• BMB Reports
• /
• 제52권1호
• /
• pp.56-63
• /
• 2019

Aging is a complex and progressive process characterized by physiological and functional decline with time that increases susceptibility to diseases. Aged-related functional change is accompanied by a low-grade, unresolved chronic inflammation as a major underlying mechanism. In order to explain aging in the context of chronic inflammation, a new integrative concept on age-related chronic inflammation is necessary that encompasses much broader and wider characteristics of cells, tissues, organs, systems, and interactions between immune and non-immune cells, metabolic and non-metabolic organs. We have previously proposed a novel concept of senescent (seno)-inflammation and provided its frameworks. This review summarizes senoinflammation concept and additionally elaborates modulation of senoinflammation by calorie restriction (CR). Based on aging and CR studies and systems-biological analysis of Omics big data, we observed that senescence associated secretory phenotype (SASP) primarily composed of cytokines and chemokines was notably upregulated during aging whereas CR suppressed them. This result further strengthens the novel concept of senoinflammation in aging process. Collectively, such evidence of senoinflammation and modulatory role of CR provide insights into aging mechanism and potential interventions, thereby promoting healthy longevity.

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.276-279
• /
• 2015

Along with the increase of the quantity of data in various industries, the construction industry has also developed various systems focusing on collecting data related to the construction performance such as productivity and costs achieved in construction job sites. Numerous researchers worldwide have been focusing on developing efficient methodologies to analyze such data. However, applications of such methodologies have shown serious limitations on practical applications due to lack of data and difficulty in finding appropriate analytic methodologies which were capable of implementing significant insights. With development of information technology, the new trend in analytic methodologies has been introduced and steeply developed with the new name of "big data analysis" in various fields in academia and industry. The new concept of big data can be applied for significant analysis on various formats of construction data such as structured, semi-structured, or non-structured formats. This study investigates preliminary application methods based on data collected from actual construction site. This preliminary investigation in this study expects to assess fundamental feasibility of big data analytic applications in construction.

• 한국응용과학기술학회지
• /
• 제37권1호
• /
• pp.76-82
• /
• 2020

Big data analysis in healthcare research seems to be a necessary strategy for the convergence of sports science and technology in the era of the Fourth Industrial Revolution. The purpose of this study is to provide the basic review to secure the diversity of big data and healthcare convergence by discussing the concept, analysis method, and application examples of big data and by exploring the application. Text mining, data mining, opinion mining, process mining, cluster analysis, and social network analysis is currently used. Identifying high-risk factor for a certain condition, determining specific health determinants for diseases, monitoring bio signals, predicting diseases, providing training and treatments, and analyzing healthcare measurements would be possible via big data analysis. As a further work, the big data characteristics provide very appropriate basis to use promising software platforms for development of applications that can handle big data in healthcare and even more in sports science.

• Journal of Information Processing Systems
• /
• 제19권2호
• /
• pp.189-202
• /
• 2023

In the era marked by information inundation, social network analysis is the most important part of big data analysis, with clique detection being a key technology in social network mining. Also, detecting maximal balance clique in signed networks with positive and negative relationships is essential. In this paper, we present two algorithms. The first one is an algorithm, MCDA1, that detects the maximal balance clique using the improved three-way concept lattice algorithm and object-induced three-way concept lattice (OE-concept). The second one is an improved formal concept analysis algorithm, MCDA2, that improves the efficiency of memory. Additionally, we tested the execution time of our proposed method with four real-world datasets.

• 대한안전경영과학회지
• /
• 제14권4호
• /
• pp.229-238
• /
• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• 한국컴퓨터정보학회논문지
• /
• 제25권4호
• /
• pp.149-156
• /
• 2020

4차산업 혁명으로 다양한 산업분야에서 빅데이터 기술을 성공적으로 활용하여 경영성과를 얻은 사례들이 보고되고 있다. 본 논문은 의료산업에서 빅데이터를 성공적으로 활용한 혁신 사례들 살펴보고 어떤 데이터가 어떠한 목적으로 활용되고 있으며 이러한 빅데이터가 어떤 가치를 창출하는지 시사점을 도출하고자 하였다. 서론에서는 본 연구의 배경과 방향에 대해 기술하여 연구의 전체적인 구조를 파악하고자 하였다. 문헌 연구에서는 빅데이터의 정의 및 개념과 빅데이터 연구와 관련된 내용, 그리고 의료 산업에서의 빅데이터의 활용과 관련된 내용을 설명하고자 하였다. 본문에서는 질병연구를 위해 국민건강정보와 개인유전정보를 활용한 기술, 개인의 생체정보를 활용하여 개인 건강 서비스, 기업의 업무 프로세스 효율화를 위해 기업이 확보하고 있는 지식 데이터와 전자의무기록 정보를 활용한 사례, 그리고 신약개발을 위해 의료빅데이터 활용 사례 등을 서술하였다. 결론에서는 본 연구의 학문적, 비즈니스적 시사도출과 함께 연구의 성과가 국내 의료산업에 어떠한 도움을 줄 수 있는지 방향성을 제시하고자 하였다.

• 품질경영학회지
• /
• 제32권4호
• /
• pp.184-195
• /
• 2004

Current companies 집중 on how to operate and select projects to achieve the best result. 6sigma projects are chosen in the best suitable concept, which are solved by the 6Sigma experts according to the priority. And every project has to be launched not the view of individual management factors but the total factors, Big Y. Therefore, a process needs to be treated to connect the vital few factors in various processes to improve the yield, which is the main performance criteria in a manufacturing industry This report is to make the total optimization through the Vital-Few mapping between quality characteristics and process factors in a manufacturing line. Accordingly, it means to secure lower variance by making the CTP(Critical To Process) optimization and finally to improve the yield.

• 한국멀티미디어학회논문지
• /
• 제24권8호
• /
• pp.1192-1201
• /
• 2021

This study focused on how to analyze the ICT policy formation process using social big data. Specifically, in this study, a method for quantifying variables that influenced policy formation using the concept of a policy triggering mechanism and elements necessary to present the analysis results were proposed. For the analysis of the ICT policy triggering mechanism, variables such as 'Scope', 'Duration', 'Interactivity', 'Diversity', 'Attention', 'Preference', 'Transmutability' were proposed. In addition, 'interpretation of results according to data level', 'presentation of differences between collection and analysis time points', and 'setting of garbage level' were suggested as elements necessary to present the analysis results.

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.44-48
• /
• 2015

Housing price is a key indicator of housing demand. Actual Transaction Price Index of Apartment (ATPIA) released by Korea Appraisal Board is useful to understand the current level of housing price, but it does not forecast future prices. Big data such as the frequency of internet search queries is more accessible and faster than ever. Forecasting future housing demand through big data will be very helpful in housing market. The objective of this study is to develop a forecasting model of ATPIA as a part of forecasting housing demand. For forecasting, a concept of time shift was applied in the model. As a result, the forecasting model with the time shift of 5 months shows the highest coefficient of determination, thus selected as the optimal model. The mean error rate is 2.95% which is a quite promising result.

• ETRI Journal
• /
• 제34권5호
• /
• pp.783-786
• /
• 2012

This letter proposes a more advanced joint maximum a posteriori (MAP) adaptation using a prior model based on a probabilistic scheme utilizing the bilinear transformation (BIT) concept. The proposed method not only has scalable parameters but is also based on a single prior distribution without the heuristic parameters of the previous joint BIT-MAP method. Experiment results, irrespective of the amount of adaptation data, show that the proposed method leads to a consistent improvement over the previous method.