Korean contemporary military strategy with a reminder that the nature and logic of war are fixed in the socially constructed state.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.499-508
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• 2015

High utility itemset(HUI) mining refers to the discovery of itemsets with high utilities which are not less than a user-specified minimum utility threshold, by considering both the quantities and weight factors of items in a transaction database. Recently the utility-list based HUI mining algorithms have been proposed to avoid numerous candidate itemsets and the algorithms need the costly join operations. In this paper, we propose a new HUI mining algorithm, using the utility-list with additional attributes of transaction utility and common utility of itemsets. The new algorithm decreases the number of join operations and efficiently prunes the search space. Experimental results on both synthetic and real datasets show that the proposed algorithm outperforms other recent algorithms in runtime, especially when datasets are dense or contain many long transactions.

• Genomics & Informatics
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• v.13 no.2
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• pp.45-52
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• 2015

Acute myeloid leukemia is a well characterized blood cancer in which the unnatural growth of immature white blood cell takes place, where several genes transcription is regulated by the micro RNAs (miRNAs). Argonaute (AGO) protein is a protein family that binds to the miRNAs and mRNA complex where a strong binding affinity is crucial for its RNA silencing function. By understanding pattern recognition between the miRNAs-mRNA complex and its binding affinity with AGO protein, one can decipher the regulation of a particular gene and develop suitable siRNA for the same in disease condition. In the current work, HOXA9 gene has been selected from literature, whose deregulation is well-established in acute myeloid leukemia. Four miRNAs (mir-145, mir-126, let-7a, and mir-196b) have been selected to target mRNA of HOXA9 (NCBI accession No. NM_152739.3). The binding interaction between mRNAs and mRNA of HOXA9 gene was studied computationally. From result, it was observed mir-145 has highest affinity for HOXA9 gene. Furthermore, the interaction between miRNAs-mRNA duplex of all chosen miRNAs are docked with AGO protein (PDB ID: 3F73, chain A) to study their interaction at molecular level through an in silico approach. The residual interaction and hydrogen bonding are inspected in Discovery Studio 3.5 suites. The current investigation throws light on understanding of AGO-assisted miRNA based gene silencing mechanism in HOXA9 gene associated in acute myeloid leukemia computationally.

• Journal of Animal Science and Technology
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• v.56 no.7
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• pp.23.1-23.7
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• 2014

Background: Scanning of the genome for selection signatures between breeds may play important role in understanding the underlie causes for observable phenotypic variations. The discovery of high density single nucleotide polymorphisms (SNPs) provide a useful starting point to perform genome-wide scan in pig populations in order to identify loci/candidate genes underlie phenotypic variation in pig breeds and facilitate genetic improvement programs. However, prior to this study genomic region under selection in commercially selected Berkshire and Korean native pig breeds has never been detected using high density SNP markers. To this end, we have genotyped 45 animals using Porcine SNP60 chip to detect selection signatures in the genome of the two breeds by using the $F_{ST}$ approach. Results: In the comparison of Berkshire and KNP breeds using the FDIST approach, a total of 1108 outlier loci (3.48%) were significantly different from zero at 99% confidence level with 870 of the outlier SNPs displaying high level of genetic differentiation ($F_{ST}{\geq}0.490$). The identified candidate genes were involved in a wide array of biological processes and molecular functions. Results revealed that 19 candidate genes were enriched in phosphate metabolism (GO: 0006796; ADCK1, ACYP1, CAMK2D, CDK13, CDK13, ERN1, GALK2, INPP1; MAK, MAP2K5, MAP3K1, MAPK14, P14KB, PIK3C3, PRKC1, PTPRK, RNASEL, THBS1, BRAF, VRK1). We have identified a set of candidate genes under selection and have known to be involved in growth, size and pork quality (CART, AGL, CF7L2, MAP2K5, DLK1, GLI3, CA3 and MC3R), ear morphology and size (HMGA2 and SOX5) stress response (ATF2, MSRB3, TMTC3 and SCAF8) and immune response (HCST and RYR1). Conclusions: Some of the genes may be used to facilitate genetic improvement programs. Our results also provide insights for better understanding of the process and influence of breed development on the pattern of genetic variations.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.179-186
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• 2008

The converge of location-aware devices, GIS functionalities and the increasing accuracy and availability of positioning technologies pave the way to a range of new types of location-based services. The field of spatiotemporal data mining where relationships are defined by spatial and temporal aspect of data is encountering big challenges since the increased search space of knowledge. Therefore, we aim to propose algorithms for mining spatiotemporal patterns in mobile environment in this paper. Moving patterns are generated utilizing two algorithms called All_MOP and Max_MOP. The first one mines all frequent patterns and the other discovers only maximal frequent patterns. Our proposed approach is able to reduce consuming time through comparison with DFS_MINE algorithm. In addition, our approach is applicable to location-based services such as tourist service, traffic service, and so on.