• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.317-326
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• 2022

This study examined the moderating effect which the interpersonal trust between christians has on the daily spiritual experiences and church commitments of christians. This study was conducted on 400 Christians - 193 men (48.3%) and 207 women (51.7%). The SPSS 25.0 program and PROCESS Procedure for SPSS version 3.5 (Model 1) were used for data analysis and for verifying the hypothesis. the results of the study showed: First, the daily spiritual experience of Christians had a significant positive effect on church commitment. Second, the interpersonal trust between christians had a significant positive effect on church commitment among Christians. Third, the interpersonal trust between christians had a significant positive effect on daily spiritual experiences and on church commitment. Hence, based on the above conclusions the role and importance of trustworthy relationships in the church as well as personal beliefs were discussed.

• Information Systems Review
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• v.16 no.3
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• pp.113-134
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• 2014

Since a movie is an experience goods, purchase can be decided upon preliminary information and evaluation. There are ongoing researches on what impact online reviews might have on movie revenues. Whereas research in the past was focused on the effect of online reviews. The influence of online reviews appears to be significant in products like a movie because it is difficult to evaluate the feature prior to "consuming" the product. Since an online review is regarded to be objective, consumers find it more trustworthy. Contrary to prior research focused on movie review ratings and volume, we focus moves on movie features related specific reviews. This research proposes a predictive model for movie revenue generation. We decided 15 criteria to classify movie features collected from online reviews through the online review mining and made up feature keyword list each criterion. In addition, we performed data preprocessing and dimensional reduction for data mining through factor analysis. We suggest the movie revenue predictive model is tested using discriminant analysis. Following the discriminant analysis, we found that online review factors can be used to predict movie popularity and revenue stream. We also expect using this predictive model, marketers and strategic decision makers can allocate their resources in more parsimonious fashion.

• Water for future
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• v.7 no.2
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• pp.11-22
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• 1974

Comparing with Seoul city's other administrative works, the work to arrange and collect monthly water rates with 470,000 faucets is tremendous in volume and simple repetition in quality. In order to cover the shortage of handling, it is urgent for us to replace the present manual system with EDP(Electronic Data Processing) system to mechanize a series of handling works of simple repeated calculation such as water consumption, rate calculation, statistics arrangement, bills and specification of water rate by computer. When this work is completely mechanized, inspectors of water meter just turn over their checking results to the Data Center and all data are processed through Input Media(OMR Card, Punched Card) and computer for programming final bills. Then, the delivery of the bills to citizens will be the only work to be carried out. such mechanization will bring about the following benefits: 1. Improvement of administrative work by efficiency and rationalization. 2. Improvement of administrative service with people. 3. Possibility of scientific with trustworthy multi-purpose policy-making data. 4. An effect to cover the personnel shortage of 252 persons (at all the water works offices) and save manpower of 166 persons (47,619 man-days). The application of the above mentioned mechanization will be started to only Chongro and Chung-ku water works offices as model cases out of all water works offices in Seoul. As the electronic calculating machines are inducted, this system will be gradually applied to other water works offices. The billing and collection works of water rates which are connected directly to the daily life of the citizenes, should be handled by the scientific EDP system as soon as possible in order to promote the convenience of consumers and effective operation. This study is to promote the sound and rational operation of this work.

• Korean Journal of Human Ecology
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• v.22 no.2
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• pp.343-355
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• 2013

E-reviews, electronic reviews, are generally perceived as trustworthy and credible by the consumers, because it is based on the experiences of other consumers who are independent of the marketers. Therefore, consumers may rely more on the review information as an important cue than direct experience or advertising. This paper explored the structural equation model to investigate the relationships among search motives of e-reviews, attributes of e-review, trust, and purchase intention for cosmetics. A self-questionnaire was developed based on previous researches. Data were collected from 300 female university students experienced purchasing cosmetics at the Internet and were analyzed by AMOS 20.0. Results showed that e-review attributes consisted of three factors: expertise/visuality, quality/functionality and advertising/design. Utilitarian and hedonic search motives were significantly related to expertise/ visuality attributes of e-review and then influenced the purchase intention for cosmetics, mediated by the trust of e-review. However, quality/functionality attributes related by utilitarian motive did not have a significant effect to trust of e-review and purchase intention for cosmetics. Regardless of search motives and trust of e-review, advertising/design attributes of e-review directly related to purchase intention of cosmetics. As predicted, the trust of e-review was an important mediated variable to stimulate the purchase intention of cosmetics at internet. The implications of findings for research and practice are discussed.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.1-9
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• 2009

In heterogeneous and distributed computing environments, with an increasing number of Web services providing similar functionalities, the reliability of Web services is a critical decision factor. To fulfill the open business model such as cooperation among enterprises, several Web services can be composed into the upper level business transaction. In Web services composition, the reliability of services is more and more critical. Though each unit Web service can be reliable, the reliability of the composed service is not guaranteed. Thus a way to efficiently assess and select composed Web services is needed. In this paper, we define new metrics for measuring the trust value of Web services, and propose an evaluation method to predict the trustworthy degree of the composed services based on the metrics. We also define a conceptual framework to support optimal Web services selection based on the proposed trust evaluation method. By selecting using the quantitative measurement rather than intuitive selection of the service user, it allows the service users to select the high reliable service meeting their quality requirements well.

• Journal of Korean Society of Archives and Records Management
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• v.3 no.1
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• pp.111-127
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• 2003

Web-based information resources should be managed and used methodically in the same manner as the paper-based resources are managed and used. It is necessitated by the prevalence of web-based delivery of a variety of information. To develop a web-based digital collection, it is critical to establish a set of standardized evaluation criteria for web-resources. The evaluation criteria needs to include authority, trustworthy, reliability, functionality, relatedness, accessibility, structure, design, user support, and security related matters. However, it is also necessary to have certain flexibility to either emphasize or include particular evaluation criteria to reflect varying characteristics of the web resources especially for the purpose of developing an effective digital collection. In addition, it is essential to review the evaluation criteria with respect to value, demand, duplication prevention, and intellectual property, which are relevant to the web-based digital collection development. Finally, various strategies were suggested as means to develop more effective web-based digital resource collection. These strategies include organizing a selection committee to ensure the objectivity and consistency in web-resource evaluation; developing a model for web-based digital resource collection; sharing new standards, protocols, markups, and metadata with other digital libraries; and developing user-centered digital resource collection.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.148-162
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• 2023

Classification systems can significantly assist the medical sector by allowing for the precise and quick diagnosis of diseases. As a result, both doctors and patients will save time. A possible way for identifying risk variables is to use machine learning algorithms. Non-surgical technologies, such as machine learning, are trustworthy and effective in categorizing healthy and heart-disease patients, and they save time and effort. The goal of this study is to create a medical intelligent decision support system based on machine learning for the diagnosis of heart disease. We have used a mixed feature creation (MFC) technique to generate new features from the UCI Cleveland Cardiology dataset. We select the most suitable features by using Least Absolute Shrinkage and Selection Operator (LASSO), Recursive Feature Elimination with Random Forest feature selection (RFE-RF) and the best features of both LASSO RFE-RF (BLR) techniques. Cross-validated and grid-search methods are used to optimize the parameters of the estimator used in applying these algorithms. and classifier performance assessment metrics including classification accuracy, specificity, sensitivity, precision, and F1-Score, of each classification model, along with execution time and RMSE the results are presented independently for comparison. Our proposed work finds the best potential outcome across all available prediction models and improves the system's performance, allowing physicians to diagnose heart patients more accurately.

• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.608-615
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• 2008

In Knowledge Q&A services where information is created by unspecified users, document quality is an important factor of user satisfaction with search results. Previous work on quality prediction of Knowledge Q&A documents evaluate the quality of documents by using non-textual information, such as click counts and recommendation counts, and focus on enhancing retrieval performance by incorporating the quality measure into retrieval model. Although the non-textual information used in previous work was proven to be useful by experiments, data sparseness problem may occur when predicting the quality of newly created documents with such information. To solve data sparseness problem of non-textual features, this paper proposes new features for document quality prediction, namely text-confidence features, which indicate how trustworthy the content of a document is. The proposed features, extracted directly from the document content, are stable against data sparseness problem, compared to non-textual features that indirectly require participation of service users in order to be collected. Experiments conducted on real world Knowledge Q&A documents suggests that text-confidence features show performance comparable to the non-textual features. We believe the proposed features can be utilized as effective features for document quality prediction and improve the performance of Knowledge Q&A services in the future.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.