• The Journal of Bigdata
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• v.3 no.2
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• pp.19-33
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• 2018

Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.

• The Journal of Bigdata
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• v.8 no.2
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• pp.125-131
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• 2023

Globally, drug side effects rank among the top causes of death. To effectively respond to these adverse drug reactions, a shift towards an active real-time monitoring system, along with the standardization and quality improvement of data, is necessary. Integrating individual institutional data and utilizing large-scale data to enhance the accuracy of drug side effect predictions is critical. However, data sharing between institutions poses privacy concerns and involves varying data standards. To address this issue, our research adopts a federated learning approach, where data is not shared directly in compliance with privacy regulations, but rather the results of the model's learning are shared. We employ the Common Data Model (CDM) to standardize different data formats, ensuring accuracy and consistency of data. Additionally, we propose a drug monitoring system that enhances security and scalability management through a cloud-based federated learning environment. This system allows for effective monitoring and prediction of drug side effects while protecting the privacy of data shared between hospitals. The goal is to reduce mortality due to drug side effects and cut medical costs, exploring various technical approaches and methodologies to achieve this.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.258-269
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• 2017

This study was conducted to examine the predictive factors for health promotion behaviors of breast cancer patients, focusing on Pender's health promotion model (1996). Data were collected from 121 patients using a structured questionnaire from September 18 to October 26 in 2015. The data were analyzed with a t-test, ANOVA, Pearson's correlation coefficients, and hierarchical multiple regression analysis using SPSS 20.0 for Windows. The predictive factors for the health promotion behavior of the participants were social support, commitment to a plan of action, prior behavior, activity related effects, perceived self-efficacy, family function, perceived benefits of action, and situational influences. The total explanatory power of these factors was 57.8%. Development and application of a nursing intervention plan that enhances patient compliance with health promotion behavior is needed to enable breast cancer patients undergoing rehabilitation to maintain their optimal health and live a high-quality life. Patients who showed a low degree of predictive factors identified in this study are in particular need of attention.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.83-89
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• 2024

After the end of the service of Internet Explorer, the use of ActiveX ended, and the Non-ActiveX policy spread. HTML5 is used as a standard protocol for web pages established based on the Non-ActiveX policy. HTML5, developed in the W3C(World Wide Web Consortium), provides a better web application experience through API, with various elements and properties added to the browser without plug-in. However, new security vulnerabilities have been discovered from newly added technologies, and these vulnerabilities have widened the scope of attacks. There is a lack of research to find possible security vulnerabilities in HTML5-applied websites. This paper proposes a model for detecting tags and attributes with web vulnerabilities by detecting and analyzing security vulnerabilities in web pages of public institutions where plug-ins have been removed within the last five years. If the proposed model is applied to the web page, it can analyze the compliance and vulnerabilities of the web page to date even after the plug-in is removed, providing reliable web services. And it is expected to help prevent financial and physical problems caused by hacking damage.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.445-456
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• 2004

The database schema is assumed to be stable enough to remain valid even as the modeled environment changes. However, in practice. data models are not nearly as stable as commonly assumed by the database designers. Even though a rich set of schema change operations is provided in current database systems, the users suffer from the problem that schema change usually impacts existing application programs that have been written against the schema. In this paper, we are exploring the possible solutions to overcome this problem of impacts on the application programs. We believe that for continued support of the existing programs on the old schema, the old schema should continue to allow updates and queries, as before. Furthermore, its associated data has to be kept up-to-date. We call this the program independency property of schema change tools. For this property. we devise so-called program independency schema evolution (PISE) methodology. For each of the set of schema change operations in the relational schemas, the sketch of the additional algorithms due to the PISE compliance is presented in order to prove the comprehensiveness and soundness of our PISE methodology.

• Korean journal of communication and information
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• v.41
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• pp.268-302
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• 2008

This paper analyzes an NHK's 'Performances of Reform and Revival'. As a result of analysis, it was focused on reinforcement of the management such as audit, corporate governance, compliance, and thus the accountability was insufficient. Generally speaking, public service broadcasting is the form of organization of mass media that is most directly accountable to society. Therefore, the efforts is required for public service broadcasting to figure out to endow the social roles and responsibilities to themselves differentiated from other commercial broadcasters. And it is necessary that the concrete systems and activities based on an answerability model so that public broadcasters fulfill the accountability. Answerability means that broadcasting organizations and journalists both take account of and are accountable to the public. In such a process, the positive and voluntary civic participation is indispensable.

• Journal of the Korean Institute of Gas
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• v.14 no.1
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• pp.28-36
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• 2010

We have garnered 3,593 data of gas accidents reported for 12 years from 1995, and then analyzed the LPG vaporizer accidents according to their types and causes based on the classified database. According to the results the gas rupture has been the most common accident followed by the release, explosion and then fire accidents, the most frequent accident-occurring sub-cause is LPG check floater faults. In addition, we have applied the Poisson Probability Functions to predict the most-likely probabilities of fire, explosion, release and rupture with the LPG vaporizer in the upcoming 5 years. In compliance with Poisson Probability Functions results, in the item which occurs below 3 "LPG-Vaporizer-Fire", in the item which occurs below 5 "LPG-Vaporizer-Products Faults-Check Floater" and the item which occurs below 10 appeared with "LPG-Vaporizer-Products Faults". From this research we have assured the successive database updating will highly improve the anticipating probability accuracy and thus it will play a key role as a significant safety- securing guideline against the gas disasters.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8095-8099
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• 2014

Background: Worldwide, over half a million women died of breast cancer in 2011 alone. Mammography screening is associated with a reduction of 20 to 35% in breast cancer mortality. The aim of this study was to determine the awareness and practice of mammography screening and predictors of its uptake in Malaysian women attending a primary care clinic. Materials and Methods: A cross-sectional study was carried out among women aged 40 to 74 years attending a primary care clinic in Selangor, Malaysia. An assisted structured questionnaire included questions on socio-demography, source of information and level of knowledge. An adapted version of the revised Champion Health Belief Model Scale plus other associated factors for mammography screening up-take were also included as part of the questionnaire. Predictors for mammography screening uptake were only determined in those who were aware about mammography screening. Significant predictors were determined by logistic regression. Results: 447 women were recruited for this study; 99.1% of them (n: 411) were aware about breast cancer. Only 50.1% (n: 206) had knowledge about mammography screening. Prevalence of clinical breast-examination (CBE) was 23.3% (n: 104) and mammography screening up-take was 13.2% (n: 59). The predictors for the latter were those who have had clinical breast-examination (aOR=17.58, 95%CI: 7.68-39.82) and those aged between 50 to 59 years (aOR=3.94, 95%CI: 1.61-9.66) as well as those aged 60 years and above (aOR=6.91, 95%CI: 2.28-20.94). Good knowledge and positive beliefs about mammography screening were not associated with mammography screening uptake. Conclusions: Half of our Malaysian women were aware about mammography screening. However, the uptake of mammography was low. Previous CBE and older age were significant predictors of mammography screening uptake. Increasing CBE services may increase compliance with guidelines.

• Computers and Concrete
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• v.15 no.6
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• pp.951-972
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• 2015

The focus of the present study is to investigate both local and global behaviour of a precast concrete sandwich panel. The selected prototype consists of two reinforced concrete layers coupled by a system of cold-drawn steel profiles and one intermediate layer of insulating material. High-definition nonlinear finite element (FE) models, based on 3D brick and 2D interface elements, are used to assess the capacity of this technology under shear, tension and compression. Geometrical nonlinearities are accounted via large displacement-large strain formulation, whilst material nonlinearities are included, in the series of simulations, by means of Von Mises yielding criterion for steel elements and a classical total strain crack model for concrete; a bond-slip constitutive law is additionally adopted to reproduce steel profile-concrete layer interaction. First, constitutive models are calibrated on the basis of preliminary pull and pull-out tests for steel and concrete, respectively. Geometrically and materially nonlinear FE simulations are performed, in compliance with experimental tests, to validate the proposed modeling approach and characterize shear, compressive and tensile response of this system, in terms of global capacity curves and local stress/strain distributions. Based on these experimental and numerical data, the structural performance is then quantified under various loading conditions, aimed to reproduce the behaviour of this solution during production, transport, construction and service conditions.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.3
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• pp.411-423
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• 2010

Retail stores with a primary competitive advantage in satisfying customers with high quality differentiated services depend heavily on a sales force to produce and deliver services in a consistent manner. Salespersons in a high service retail context are required to act to express certain types of emotion in compliance with the emotional rules of the organization that is conceptualized as "emotional labor" in the literature. This study adopts the dyadic model of emotional labor originally proposed by Hochschild. A survey method is implemented to collect data to test the hypotheses among the variables such as positive and negative affectivity, performance stressor, emotional labor, burnout, and job satisfaction. One hundred and twelve responses were analyzed by factor analysis and path analysis with SPSS12.0 and Amos 6.0. The factor analysis confirms that emotional labor is composed of deep acting and surface acting. Eleven hypotheses were tested by path analysis and seven were accepted. The major findings are that deep acting was affected by positive affectivity, negative affectivity, and a performance stressor. The surface acting was affected only by negative affectivity. Surface acting had an indirect negative effect on job satisfaction via emotional burnout while deep directly acting influenced job satisfaction. Furthermore, the interaction effect between positive affectivity and a performance stressor on surface acting was significant. The implications for retail firms are discussed based on the findings with suggestions for future studies.