• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.1-23
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• 2021

This study introduces novel research using Practice Context Models supported by Knowledge Networks and Percolation Theory with the aim to contribute to knowledge management in Proof-of-Concept (PoC) activities. The authors envision this proposal as a potential instrument to identify network structures based on a percolation (propagation) threshold and to analyze the importance of nodes (e.g., practitioners, practices, competencies, movements, and scenarios) during the percolation of knowledge in PoC activities. After thirty months immersed in the natural PoC habitat, acting as observers and practitioners, and supported by an ethnographic exercise and a designer-research mindset, the authors identified the production of meaning in PoC activities occurring in a hermeneutic circle characterized by the presence of several knowledge networks; thus, discovering the 'natural knowledge' in PoC as a spectrum of cognitive development spread throughout its network, as each node could produce and disseminate certain knowledge that flows and influences other nodes. Therefore, this research presents the use of Practice Context Models 'connected' to Knowledge Networks and Percolation Theory as a potential and feasible proposal to be built using the attribution of values (weights) to the nodes (e.g., practitioners, practices, competencies, movements, scenarios, and also knowledge) in the context of PoC with the aim to allow the players (e.g., PoC practitioners) to have more flexibility in building alliances with other players (new nodes); that is, focusing on those nodes with higher value (focus on quality) in collaboration networks, i.e., alliances (connections) with the aim to contribute to knowledge management in the context of PoC.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.417-430
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• 2024

As modern technology advances and the proliferation of the internet continues, cyber threats are also on the rise. To effectively counter these threats, the importance of utilizing Cyber Threat Intelligence (CTI) is becoming increasingly prominent. CTI provides information on new threats based on data from past cyber incidents, but the complexity of data and changing attack patterns present significant analytical challenges. To address these issues, this study aims to utilize graph data that can comprehensively represent multidimensional relationships. Specifically, the study constructs a heterogeneous graph based on malware data, and uses the metapath2vec node embedding technique to more effectively identify cyber attack groups. By analyzing the impact of incorporating topology information into traditional malware data, this research suggests new practical applications in the field of cyber security and contributes to overcoming the limitations of CTI analysis.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• Tuberculosis and Respiratory Diseases
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• v.45 no.4
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• pp.776-784
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• 1998

Background: The cyclin D1 gene is one of the most frequently amplified chromosomal regions(11q13) in human carcinomas. In laryngeal and head and neck carcinomas, its overexpression has been shown to be associated with advanced local invasion and presence of lymph node metastases. Cyclin D1 may therefore playa key role in cell growth regulation and tumorigenesis. Lung cancer is a worldwide problem and in many contries it is the most lethal malignancy. As relapse is frequent after resection of early stage non-small cell lung cancer, there is an urgent need to define prognostic factors. Purpose: This study was undertaken to evaluate the prognostic value of the cyclin D1, that is one the G1 cyclins which control cell cycle progression by allowing G1 to S phase transition, on the patients in radically resected non-small cell lung cancer. Method: Total 81 cases of formalin-fixed paraffin-embedded blocks from resected primary non-small cell lung cancer from January 1, 1983 to July 31, 1995 at Hanyang University Hospital were available for both clinical follow-up and immunohistochemical staining using monoclonal antibodies for cyclin D1. Results : The histologic classification of the tumor was based on WHO criteria, and the specimens included 45 squamous cell carcinomas, 25 adenocarcinomas and 11 large cell carcinomas. Cyclin D1 overexpression was noted in 26 cases of 81 cases tested (30.9%). Cyclin D1 expression was not significantly associated with cell types of the tumor, pathological staging and the size of the tumor. But cyclin D1 overexpression was significantly correlated with positive lymph node metastasis(p=0.035). The mean survival duration was $22.76{\pm}3.50$ months in cyclin D1 positive group and $45.38{\pm}5.64$ months in eyclin D1 negative group. There was a nearly significant difference in overall survival between cyclin D1 positive and negative groups(p=0.0515) in radically resected non-small cell lung cancer. Conclusion: Based on this study, cyelin D1 overexpression appears an important poor prognostic indicator in non-small cell lung cancer and may have diagnostic and prognostic importance in the treatment of resectable non-small cell lung cancer.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.46-56
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• 2012

Recently, when software architecture is designed, the efficiency of reusability is emphasized. The reusability of the design can raise the quality of GIS software, and reduce the cost of maintenance. Because the object oriented GoF design pattern provides the class hierarchy that can represent repetitively, the importance is emphasized more. This method that designs the GIS software can be applied from various application systems. A multiple distributed sensor network system is composed of the complex structure that each node of the sensor network nodes has different functions and sensor nodes and server are designed by the combination of many classes. Furthermore, this sensor network system may be changed into more complex systems according to a particular purpose of software designer. This paper will design the CATL model by applying Facade pattern that can enhance the efficiency of reuse according to attributes and behaviors in classes in order to implement the complicated structure of the multiple distributed sensor network system based on TinyOS. Therefore, our object oriented GIS design pattern model will be expected to utilize efficiently for design, update, or maintenance, etc. of new systems by packing up attributes and behaviors of classes at complex sensor network systems.

• Radiation Oncology Journal
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• v.33 no.2
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• pp.109-116
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• 2015

Purpose: To analyze prognostic factors for locoregional recurrence (LRR), distant metastasis (DM), and overall survival (OS) in cervical cancer patients who underwent radical hysterectomy followed by postoperative radiotherapy (PORT) in a single institute. Materials and Methods: Clinicopathologic data of 135 patients with clinical stage IA2 to IIA2 cervical cancer treated with PORT from 2001 to 2012 were reviewed, retrospectively. Postoperative parametrial resection margin (PRM) and vaginal resection margin (VRM) were investigated separately. The median treatment dosage of external beam radiotherapy (EBRT) to the whole pelvis was 50.4 Gy in 1.8 Gy/fraction. High-dose-rate vaginal brachytherapy after EBRT was given to patients with positive or close VRMs. Concurrent platinum-based chemoradiotherapy (CCRT) was administered to 73 patients with positive resection margin, lymph node (LN) metastasis, or direct extension of parametrium. Kaplan-Meier method and log-rank test were used for analyzing LRR, DM, and OS; Cox regression was applied to analyze prognostic factors. Results: The 5-year disease-free survival was 79% and 5-year OS was 91%. In univariate analysis, positive or close PRM, LN metastasis, direct extension of parametrium, lymphovascular invasion, histology of adenocarcinoma, and chemotherapy were related with more DM and poor OS. In multivariate analysis, PRM and LN metastasis remained independent prognostic factors for OS. Conclusion: PORT after radical hysterectomy in uterine cervical cancer showed excellent OS in this study. Positive or close PRM after radical hysterectomy in uterine cervical cancer correlates with poor prognosis even with CCRT. Therefore, additional treatments to improve local control such as radiation boosting need to be considered.

• Journal of KIISE
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• v.44 no.1
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• pp.84-94
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• 2017

Recently, the importance of velocity, one of the characteristics of big data (5V: Volume, Variety, Velocity, Veracity, and Value), has been emphasized in the data processing, which has led to several studies on the real-time stream processing, a technology for quick and accurate processing and analyses of big data. In this paper, we propose a Squall framework using Time-triggered Message-triggered Object (TMO) technology, a model that is widely used for processing real-time big data. Moreover, we provide a description of Squall framework and its operations under a single node. TMO is an object model that supports the non-regular real-time processing method for certain conditions as well as regular periodic processing for certain amount of time. A Squall framework can support the real-time event stream of big data and micro-batch processing with outstanding performances, as compared to Apache storm and Spark Streaming. However, additional development for processing real-time stream under multiple nodes that is common under most frameworks is needed. In conclusion, the advantages of a TMO model can overcome the drawbacks of Apache storm or Spark Streaming in the processing of real-time big data. The TMO model has potential as a useful model in real-time big data processing.

• Journal of Gastric Cancer
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• v.5 no.2
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• pp.79-88
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• 2005

Quality assurance may be defined as the complete set of systemic actions that is required to achieve a better treatment result by standardizing treatment and by using various audit programs. In general, application of a quality assurance program in surgery is considered to be more difficult than it is in chemotherapy or radiotherapy. However, recently, the importance of quality assurance in the surgical field has been emphasized in clinical trials comparing different surgical procedures and evaluating the role of postoperative adjuvant therapy. In the case of gastric cancer surgery, excellent quality assurance programs have rarely been applied in most large prospective clinical trials. Although the quality assurance in Dutch trial was conducted very systemically and strictly, the situation is quite different from ours. On the other hand, several quality assurance programs in Japanese trials comparing D2 and D2 plus para-arotic lymph node dissection seem to be applicable to Korean clinical trials. Several factors, including selection of appropriate surgeons based on personal experience and annual number of operations, standardization of surgical procedures by education and consensus, development of a unified database program, application of standardized perioperative management, and standardization of pathologic examination, are required to guarantee a successful multi-institutional prospective clinical trial. In contrast, one needs to realize that protocols that are too strict and sophisticated can make the enrollment of patients and surgeons more difficult and can promote protocol violation during the clinical trials. (J Korean Gastric Cancer Assoc 2005;5:79-88)

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6789-6794
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• 2015

Background: To analyze the expression of estrogen receptors (ER), progesterone receptors (PR), C-erbB-2 and Ki-67 in endometrial carcinoma (EC) and their relationships with the clinicopathological features. Materials and Methods: Sixty-seven EC samples, 53 normal endometrial samples and 53 atypical hyperplasia endometrial samples were all selected in Shaanxi Provincial People's Hospital from Jun., 2012 to Jun., 2014. The expression of ER, PR, C-erbB-2 and Ki-67 in EC tissue, normal endometrial tissue and atypical hyperplasia endometrial tissue was respectively detected using immunohistochemical SP method. The relationships between the expression of ER, PR, C-erbB-2 and Ki-67 and the patients' clinicopathological features as well as their correlations in EC tissue were also analyzed. Results: The positive expression rates of ER and PR in EC tissue were 44.8% and 41.8%, respectively, dramatically lower than in atypical hyperplasia endometrial tissue and normal endometrial tissue (P<0.01). The positive expression rates of C-erbB-2 and Ki-67 in EC tissue were 80.6% and 64.2%, respectively, significantly higher than in atypical hyperplasia endometrial tissue and normal endometrial tissue (P<0.01). In EC tissue, the expression of ER and PR was closely associated with the differentiated degrees and depth of myometrial invasion (P<0.05), while that of C-erbB-2 and Ki-67 with the clinical staging, differentiated degrees, depth of myometrial invasion and presence or absence of lymph node metastasis (P<0.05). Spearman correlation analysis further displayed that the expression of ER was positively correlated with PR (r=0.393, P=0.001), but negatively with C-erbB-2 and Ki-67 (r=-0.469, P=0.000; r=-0.329, P=0.007); The expression of PR was negatively correlated with C-erbB-2 and Ki-67 (r=-0.273, P=0.025; r=-0.251, P=0.041), but that of C-erbB-2 positively with Ki-67 (r=0.342, P=0.005). Conclusions: Abnormal expression of ER, PR, C-erbB2 and Ki-67 might play an important role in endometrial malignant transformation and cell differentiation, so their joint detection is likely to be a comprehensive combination of immune factors, which is of great importance for EC prognosis.

• Spatial Information Research
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• v.18 no.4
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• pp.109-120
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• 2010

Recently, due to rapid increasement of spatial data collected from various geosensors in u-GIS environments, the importance of spatial index for efficient search of large spatial data is rising gradually. Especially, researches based R-Tree to improve search performance of spatial data have been actively performed. These previous researches focus on reducing overlaps between nodes or the height of the R -Tree. However, these can not solve an unnecessary node access problem efficiently occurred in tree traversal. In this paper, we propose a MR-Tree(Mapping-based R-Tree) to solve this problem and to support efficient search of large spatial data. The MR-Tree can improve search performance by using a mapping tree for direct access to leaf nodes of the R-Tree without tree traversal. The mapping tree is composed with MBRs and pointers of R-Tree leaf nodes associating each partition which is made by splitting data area repeatedly along dimensions. Especially, the MR-Tree can be adopted in various variations of the R-Tree easily without a modification of the R-Tree structure. In addition, because the mapping tree is constructed in main memory, search time can be greatly reduced. Finally, we proved superiority of MR-Tree performance through experiments.