• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.857-870
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• 2010

This study was conducted to investigate the relationship between the socio-demographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data from 2006 to 2008 by National Institute of Animal Science. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender occupation, monthly income, beef cut and the the palatability grade as the categorical dependent variable and tenderness, 리avor and juiciness as the continuous dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to nd the associations between categories.

• Food Engineering Progress
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• v.14 no.1
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• pp.75-79
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• 2010

Partial least square regression (PLSR) was executed on curve data of force-deformation from back extrusion test and sensory data for commercial instant noodles. Sensory attributes considered were hardness (A), springiness (B), roughness (C), adhesiveness to teeth (D), and thickness (E). Eight and two kinds of fried and non-fried instant noodles respectively were used in the tests. Changes in weighted regression coefficients were characterized as three stages: compaction, yielding, and extrusion. Correlation coefficients appeared in the order of E>D>A>B>C, root mean square error of prediction D>C>E>B>A, and relative ability of prediction D>C>E>B>A. Overall, 'D' was the best in the correlation and prediction. 'A' with poor prediction ability but high correlation was considered good when determining the order of magnitude.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.98-105
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• 2021

The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.2
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• pp.323-338
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• 1994

This paper outlines a framework for performing intelligent sensor validation for a diagnostic expert system while reasoning under uncertainty. The emphasis is on the algorithmic preprocess technique. A companion paper focusses on heuristic post-processing. Sensor validation plays a vital role in the ability of the overall system to correctly detemine the state of a plant monitored by imperfect sensors. Especially, several theoretical developments were made in understanding uncertain sensory data in statistical aspect. Uncertain information in sensory values is represented through probability assignments on three discrete states, "high", "normal", and "low", and additional sensor confidence measures in Algorithmic Sv.Upper and lower warning limits are generated from the historical learning sets, which represents the borderlines for heat rate degradation generated in the Algorithmic SV initiates a historic data base for better reference in future use. All the information generated in the Algorithmic SV initiate a session to differentiate the sensor fault from the process fault and to make an inference on the system performance. This framework for a diagnostic expert system with sensor validation and reasonig under uncertainty applies in HEATXPRT$^{TM}$, a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants.

• Korean Journal of Food Science and Technology
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• v.40 no.2
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• pp.160-165
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• 2008

This study was conducted to analyze sensory profiles of commercial sojues using a standardized sensory evaluation procedure, and to investigate the effects of sensory characteristics and brands on consumer liking for soju. Descriptive analysis and consumer taste testing were conducted for seven commercial sojues. For the descriptive analysis, eight panelists generated and evaluated 12 flavor and one pain-sensation attributes for the soju, and there were significant differences among the soju samples for all the 13 sensory attributes. For the descriptive data, principal component analysis was performed to summarize the sensory characteristics of the sojues. For the consumer testing, 224 soju drinkers (20-29 year-olds) were recruited and randomly divided into two groups; a blind group and a group with the knowledge of brand. While the hedonic ratings obtained from the blind group didn't indicate significant differences among the sojues, the ratings obtained from the brand-informed group showed significant differences. Finally, the individual preferences of the 112 consumers in each group were investigated by preference mapping techniques.

• The Journal of Korean Academy of Sensory Integration
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• v.20 no.3
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• pp.60-71
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• 2022

Objective : This study aimed to summarize and present the effects of group sensory integration treatment applied to children with and without disabilities in Korea. Methods : The search period was from January 2010 to December 2021, and databases of 'The Journal of Korean Academy of Sensory Integration', 'The Korean Journal of Occupational Therapy', 'Koreanstudies Information Service System', 'Research Information Sharing Service', 'DBpia' were used for data search. A total of 11 studies were selected, and the Patient, Intervention, Comparison, Outcome method was applied to organize them systematically. Results : As a result of the study, single-group non-randomized studies were the most common with 8 out of 11 studies (72.73%). There were 99 subjects, ranging in age from 3 to 11, and an average of 7.39. Among them, there were more children with disabilities, and 40 out of 99 (40.41%) were diagnosed with developmental disabilities the most. A total of 5 to 45 treatment intervention sessions were provided, and 60 minutes were the most frequently provided once or twice a week. The Canadian Occupational Performance Measure and The Penn Interactive Peer Play Scale were the most commonly used evaluation tools in 4 times each (12.90%). As the treatment intervention goal, social interaction skills was the most common with 8 studies (36.36%). As a result of treatment intervention, 8 studies showed significant results. Conclusion : Based on this study, it is expected that in the future, various methods of intervention of sensory integration therapy based on high quality levels can be systematically presented and used as useful information in clinical practice.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2354-2360
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• 2009

Healthcare is a field where ubiquitous computing is most widely used. We propose a mining-based healthcare multi-agent system for ubiquitous computing environments. This proposed scheme select diagnosis patterns using mining in the real-time biosignal data obtained from a patient's body. In addition, we classify them into normal, emergency and be ready for an emergency. This proposed scheme can deal with the enormous quantity of real-time sensing data and performs analysis and comparison between the data of patient's history and the real-time sensory data. We separate Association rule exploration into two data groups: one is the existing enormous quantity of medical history data. The other group is real-time sensory data which is collected from sensors measuring body temperature, blood pressure, pulse. Proposed system has advantage that can handle urgent situation in the far away area from hospital through PDA and mobile device. In addition, by monitoring condition of patient in a real time base, it shortens time and expense and supports medical service efficiently.

• Food Science of Animal Resources
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• v.29 no.1
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• pp.132-139
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• 2009

The objective of this study was to investigate the most effective analysis methods for palatability grading of Hanwoo beef by comparing the results of discriminant analysis with sensory data. The sensory data were obtained from sensory testing by 1,300 consumers evaluated tenderness, juiciness, flavor-likeness and overall acceptability of Hanwoo beef samples prepared by boiling, roasting and grilling cooking methods. For the discriminant analysis with one factor, overall acceptability, the linear discriminant functions and the non-parametric discriminant function with the Gaussian kernel were estimated. The linear discriminant functions were simple and easy to understand while the non-parametric discriminant functions were not explicit and had the problem of selection of kernel function and bandwidth. With the three palatability factors such as tenderness, juiciness and flavor-likeness, the canonical discriminant analysis was used and the ability of classification was calculated with the accurate classification rate and the error rate. The canonical discriminant analysis did not need the specific distributional assumptions and only used the principal component and canonical correlation. Also, it contained the function of 3 factors (tenderness, juiciness and flavor-likeness) and accurate classification rate was similar with the other discriminant methods. Therefore, the canonical discriminant analysis was the most proper method to analyze the palatability grading of Hanwoo beef.

• The Journal of Korean Academy of Sensory Integration
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• v.1 no.1
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• pp.17-23
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• 2003

Objective : The purpose of this study is to identify the developmental characteristics of sensory integration according to age and sex distinction using COMPS for school-aged children and to provide the preparatory data for standardization appropriate for our social and cultural environment. Methods : The COMPS was administered to 40 normal children in the first grade of elementary school by 4 occupational therapists. Results : By comparison between age groups, 6 and 7 year olds performed similarly and statistically in all items. Between males and females, there was no significant difference in performance of all items Conclusion : Findings from the study suggested that the performance of the COMPS by children followed developmental trends. The COMPS is easy to administer to groups and beneficial to discriminate children with motor problems, and it should be standardized.

• Journal of the East Asian Society of Dietary Life
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• v.18 no.2
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• pp.172-180
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• 2008

The purpose of this study was to measure the causal relationships among food involvement, health, mood, convenience, sensory appeal, weight control, and fruit consumption. A total of 290 questionnaires were completed. A structural equation model was used to measure the causal effects of the constructs, and the structural analysis results for the data indicated an excellent model fit. The effects of food involvement on health, mood, convenience, sensory appeal, weight control, and fruit consumption were statistically significant. As expected, health, mood, and weight control had significant effects on fruit consumption. Moreover, food involvement had a significant indirect effect on fruit consumption through health, mood, convenience, sensory appeal and weight control. For the future development and testing of conceptual models that integrate the relationships among personality traits, food choice motives, and fruit consumption, this study may approach a deeper understanding of the complex relationships among fruit consumption behavior-related variables. Greater understanding of these complex relationships can improve the managerial diagnosis of the problem and opportunities for different marketing strategies, including fruit production and fruit product development and marketing communications.