• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.31-48
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• 2023

The popularization of smart devices and subsequent optimization of their sensing capacity has resulted in a novel mobile crowdsensing (MCS) pattern, which employs smart devices as sensing nodes by recruiting users to develop a sensing network for multiple-task performance. This technique has garnered much scholarly interest in terms of sensing range, cost, and integration. The MCS is prevalent in various fields, including environmental monitoring, noise monitoring, and road monitoring. A complete MCS life cycle entails task allocation, data collection, and data aggregation. Regardless, specific drawbacks remain unresolved in this study despite extensive research on this life cycle. This article mainly summarizes single-task, multi-task allocation, and space-time multi-task allocation at the task allocation stage. Meanwhile, the quality, safety, and efficiency of data collection are discussed at the data collection stage. Edge computing, which provides a novel development idea to derive data from the MCS system, is also highlighted. Furthermore, data aggregation security and quality are summarized at the data aggregation stage. The novel development of multi-modal data aggregation is also outlined following the diversity of data obtained from MCS. Overall, this article summarizes the three aspects of the MCS life cycle, analyzes the issues underlying this study, and offers developmental directions for future scholars' reference.

• The Journal of Bigdata
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• v.1 no.2
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• pp.91-102
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• 2016

In traditional environments we have called the data life cycle DIKW, which represents data-information-knowledge-wisdom. In big data environments, on the other hand, we call it DIA, which represents data-insight-action. The difference between the two data life cycles results in new architecture of data resource management. In this paper, we study data resource management architecture for big data environments. Especially main components of the architecture are proposed in this paper.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.213-220
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• 1999

The life data analysis of the system and component are useful to describe the result of reliability test in product life to satisfy customer's growing need and to change test specifications or design criteria by life data analysis. And vehicle durability tesr occurred market environment. In this study, a statistical analysis for the wear life of brake pad linings helped perform correlation procedure between vehicle durability test and market. B-life values of the brake pad wear life data from both vehicle durability test and marker usage were compared to determine acceleration of the test by the Weibull, normal and log-normal distribution. The acceleration coefficient of the vehicle durability test can access to evaluate design criteria of product and test specification.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.61-68
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• 2022

In this paper, the change history of various types of MV (Medium Voltage) cables was investigated. In addition, the statistical life expectancy of each type was calculated by using the operation data and the failure data. For cut-off year, 10 years was applied, and realistically applicable statistical life expectancy was calculated by correcting the cause of failure entered by mistake. The life expectancy of FR-CNCO-W was calculated as 51.2 years, CNCV-W 38.1 years, and CNCV 31.4 years and the overall average is 33.8 years. Currently, the life expectancy of TR CNCV-W is 29.4 years, but it is estimated that the lifespan will be extended if failure data is accumulated. As a result, it is expected that life expectancy results can be applied to Asset Management System (AMS) in the future.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.24
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• pp.10871-10874
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• 2015

Background: Gestational trophoblastic neoplasia (GTN) is a malignant disease which occurs in women of reproductive age. Treatment of GTN has an excellent outcome and further pregnancies can be expected. However, data concerning quality of life in these cancer survivor patients are limited. This study aimed to assess quality of life in women who were diagnosed with GTN and remission after treatment, and to determine factors that may affect quality of life status. Materials and Methods: This cross sectional study was conducted from July 2013 to May 2014 in the Gestational Trophoblastic Disease Clinic, King Chulalongkorn Memorial Hospital, Bangkok, Thailand. Patients who were diagnosed GTN and complete remission were recruited. Data collection was accomplished by interview with two sets of questionnaires, one general covering demographic data and the other focusing on quality of life, the fourth version of Functional Assessment of Cancer Therapy (FACT-G). Descriptive statistics were used to determine general data and quality of life scores. Students t-test and one way ANOVA were used to compare between categorical and continuous data. Results: Forty four patients were enrolled in this study. The overall mean quality of life score (FACT-G) was 98.2. The overall FACT-G score was not significantly correlated with age, education level, stage of disease, treatment modalities, and time interval from remission to enrollment. However, patients who needed further fertility showed significant lower FACT-G scores in the emotional well-being domain (p=0.02). Conclusions: Overall quality of life scores in post-treatment gestational trophoblastic neoplasia patients are in the mild impairment range. Patients who desire fertility suffer lower quality of life in the emotional well-being domain.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.3
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• pp.30-36
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• 2013

This paper presents a method to estimate a storage life for loss of stabilizer content as storage periods using accelerated life test data. The estimate of storage life based on deterministic accelerated life test and degradation data cannot describe a condition distribution and storage life distribution. Previously, the method to show the condition distribution and storage life distribution by using gamma process has been studied. But it has limitation because it is impossible to collect the deterioration data at initial production phase. The estimated storage life presented by this study shows the similar value to previous studies and the method can describe the condition distribution and storage life distribution. So, the estimation method studied in this paper can be used for a life cycle management about deterioration of propellant for propulsion unit or components of missile, too.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.645-654
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• 2019

The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.679-694
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• 2003

The purpose of this paper is to develop the Index of Balanced Life from the Korean life style. This paper presents How Koreans live for 24 hours a day, generally. The Index of Life Style is composed of necessary life, duty life and leisure life. Specifically, this paper considers moving time of activity between indexes of balanced life. We suggest that there is a difference among the characteristics, i.e., a sex, week, state of student and region that are explained by analyzing the exploratory data. Thereafter we obtain the statistical inference from each characteristic table.

• Journal of Family Resource Management and Policy Review
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• v.11 no.1
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• pp.65-81
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• 2007

The purpose of this study is to analyze income and consumption expenditure patterns over the family life cycle. The data used in this study is the 2004 Survey data from the Annual Report on the Family Income and Expenditure Survey data which are included salary and wage earners' households living in urban areas. The income and expenditure data of 20,383 households are analyzed. The family life cycle is classified into six stages and the items of expenditure are classified into 12 categories. The data are analyzed by descriptive statistics, $X^2$ test, F-test, and Duncan's multiple range test using SAS 8.0 package program. The major findings of this study are as fellows: First, the average monthly family income of the total sample is 3,480,000 won. The proportion of regular and irregular income among the total family income is 95.5% and 4.5% respectively. Second, the amount and ratio of monthly regular income fur each category are significantly different over the family life cycle. Third, the average monthly family expenditure of the total sample is 2,250,000 won. The amount and ratio of monthly expenditure of all items are significantly different over the family life cycle. The highest expenditure item is the traffic expanse and phone charge.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.189-193
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• 2014

SNS (Social Network Service) has evolved to life-friendly service with the combination of local services. Unlike exsiting mobile services, life-friendly service is expected to be personalized with gathering of local information, location information and social network service information. In the process of gathering various kinds of information, Big-data technology and Cloud technology is needed. The effective algorithem has researched for this already, however the privacy protection model hasn't researched enough in life-friendly service or big-data using circumstance. In this paper, the privacy issue is dealt with in terms of 'Structure hole', and the privacy issue comes from big-data technology of life-friendly service.