• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.226-232
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• 2024

This study attempted to demonstrate the role of perceived value and trust in the relationship between mobile banking service quality and use satisfaction. A survey was conducted on customers of Mongolian banks, and an analysis was conducted based on the collected data With the development of the fintech industry, the Internet-based mobile banking market is striving to provide convenient services to consumers. The result led to the introduction of an online-oriented Internet bank that can operate 24 hours a day regardless of time and space. The characteristic of operating only with the Internet has a positive aspect of providing services quickly and conveniently, but at the same time, including concerns about security and personal information leakage. This can make you hesitate to use the service. Therefore, we attempted to find out how the quality of mobile banking service affects the perceived value and satisfaction of using trust. A survey was conducted to verify the contents of the research model and hypothesis. This is to secure data to be used for empirical analysis of research hypotheses. The survey was conducted with 124 consumers in Ulaanbaatar, the capital of Mongolia. Based on the analysis results, we understood the satisfaction of consumers using mobile banking and suggested ways for consumers to improve their actual satisfaction using mobile banking. Specifically, service quality sensitivity, security, convenience, and design had a positive effect on perceived value or trust, ultimately leading to consumer satisfaction.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.73-79
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• 2017

It is difficult to detect the adult hearing loss after the language acquisition because of its slow progression, which can be evaluated voluntarily and actively when the appropriate tools are provided. Smartphones are one of useful tools, and they can utilize surveys and/or applications for hearing screening. This study aims to verify the possibility as a tool discovering delayed acquired hearing losses by comparing the pure tone screening application (app_PTS) which was recently developed by our research team and hearing handciap inventory (HHI). The subjects were 22 people whose age ranges from 10s to 80s. For pure tone averages (PTAs), hearing threshold level was selected the best one in same frequency, in both ears. Sensitivity and specificity of HHI were confirmed based on self awareness of hearing loss and PTAs at 1, 2, 4 kHz. Comparisons of two tests were measured by analyzing simple regression of correlation between PTAs of App_PTS and HHI scores. Sensitivity and specificity were 1.000 in both criteria. There was a statistically significant relationship between the PTAs_4 kHz and HHI (R-square = .951, p = .000). Hearing screening by questionnaire showed high correlation with smart phones based on application. Therefore, it can be useful as a hearing screening tool for individual life cycle using an user-friendly tool.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.81-93
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• 2011

This research deals with the multi-modal continuous network design problem to resolve the transportation policy problems for constructing and operating transportation facilities with considering the mutual decision-making process between transportation operator and user in the multi-modal network. Particularly, in the consideration of changes in travel pattern between transport modes due to the changes in transportation policy, road network for passenger car and transit network for public transportation are considered together. In the development of network design model, more rational Stackelberg equilibrium(cooperative game) rather than more general Nash equilibrium(non-cooperative game) approach is used and sensitivity analysis considering transport mode is used. A multi-modal continuous network design model in this study is developed for the arbitrary continuous network design parameters(${\epsilon},\hat{\epsilon},p$) of transportation policy decisions. As examples of application and evaluation for these design parameters, the developed model is applied to calculate 1)the optimal capacity of road link in the road transport policy, 2)the optimal frequency of transit line in public transport policy and 3)the optimal modal split in transport modal share policy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1797-1806
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• 1998

Future satellite communication systems will be developed at Ka-band (20/30 GHz) owing to the relatively wide frequency allocation and current freedom from terrestrial interference for multimedia services. A serious disadvantage of the Ka-band, however, is the very high atmospheric attenuation in rainy weather. Synchronous CDMA drastically redces the effect of self-noise with several interesting features of CDMA for mobile communications such as fixible freuqncy rese, the capability of performin soft-handover and a lower sensitivity to interference. This paper evaluates the performance of a synchronous CDMA reture link for a Ka-band geostationary satellite communication system. For a fixed satellite channel whose characteristics depend on weather conditions, the signal envelope and phase for this channel is modelled as Gaussian. The bit error and outage probability, and the detection loss due to imperfect chip timing synchronization is analytically evaluated and the system capacity degaradation due to the weather condition is estimated. The two cases consist of the general case in which all users are affected by rain condition, and the worst case in which the reference user is only affected by rain attenuation. the results for two cases of rain condition clearly show that synchronous CDMA eases the power control requirements and has less sensitivity to imperfect power control.

• Informatization Policy
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• v.19 no.2
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• pp.21-38
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• 2012

The proliferation of the Internet and the advent of e-commerce have amplified public concerns about privacy. Accordingly, much research effort has been made on the issue. While existing research on online information privacy has usually focused on the examination of antecedents of personal information disclosure, the literature has not paid attention to the potential changes of the antecedents' effects depending on the user's experience of the service. The current study aims to investigate the moderating role of site usage experience in Internet users' decision on personal information disclosure. Specifically, this study considers two types of antecedents of personal information disclosure on a site - the attributes of personal information requested (sensitivity and relevance of information) and the value of the service provided by the site; and examines how the effects of the antecedents on the disclosure intention are affected by the users'experience of the site. Our analysis of the data gathered through a web-based experiment reveals that site usage experience moderates the relationship between the attributes of personal information and disclosure intention. While usage experience attenuates the negative effect of information sensitivity on disclosure intention, it intensifies the positive impact that relevance of information has on disclosure intention. Based on the analysis results, we provide implications for the mitigation of the Internet users' privacy concerns as well as theoretical implications.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.6
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• pp.503-513
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• 2005

With the recognition of the importance of computational approach for protein-protein interaction prediction, many techniques have been developed to computationally predict protein-protein interactions. However, few techniques are actually implemented and announced in service form for general users to readily access and use the techniques. In this paper, we design and implement a protein interaction prediction service system based on the domain combination based protein-protein interaction prediction technique, which is known to show superior accuracy to other conventional computational protein-protein interaction prediction methods. In the prediction accuracy test of the method, high sensitivity($77\%$) and specificity($95\%$) are achieved for test protein pairs containing common domains with teaming sets of proteins in a Yeast. The stability of the method is also manifested through the testing over DIP CORE, HMS-PCI, and TAP data. Performance, openness and flexibility are the major design goals and they are achieved by adopting parallel execution techniques, web Services standards, and layered architecture respectively. In this paper, several representative user interfaces of the system are also introduced with comprehensive usage guides.

• Advances in nano research
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• v.16 no.4
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• pp.375-394
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• 2024

The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.139-149
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• 2004

As the expansion of road capacity has become impractical in many urban areas, congestion pricing has been widely considered as an effective method to reduce urban traffic congestion in recent years. The principal reason is that the congestion pricing may lead the user equilibrium (UE) flow pattern to system optimum (SO) pattern in road network. In the context of network equilibrium, the link tolls according to the marginal cost pricing principle can user an UE flow to a SO pattern. Thus, the pricing method offers an efficient tool for moving toward system optimal traffic conditions on the network. This paper proposes a continuous network design program (CNDP) in network equilibrium condition, in order to find optimal congestion toll for maximizing net economic benefit (NEB). The model could be formulated as a bi-level program with continuous variable(congestion toll) such that the upper level problem is for maximizing the NEB in elastic demand, while the lower level is for describing route choice of road users. The bi-level CNDP is intrinsically nonlinear, non-convex, and hence it might be difficult to solve. So, we suggest a heuristic solution algorithm, which adopt derivative information of link flow with respect to design parameter, or congestion toll. Two example networks are used for test of the model proposed in the paper.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.126-134
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• 2015

A sleep disorder is being recognized as one of the major health issues related to high levels of stress. At the same time, interests about quality of sleep are rapidly increasing. However, diagnosing sleep disorder is not a simple task because patients should undergo polysomnography test, which requires a long time and high cost. To solve this problem, an accelerometer embedded wrist-worn device is being considered as a simple and low cost solution. However, conventional methods determine a state of user to "sleep" or "wake" according to whether values of individual section's accelerometer data exceed a certain threshold or not. As a result, a high miss-classification rate is observed due to user's intermittent movements while sleeping and tiny movements while awake. In this paper, we propose a novel method that resolves the above problems by employing a dynamic classifier which evaluates a similarity between the neighboring data scores obtained from SVM classifier. A performance of the proposed method is evaluated using 50 data sets and its superiority is verified by achieving 88.9% accuracy, 88.9% sensitivity, and 88.5% specificity.

• Journal of Korea Trade
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• v.24 no.7
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.