• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
• /
• v.28 no.1
• /
• pp.39-46
• /
• 2022

This study compared the effects of cocopeat and perlite growth media on the storability and quality of sweet pepper fruit stored using modified atmosphere packages (MAP) and carton boxes. The fruits were stored at 8℃ for 35 and 30 days, respectively. Perlite-grown fruits had a significantly lower size at harvest due to the medium's inability to hold plenty of water during the growing stage. Contrary to what is expected for small fruits, the result shows box-stored perlite-grown fruits to have lower weight loss and a longer shelf life than cocopeat-grown fruits, while MAP fruits have indifference. Perlite fruits also had a higher quality in terms of dry matter, soluble solids, and vitamin C, while box-stored fruits had a better visual quality. As expected, respiration and ethylene production rates were high, and fruits had similar after-storage firmness values. Based on the findings, perlite-grown sweet pepper fruits may have a better quality and give preference in a box storage condition.

• Journal of the Korean Wood Science and Technology
• /
• v.51 no.3
• /
• pp.173-182
• /
• 2023

Color is an attribute of visual perception and can be an important factor that affects the preference of customers toward bamboo and wood products. Solar radiation can discolor bamboo surfaces and initiate cracking. The purpose of this study is to investigate the effects of an ultraviolet (UV)-protective coating on the photodiscoloration of untreated and heat-treated Phyllostachys bambusoides bamboo surfaces. Artificial UVA radiators are set at a UVA irradiance of 2,000 W/m² to accelerate the aging of the outer surfaces of hot-air-dried and heat-treated bamboo samples. Half of the samples are coated with transparent UV-protective paint. As the UVA radiation progresses, the discoloration prevention efficiency (DPE) of the UV-protective coating on all samples decreases gradually. The DPEs of the hot-air-dried samples are estimated to be 31.4% and 18.8% after 21 and 72 hours of artificial UVA radiation, respectively. The heat-treated samples exhibit similar trends (29.0% after 21 hours and 10.3% after 72 hours). Recoating the UV-protective paint periodically every six months is expected to minimize the discoloration of the bamboo's outer surface.

• Asian-Australasian Journal of Animal Sciences
• /
• v.32 no.12
• /
• pp.1923-1932
• /
• 2019

Objective: We investigated visual marbling level (VML) influence on pork loin physicochemical traits, consumer palatability responses, VML liking, purchase intent, and their relationships. Methods: For each of five slaughtering dates, at 24-h postmortem, nine paired Duroc castrated male boneless Longissimus dorsi (LD) muscles were categorized into low (LM, score 1 to 2, n = 3), medium (MM, score 3 to 4, n = 3), and high (HM, score 5 to 6, n = 3) VML. Meat physicochemical quality traits and consumer responses (n = 389) on palatability and VML liking, and purchase intent were evaluated. The experiment was in randomized complete block design. Analysis of variance, Duncan's multiple mean comparisons, and correlation coefficients were determined. Results: VML correspond to crude fat (r = 0.91, p<0.01), but both were reversely related to moisture content (r = -0.75 and -0.91, p<0.01, respectively). As VML increased, ash (p<0.05) and protein (p = 0.072) decreased, pH and $b^{\star}$ increased (p<0.05), but drip, cooking (p<0.05) and thawing (p = 0.088) losses decreased. Among treatments, muscle fiber diameter, sarcomere length, total and insoluble collagen contents, $L^{\star}$, and $a^{\star}$ did not differ (p>0.05). Compared to the others, HM had lower collagen solubility percentage (p<0.05), but similar (p>0.05) Warner-Bratzler shear force (WBSF). No differences (p>0.05) were found in juiciness, overall flavor, oiliness, and overall acceptability, but HM was more tender (p<0.05) than the others. Based on VML, consumers preferred MM to HM (p<0.05), while LM was similar to MM and HM (p>0.05). Corresponding to VML preference (r = 0.45, p<0.01), consumers (83%) would (p<0.01) definitely and probably buy MM, over LM (74%), and HM (68%), respectively. Conclusion: Increasing VML in pork LD altered its chemical composition, slightly increased pH, and improved water holding capacity, thereby improving its tenderness acceptability. Marbling might reduce chewing resistance, as lower collagen solubility in HM did not impact tenderness acceptability and WBSF. While HM was rated as most tender, consumers visually preferred and would purchase MM.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.1
• /
• pp.19-30
• /
• 2021

This research studied the effect of visual improvement of "72 Hour Project" that has regenerated small scale derelict spaces in Seoul through citizen participation. 29 projects built form 2016 to 2019 were analyzed. The research analyzed landscape image preference of before and after status of projects using 12 pairs of landscape adjectives. Basic statistical analysis, correlation analysis, factor analysis, cluster analysis, and ANOVA were performed based on the survey results. Since the satisfaction level of the projects compared with the before-condition was 3.63 higher than 3.00, it could be concluded that there was an meaningful effect of visual improvement after completion of the projects. As the result of the factor analysis, landscape adjective pairs were categorized into two factors: harmony and aesthetics. Through the cluster analysis, four clusters were formed and characteristics of each cluster were identified. As the result of rhe cluster analysis, the cluster with the high harmony level and the aesthetics level showed the highest overall satisfaction level. Comparing each cluster, it could be concluded that the factor of harmony was more important than the factor of aesthetics in evaluating the satisfaction level of projects. Analyzing qualitative aspects of project groups, spatially well-balanced design with generous vegetation areas was more effective in landscape improvement than artistic design with visually strong installations. Further researches based on behavior studies of actual users are required to compensate the limits of this research. This research can contribute to establish the improved direction of policies to regenerate various types of small scale derelict spaces.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.85-109
• /
• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.107-120
• /
• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Journal of the HCI Society of Korea
• /
• v.8 no.2
• /
• pp.9-19
• /
• 2013

There has been much advancement in reality enhancement using audio-visual information. On the other hand, there is little research on provision of olfactory information because smell is difficult to implement and control. In order to obtain necessary basic data when intend to provide smell for video reality, in this research, we investigated user perception of smell in diverse videos and then classified the videos based on the collected user perception data. To do so, we chose five main questions which were 'whether smell is present in the video'(smell presence), 'whether one desire to experience the smell with the video'(preference for smell presence with the video), 'whether one likes the smell itself'(preference for the smell itself), 'desired smell intensity if it is presented with the video'(smell intensity), and 'the degree of smell concreteness'(smell concreteness). After sampling video clips of various genre which are likely to receive either high and low ratings in the questions, we had participants watch each video after which they provided ratings on 7-point scale for the above five questions. Using the rating data for each video clips, we constructed scatter plots by pairing the five questions and representing the rating scale of each paired questions as X-Y axes in 2 dimensional spaces. The video clusters and distributional shape in the scatter plots would provide important insight into characteristics of each video clusters and about how to present olfactory information for video reality.

• Journal of Korean Ophthalmic Optics Society
• /
• v.18 no.2
• /
• pp.149-156
• /
• 2013

Purpose: The aim of this study was to determine a suitable type and size of Hangul fonts for printed materials in the presbyopic age. Methods: Based on the most common Hangul fonts used today, three types of fonts were used Hamchrombatang, Sinmoonmyungjo and Sinmyungjo at small font sizes in the range 9-11 point (pt). Subjects were 101 volunteers aged 41 through 85 years. Near visual acuity (VA) was corrected to read VA 0.5 at 40 cm after distance correction. The subjects were asked to read words containing 88 characters in 10 pt after a question about preference. Readability was assessed by reading rate that was calculated as the number of words read correctly in one minute (words per minute, wpm). Results: The most preferred font type was Simmyungjo at small font sizes. Although preferred font sizes were different in each font type, Sinmyungjo was generally preferred at 10 pt more than other fonts. Hamchrombatang and Sinmyungjo were read significantly faster than Sinmoonmyungjo. There was a weak negative relationship between readability and age in Sinmyungjo. In comparing between the top 10% and the bottom 10% group sorted by reading rate, the top group showed lower average age and addition than the bottom group, however there were no significant differences in reading rate among the fonts. Conclusions: Although increasing age tends to be low in readability for Sinmyungjo, in the light of preferred font and readability, it is recommended to use a 10 pt Sinmyungjo font in printed materials for the presbyopic age.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.40 no.4
• /
• pp.18-27
• /
• 2012

This paper proposes a management method for a coastal black pine forest landscape considering the parallax effect. For the study, 10 coastal black pine forests in Gangneung were investigated about the average width of the coastal forests, the average diameters, and the intervals of the pines. Categorizations were realized for the 3 types of scene(sea, field, mountain, residential area, commercial area), diameter(16cm, 22cm, 28cm) and interval(5m, 7m, 10m) to produce a total of 45 scenic simulations. An investigation was made on the scenic preferences using 45 simulation images with S.D, and Likert Scales. The results were as follows: According the comparison of scenic preferences, natural landscapes(sea, field, and mountain) ranked high among preferences, with fabricated landscapes(residential area, commercial area) ranked low. The highest scenic preferences were shown with the seascape and an interval of 7m between the trees. On the contrary, the interrelationship was very low between the visual quantity of the scenic's elements(green, sky, building, road etc.) and the scenic preferences. As the results of the factor analysis, the 3 sense factors of "Depth(78.0%)" "Diversity(l5.6%)" and "Spatiality(6.4%)" explained coastal scenic preferences. "Spatiality" showed significant differences at intervals of 5~7m, and 10m between trees. This shows coastal forest management based on the interval of 10m standard affecting scenic preference.

• Clinics in Shoulder and Elbow
• /
• v.18 no.3
• /
• pp.120-127
• /
• 2015

Background: We prospectively compared the response to blind and ultrasound-guided glenohumeral injection of corticosteroids for treatment of shoulder stiffness. Methods: A total of 77 patients with shoulder stiffness between April 2008 and March 2012 were recruited. Patients were randomized to receive either a blind (group 1, n=39) or ultrasound-guided (group 2, n=38) glenohumeral injection of 40 mg triamcinolone. The clinical outcomes and shoulder range of motion (ROM) before injection, at 3, 6, and 12 months after injection and at the last follow-up were assessed. The same rehabilitation program was applied in both groups during the follow-up period. Results: There was no significant difference in demographic data on age, sex, ROM, and symptom duration before injection between groups (p>0.05). There were no significant differences in ROM including forward flexion, external rotation at the side, external rotation at $90^{\circ}$ abduction, and internal rotation, visual analogue scale for pain and functional outcomes including American Shoulder and Elbow Surgeons score, Simple Shoulder test between the two groups at any time point (p>0.05). Conclusions: Based on the current data, the result of ultrasound-guided glenohumeral injection was not superior to that of blind injection in the treatment of shoulder stiffness. We suggest that ultrasound-guided glenohumeral injection could be performed according to the patient's compliance and the surgeon's preference. Once familiar with the non-imaging-guided glenohumeral injection, it is an efficient and reliable method for the experienced surgeon. Ultrasound could be performed according to the surgeon's preference.