• Food Science and Biotechnology
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• v.18 no.3
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• pp.745-748
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• 2009

Sensory quality variations of jajang sauce were monitored by the $\bar{X}-chart$ and capability analysis based on specifications of each sensory attributes. For sensory quality control (QC) of the sauce which has a strong sweetness and sourness, the ratio of sourness/sweetness was examined as a necessary QC factor to maintain the balance of sweetness and sourness. For the sensory QC factors, all the sensory data were divided into individual sensory score of reference which was a pack of sauce manufactured a week ago. The ratio form of sensory data was useful for decreasing individual variations and for increasing normality of data measured by category scale. The overall proportion of out-spec products under normal manufacturing conditions was obtained by capability analysis of sensory data with normal distribution. Out-spec samples were monitored by the $\bar{X}-chart$ of each sensory attributes.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.383-386
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• 1993

In this paper, we propose a sensory data combination method by a fuzzy number approach for multisensor data fusion. Generally, the weighting of one sensory data with respect to another is derived from measures of the relative reliabilities of the two sensory modules. But the relative weight of two sensory data can be approximately determined through human experiences or insufficient experimental data without difficulty. We represent these relative weight using appropriate fuzzy numbers as well as sensory data itself. Using the relative weight, which is subjective valuation, and a fuzzy-numbered sensor data, the fuzzy weighted average method is used for a representative sensory data. The manipulation and calculation of fuzzy numbers can be carried out using the Zadeh's extension principle which can be approximately implemented by the $\alpha$-cut representation of fuzzy numbers and interval analysis.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.65-75
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• 2019

Sensory substitution involves mapping the characteristics of one sensory modality to the stimuli of another sensory modality. In general, when a person is visually impaired or deaf, they do not actually lose their ability to see or hear completely; however, they only lose their ability to transmit sensory signals from the periphery to the brain. It has been experimentally proven that a person who has lost the ability to retrieve data from the retina can still visualize subjective images by using data transferred from other sensory modalities such as tactile or auditory modalities. This is because vision processing pathways are still intact in most cases. Therefore, sensory substitution uses human perception and the plasticity of the human brain to transmit sensory signals through pathways that have not been lost. In this study, we analyze the characteristics and problems of various devices used for sensory substitution and summarize the recent technological trends in these devices.

• Journal of the Korean Society of Food Culture
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• v.35 no.2
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• pp.193-200
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• 2020

This study was conducted to understand the sensory characteristics and consumer acceptance for the commercially available clear broth for noodles. Totally, eight different clear broth samples were evaluated in this study. Seven trained panelists developed and evaluated sensory characteristics in the descriptive analysis. Significant differences (p<0.05) were obtained for all 28 attributes evaluated. Descriptive data was obtained by performing multivariate analysis of variance to identify differences between samples. Principal component analysis (PCA) was performed on the mean values of descriptive attributes obtained in the descriptive analysis, and summarizes the sensory characteristics of clear broth for noodles. PCA of the clear broths revealed that the first two principal components are responsible for 80.66% variations. For sensory testing, 160 consumers were recruited, and their acceptance for each sample was assessed. Consumer data was obtained by applying partial least square-regression (PLSR) to establish the relationship between the descriptive data and the consumer acceptance data.

• Journal of the Korean Society of Tobacco Science
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• v.22 no.2
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• pp.184-189
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• 2000

This study was conducted to develop the objective evaluation method for tobacco smoke. The evaluation was carried out by using the data of cut or blended tobacco components, smoke components, electric nose system (ENS), and sensory test. By using the statistical methods, such as cluster analysis, discriminant analysis, factor analysis, correlation analysis, and multiple regression analysis, the relationship among the data of tobacco, smoke, ENS, and sensory evaluation was studied. By the results of cluster analysis, the data from smoke analysis by GC and ENS were able to select the difference of tobacco leaf characteristics. As the results of discriminant analysis, grouping by the components of tobacco leaves and smoke was possible and the results of GC analysis of smoke could be used for discrimination of tobacco leaves. In the results of factor analysis, nicotine, tar, CO, puff No and pH in the smoke were the factors effecting on the tobacco leaf characteristics. From the correlation analysis, aroma, taste, irritation, and smoke volume of sensory test had high relation to tar, p-cresol threonolatone, levoglucosane, and quinic acid- ${\gamma}$ -lactone of smoke. The ENS data showed high efficiency for discriminant analysis and cluster analysis, but it was not good for factor analysis, and correlation analysis. It was possible to estimate tobacco leaves and their blending characteristics by the analytical data of tobacco leaves, smoke, ENS, and sensory test results. By the multiple regression analysis, some correlation among selected chemical components and sensory evaluation were found. This study strongly indicated that the some chemical analysis data was available for the objective evaluation of tobacco sensory attributes.

• Electronics and Telecommunications Trends
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• v.33 no.6
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• pp.69-80
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• 2018

Sensory devices have been developed to help people with disabled or weakened sensory functions. Such devices play a role in collecting and transferring data for the five senses (vision, sound, smell, taste, and tactility) and also stimulating nerves. To provide brain or prosthesis devices with more sophisticated senses, hyper sensory devices with a high resolution comparable to or even better than the human system based on individual neuron cells are essential. As for data collecting components, technologies for sensors with higher resolution and sensitivity, and the conversion of algorithms from physical sensing data to human neuron signals, are needed. Converted data can be transferred to neurons that are responsible for human senses through communication with high security, and neural interfaces with high resolution. When communication deals with human data, security is the most important consideration, and intra-body communication is expected to be a candidate with high priority. To generate sophisticated human senses by modulating neurons, neural interfaces should modulate individual neurons, and therefore a high resolution compared to human neurons (~ several tens of um) with a large area covering neuron cells for human senses (~ several tens of mm) should be developed. The technological challenges for developing sensory devices with human and even beyond-human capabilities have been tackled by various research groups, the details of which are described in this paper.

• Smart Structures and Systems
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• v.8 no.1
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• pp.107-117
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• 2011

Biological sensory systems continuously monitor and analyze changes in real-world environments that are relevant to an animal's specific behavioral needs and goals. Understanding the sensory mechanisms and information processing principles that biological systems utilize for efficient sensory data acquisition may provide useful guidance for the design of smart-sensing systems in engineering applications. Weakly electric fish, which use self-generated electrical energy to actively sense their environment, provide an excellent model system for studying biological principles of sensory data acquisition. The electrosensory system enables these fish to hunt and navigate at night without the use of visual cues. To achieve reliable, real-time task performance, the electrosensory system implements a number of smart sensing strategies, including efficient stimulus encoding, multi-scale virtual sensor arrays, task-dependent filtering and online subtraction of sensory expectation.

• The Journal of Korean Academy of Sensory Integration
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• v.7 no.1
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• pp.1-12
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• 2009

Objective : This study is to verify effect of a sensory integration (SI) intervention on sensory processing of children with sensory modulation disorder (SMD), and to explore how the SI intervention affect play, socialization, occupational performance and occupational satisfaction of those children. Method : Five children with developmental disabilities living in metropolitan were diagnosed as SMD by the Sensory History Interview (SHI) and Short Sensory Profile (SSP). The SMD children undergone the 48 sessions of 50 min intervention twice in a week for six months and took the Revised Knox Preschool Play Scale(RKPPS), Social maturity test, Canadian Occupational Performance Measure(COPM), and Japanese Sensory Inventory Revised(JSI-2) before- and after the intervention. The result data analyzed by the Wilcoxon matched-pair signed rank test. Results : All data of post-intervention differed significantly; RKPPS(Z=-2.023, p=.043), Social maturity test(Z=-2.023, p=.043); occupational performance(Z=-2.023, p=.043); satisfaction(Z=-2.032, p=.042); and tactile system of JSI-2(Z=-2.032, p=.042). Conclusions : The results advocate that sensory integration intervention is effective in improving tactile processing, play, socialization, occupational performance, and occupational satisfaction of child with SMD. It is found that sensory integration intervention improves not only one's occupational performance but also underlying components of the performance. In order to generalize this conclusion, further studies need to be done with more number of subjects and consideration of environmental factors. Striving for more reliable and valid methods of data collection is also suggested.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.1 s.53
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• pp.134-140
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• 2005

The purpose of this study was the discrimination of different tobacco types by the E-Nose/tongue and the analysis of what human sensory attributes are correlated with e-instrument's sensors. Samples were made from five groups of Korean domestic tobacco leaves, aged burley and not aged, aged flue-cured and not aged and blending types of the four. Instrumental tests were conducted to discriminate characteristics among different tobacco samples by the E-Nose and the E-Tongue. Sensory attributes of tobacco tastes were impact, irritation, bitterness, hay-like, tobacco taste, smoke volume, smoke pungent and mouth cleanness. STATISTICA software was used to analyze correlation between the human sensory data and the raw data of e-instruments. Discrimination analysis can be achieved using principal components analysis (PCA) and discriminant factorial analysis(DFA). As a result, impact, bitterness, irritation, smoke volume and smoke pungent of human sensory attributes were correlated with data from the several clustered E-Nose sensors(p < 0.10). And bitterness, irritation, and smoke pungent of human sensory attributes were correlated with data from the E-Tongue sensors(p < 0.10). PCA plot by the E-Nose shows that aged tobacco and not aged were discriminated and DFA plot shows that three groups(aged burley, not aged burley and flue-cured) were discriminated. PCA plot by the E- Tongue shows that flue-cured tobacco was separated from burley. Our results indicated that the e-instruments are sensitive enough to distinguish among tobacco types and their several sensors are reacted to the human sensory attributes.

• Korean Journal of Geomatics
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• v.4 no.2
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• pp.39-45
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• 2004

Building reconstruction attempts to generate geometric and radiometric models of existing buildings usually from sensory data, which have been traditionally aerial or satellite images, more recently airborne LIDAR data, or the combination of these data. Extensive studies on building reconstruction from these data have developed some competitive algorithms with reasonable performance and some degree of automation. Nevertheless, the level of details and completeness of the reconstructed building models often cannot reach the high standards that is now or will be required by various applications in future. Hence, the use of terrestrial sensory data that can provide higher resolution and more complete coverage has been intensively emphasized. We developed a fusion framework for building reconstruction from terrestrial sensory data, that is, points from a laser scanner, images from digital camera, and absolute coordinates from a total station. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large complex existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS with reasonable resources.