• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.8
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• pp.1265-1273
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• 2002

The purposes of this study were to examine online store attributes sought and evaluated by online shoppers and to compare those attributes with those of off-line stores. Data were obtained from an online questionnaire survey to 850 online shoppers who were randomly selected from the panel of an online survey agency, and 615 responses were analyzed. The t-tests revealed that there were significant differences on store attributes sought and evaluated by shoppers between online and off-line stores. Price related attributes (i.e., low price and reasonable price) and store name were more important for online stores while product related attributes (i.e., assortment, fashion, and brand) were more for off-line stores. Price related attributes, promotion, and entertainment were highly evaluated on online stores while product related attributes and service were on off-line stores.

• Journal of Integrative Natural Science
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• v.14 no.2
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• pp.35-40
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• 2021

In this paper, we proposed a multi-subject-level sentiment analysis model for user reviews using the Latent Dirichlet Allocation (LDA) method targeting user-generated content (UGC). Data were collected from users' online reviews of hotels in major tourist cities in the world, and 30 hotel-related topics were extracted using the entire user reviews through the LDA technique. Six major hotel-related themes (Cleanliness, Location, Rooms, Service, Sleep Quality, and Value) were selected from the extracted themes, and emotions were evaluated for sentences corresponding to six themes in each user review in the proposed sentiment analysis model. Sentiment was analyzed using a dictionary. In addition, the performance of the proposed sentiment analysis model was evaluated by comparing the emotional values for each subject in the user reviews and the detailed scores evaluated by the user directly for each hotel attribute. As a result of analyzing the values of accuracy and recall of the proposed sentiment analysis model, it was analyzed that the efficiency was high.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.12 no.1
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• pp.17-21
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• 2001

Aims of study : The purpose of this study is to measure the chronic and daily voice burden of the professionals in their actual working places. These will be a valuable guideline for preventing and controlling the voice production of professionals. Material and method : Our study was selected to the 10 female telephone operators in the Asan Medical Center, ages ranging from 22 to 38 years old. The symptoms and acoustic analysis of both telephone operators and the controls were evaluated before and after their working. The symptoms were evaluated with questionaires, and the acoustic analysis was measured by using CSL (computerized speech laboratory) system. Results : The symptoms of the professional voice abusers are same as those symptoms in laryngeal fatigue. The acoustic analysis before their working were significantly increased in jitter and shimmer, in comparison with the data of the control. This shows that the experimental group is exposed to the chronic burden of voice production. The jitter, shimmer, and NHR after their working are significantly increased in comparison with the data of the acoustic analysis before their working. This also shows that the experimental group is exposed to the daily burden of voice production. Conclusion : The acoustic analysis of the professional voice overusers has objectively measured that there are chronic and daily overloading to the voice of operators, and these will be a valuable data for preventing and controlling the professionals that abuse their voice.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.599-602
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• 2003

A new technique is presented to construct predictive models of plasma etch processes. This was accomplished by combining a backpropagation neural network (BPNN) and a random generator (RC). The RG played a critical role to control neuron gradients in the hidden layer, The predictive model constructed in this way is referred to as a randomized BPNN (RG-BPNN). The proposed scheme was evaluated with a set of experimental plasma etch process data. The etch process was characterized by a 2$^3$ full factorial experiment. The etch responses modeled are 4, including aluminum (Al) etch rate, profile angle, Al selectivity, and do bias. Additional test data were prepared to evaluate model appropriateness. The performance of RC-BPNN was evaluated as a function of the number of hidden neurons and the range of gradient. for given range and hidden neurons, 100 sets of random neuron gradients were generated and among them one best set was selected for evaluation. Compared to the conventional BPNN, the proposed RC-BPNN demonstrated about 50％ improvements in all comparisons. This illustrates that the RG-BPNN of multi-valued gradients is an effective way to considerably improve the predictive ability of current BPNN of single-valued gradient.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.130-139
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• 2011

In this paper, vehicle tracking algorithm using hue transformation in HIS color model is proposed. the proposed algorithm is installed on the road of the two horizontal virtual data sampling lines. The difference images are detected between the frame and the frame, respectively and also detected in the vehicle by using the hue color distribution to determine identity and lane changes. To examine the effectiveness of proposed algorithm, identification and velocity measurement for driving vehicle are evaluated. this evaluated results is shown by hue data of vehicle passing of two virtual data sample lines, and the velocity measurement for driving vehicle is less than 0.4% comparing with existing vehicle speed meter system.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• Nuclear Engineering and Technology
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• v.28 no.1
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• pp.72-78
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• 1996

A computer program COVAFIT has been developed and applied to the evaluation of experimental cross sections for MeV energy incident particles. The program utilizes weighted least-square linear regression method with high-order polynomials derived in this study. Meeting the growing demand for the treatment of covariances in nuclear data, it deals with the variance and covariance data provided along with experimental cross sections and yields those for the evaluated ones. The evaluated results on two sets of neutron total cross section of oxygen and three sets of proton cross section for $C^{11}$ production reactions confirm the methodology formulated in and the applicability of the program.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.109-120
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• 2021

Despite the growing online exposure of retailes, offline retail channels still outperform online channels in the total retail volume of some countries. There is much interest in the physical layout plans of retail stores to expand sales. Product placement that have a large impact on customer purchasing behavior at offline retailers influences customer movement and sales volume. But in many cases, each retailer relies on unsystematic and autonomous product placement. When multiple products are sold with one purchase, the customer's movement for shopping may be evaluated in terms of customer efficiency and additional impulse purchase. In this paper, the social network is applied to sales data of a retail store and the result is used for evaluation of product placement and customer path. The frequent sales product composition was identified using k-core from sales data in the form of shopping baskets. The location was checked for the identified compositions of products, the spatial variance was measured and the customer's path was identified. With these results, the store arrangement of products was evaluated with appropriate improvement directions. The analysis method of this paper can be an alternative analysis approach for better layout of retail stores.

• Smart Structures and Systems
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• v.30 no.1
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• pp.35-47
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• 2022

Data-driven engineering is crucial for information delivery between design, fabrication, assembly, and maintenance of prefabricated structures. Design for manufacturing and assembly (DfMA) is a critical methodology for prefabricated bridge structures. In this study, a novel concept of digital engineering model that combined existing knowledge of DfMA with object-oriented parametric modeling technologies was developed. Three-dimensional (3D) geometry models and their data models for each phase of a construction project were defined for information delivery. Digital design models were used for conceptual design, including aesthetic consideration and possible variation during fabrication and assembly. The seismic performance of a bridge pier was evaluated by linking the design parameters to the calculated moment-curvature curves. Control parameters were selected to consider the tolerance control and revision of the digital models. Digitalized fabrication of the prefabricated members was realized using the digital fabrication model with G-code for a concrete printer or a robot. The fabrication error was evaluated and the design digital models were updated. The revised fabrication models were used in the preassembly simulation to guarantee constructability. For the maintenance of the bridge, the as-built information was defined for the prefabricated bridge piers. The results of this process revealed that data-driven information delivery is crucial for lifecycle management of prefabricated bridge piers.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2445-2453
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• 2021

Since the nuclear data forms a vital component in reactor physics computations, the nuclear community needs processing codes as tools for translating the Evaluated Nuclear Data Files (ENDF) to simulate nuclear-related problems such as an ACE format that is used for MCNP. Errors, inaccuracies or discrepancies in library processing may lead to a calculation that disagrees with the experimentally measured benchmark. This paper provides an overview of the processing and preparation of ENDF/B-VIII.0 incident neutron data with NECP-Atlas and NJOY codes for implementation in the MCNP code. The resulting libraries are statistically inter-compared and tested by conducting benchmark calculations, as the mutualcomparison is a source of strong feedback for further improvements in processing procedures. The database of the benchmark experiments is based on a selection taken from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP handbook) and those proposed by Russell D. Mosteller. In general, there is quite good agreement between the NECP-Atlas1.2 and NJOY21^(1.0.0.json) results with no substantial differences, if the correct input parameters are used.