• Journal of the Korean Society for Library and Information Science
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• v.41 no.2
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• pp.237-256
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• 2007

This study examined DEA(Data Envelopment Analysis) and how it measures the efficiency of library units. DEA is a useful nonparametric method to evaluate the relative efficiency of a set of decision making units(DMUs) with multiple inputs and outputs. This study evaluated 102 different public libraries utilizing 4 inputs and 4 outputs focussing on the year 2005. For inefficient libraries, the study analysed the potential improvement and the source of inefficiency comparing the peer groups. The result of this study shows that efficiency of public libraries varies in different localities and forms of operation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6A
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• pp.586-592
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• 2006

In this paper, a novel detection method called the joint multiple frequency cell (JMFC) detection is addressed for spread spectrum code acquisition in the presence of residual Doppler frequency offset (RDFO). When the RDFO exists, the correlation peak used for detection during the acquisition process is split into several lower neighboring peaks, resulting in severe degradation in the detection performance, and consequently, in the overall acquisition performance. In the JMFC detection, a decision variable for detection is formed by combining several consecutive correlator outputs, so that the reduction in the correlation value due to the RDFO can be alleviated. Numerical results show that the proposed scheme can offer better detection performance over the conventional scheme based on the cell-by-cell detection.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.2
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• pp.56-66
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• 2016

Robustness is essential for model based FDI (Fault Detection and Isolation) and it is inevitable to have modeling errors and sensor signal noises during the process of FDI. This study suggests an improved method by applying NARX (Nonlinear Auto Regressive eXogenous) model and Kalman estimator in order to cope with problems caused by linear model errors and sensor signal noises in the process of fault diagnoses. Fault decision is made by the probability of the trend of gradually accumulated errors applying Fuzzy logic, which are robust to instantaneous sensor signal noises. Reliability of fault diagnosis is verified under various fault simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1992-2008
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• 2018

Mobile opportunistic network is a kind of ad hoc networks, which implements the multi-hop routing communication with the help of contact opportunity brought about by the mobility of the nodes. It always uses opportunistic data transmission mode based on store-carry-forward to solve intermittent connect problem of link. Although many routing schemes have been proposed, most of them adopt the greedy transmission mode to pursue a higher delivery efficient, which result in unfairness extremely among nodes. While, this issue has not been paid enough attention up to now. In this paper, we analyzed the main factors that reflect fairness among nodes, modeled routing selection as a multiple attribute decision making problem, and proposed our Fairness-aware Routing Strategy, named FARS. To evaluate the performance of our FARS, extensive simulations and analysis have been done based on a real-life dataset and a synthetic dataset, respectively. The results show that, compared with other existing protocols, our FARS can greatly improve the fairness of the nodes when ensuring the overall delivery performance of the network.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.443-450
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• 2021

The paper investigates the factors that affect the decision of young Chinese consumers to buy high-end cosmetics. The study is based on the responses obtained by questionnaires from 400 respondents in Guangzhou, China. The information was collected and classified on the basis of gender, occupation, age and education in order to understand the main characteristics of the sample in a better way. The purposive, convenient and quota sampling techniques of non-probability sampling method were used. Besides this, the predictive test was carried out with 30 respondents to ensure the reliability and validity of the questionnaires. The data was put to descriptive statistical analysis and multiple regression analysis in order to verify the hypotheses. The data revealed that, while brand awareness does not affect the consumer attitude about the high-end cosmetics, other factors like product involvement, perceived quality, subjective norm, and word-of-mouth have significant effect on consumer's attitude and consumers' intention about high-end cosmetics. The findings of the study show that subjective norm, perceived value, word-of-mouth, and consumer attitude of cosmetic products highly affect consumers purchase intention of high-end cosmetic products. The research paper helps to form concrete and effective marketing strategy based on various aspects of consumer behavior for high-end cosmetics in China.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.85-91
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• 2021

This research aims to analyze the impact of Financial Risk (FR), Information Asymmetric (IA), and Earning Power (EP) on Real Earning Management (REM) of listed trading companies in IDX Indonesia. This study aims to analyze the influence of FR, IA, EP, on REM through Operating Cash Flow, Production expense, and Discretionary Expense. The study employs an unbalanced panel of data set from 2014 to 2018 on the activity of all trading companies (15 in total) as selected samples of 48 feasible samples from 144 existing data. The sample used a non probability sampling method with a purposive sampling technique. This research was classified as causative and tested by multiple linear regression model with cross-sectional analysis. The result indicated a significant impact of FR on REM through PROD and DISX but not through COF. How ever, IA, and EP showed significant impact on REM by means of COF but not go by PROD and DISX..The findings in this study contribute to the users of financial reports particularly the stakeholders in defining the determinants of real earning management practices among firms when it comes to decision making.

• Journal of Distribution Science
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• v.20 no.10
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• pp.93-103
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• 2022

Purpose: This study aims to determine the relationship between disruptive factors and customer satisfaction at chain stores. Survey-based questionnaires were designed in the distribution technique to measure the findings in this study. Research design, data, and methodology: In terms of the sampling technique, the researchers adopted the simple random sampling technique with a total of 200 sample sizes. For the statistical method, the researchers applied multiple linear regression analysis to determine the potential factors that affect customer satisfaction at chain stores. The analysis of this study measured how product quality, pricing policies of chain stores, design and layout, responsiveness, and location of chain stores impart their roles in customer satisfaction. Results: This study found a significant relationship between the product quality and location of chain stores on customer satisfaction. In addition, the responsiveness, pricing policy, and physical design of chain stores impart an insignificant role in customer satisfaction. However, it is proven that the location of chain stores and product quality positively impact customer satisfaction. Conclusions: The study is geographically limited to the region of Karachi, Pakistan. Therefore, the findings may differ in the context of study implications in the other areas.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.508-512
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• 2015

Carbon emission calculation guidelines provided by the Korean Ministry of Land, Infrastructure and Transportation (MOLIT) and existing environmental load assessment studies have suggested a method for estimating based on the volume determined after the design development. Therefore they are not being helpful in the decision making of the environmental economics of road facilities in the planning stage in which specific information on construction output volume is lacking. Based on literature analysis of existing studies and consultation from a group of construction environmental professionals, 12 types of property information considered to be related to environmental load were selected from an inventory of information that will be available in the road planning stage. In addition, multiple regression analysis was performed based on the environmental load computed through the life cycle assessment (LCA) of 40 national highway project cases of Korea to deduce five impact factors of environmental load in the road facilities planning stage.

• ETRI Journal
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• v.45 no.6
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• pp.1022-1034
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• 2023

In this study, the impact of varying lighting conditions on recognition and decision-making was considered. The luminosity approach was presented to increase gesture recognition performance under varied lighting. An efficient framework was proposed for sensor-based sign language gesture identification, including picture acquisition, preparing data, obtaining features, and recognition. The depth images were collected using multiple Microsoft Kinect devices, and data were acquired by varying resolutions to demonstrate the idea. A case study was designed to attain acceptable accuracy in gesture recognition under variant lighting. Using American Sign Language (ASL), the dataset was created and analyzed under various lighting conditions. In ASL-based images, significant feature points were selected using the scale-invariant feature transformation (SIFT). Finally, an artificial neural network (ANN) classified hand gestures using specified characteristics for validation. The suggested method was successful across a variety of illumination conditions and different image sizes. The total effectiveness of NN architecture was shown by the 97.6% recognition accuracy rate of 26 alphabets dataset with just a 2.4% error rate.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.68-82
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• 2024

The planning stage of laser scanning is crucial for acquiring high-quality 3D source data. It involves assessing the target space's environment and formulating an effective measurement strategy. However, existing practices often overlook on-site conditions, with decisions on scanner deployment and scanning locations relying heavily on the operators' experience. This approach has resulted in frequent modifications to scanning locations and diminished 3D data quality. Previous research has explored the selection of optimal scanner locations and conducted preliminary reviews through simulation, but these methods have significant drawbacks. They fail to consider scanner inaccuracies, do not support the use of multiple scanners, rely on less accurate 2D drawings, and require specialized knowledge in 3D modeling and programming. This study introduces an optimization technique for laser scanning planning using 3D simulation to address these issues. By evaluating the accuracy of scan data from various laser scanners and their positioning for scanning a retaining wall structure in a small-scale building, this method aids in refining the laser scanning plan. It enhances the decision-making process for end-users by ensuring data quality and reducing the need for plan adjustments during the planning phase.