• Food Engineering Progress
• /
• v.13 no.4
• /
• pp.297-301
• /
• 2009

This study was performed to develop a prediction model of sugar content for strawberry. Near-infrared (NIR) spectroscopy has been prevailed for on-line and portable applications for non-invasive quality assessment of intact fruit. This work presents effects of illumination method and coating of reflection surface of light source on prediction result of sugar content. Effect of preprocessing methods was also examined. A low-cost commercially available VIS/NIR spectrometer was used for estimation of total soluble solids content (Brix). To predict sugar contents of strawberry, the best results were obtained with the spectrum data measured under intensive illuminations at three locations induced from the light source with fiber optic bundles. Gold coating of reflection surface of light source lamp gave favorable effect to prediction result. The best results in validation of PLSR model were $r_{SEP}$ = 0.891 and SEP = 0.443 Brix under OSC preprocessing and those of PCR were $r_{SEP}$ = 0.845, SEP $r_{SEP}$= 0.520 Brix, under no preprocessing.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.19 no.6
• /
• pp.915-936
• /
• 2017

In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.

• Journal of Korean Society of Forest Science
• /
• v.89 no.5
• /
• pp.618-629
• /
• 2000

This study was carried out to investigate ecological niche of Quercus acuta communities in Bogildo-island from July to October, 1998. This island is occupied by a subtropical evergreen broad-leaved forests. The study on community ecology of Q. acuta, mostly dominant species of subtropical forests, is very important for successful forest management. Sampling areas were selected in 16 quadrats, dominated by Q. acuta to examine the vegetation characteristics(plant identification, D.B.H.) and environmental elements (microtopography, altitude, slope degree, aspect, illumination and soil physicochemical properties). On the basis of data from field surveys, importance values were calculated for the dominance of Q. acuta and volume growth was analyzed by tree ring widths. The results obtained were as follows ; 1. The lists of vascular plants in the investigations were identified as 54 families, 91 genera, 113 species, 9 varieties, 1 formae. It appeared that 45 kinds were evergreen, 6 kinds(Camellia japonica, Ligustrum japonicum, Eurya japonica, Smilax china, Trachelospermum asiaticum var. intermedium, Carex lanceolata) were commonly observed in all plots and 5 species(Cinnamomum japonicum, Ardisia japonica, Cymbidium goeringii, Dryopteris bissetiana, Viburnum erosum) were most highly observed in all plots(over 80%). 2. The dominating species per strata were, Quercus acuta, Castanopsis cuspidata sp. Quercus salicina, Pinus thunbergii, Prunus sargentii in tree layer, Camellia Japonica, Ligustrum japonicum, Quercus acuta, Eurya japonica, Castanopsis cuspidata sp. in subtree layer, Camellia japonica, Ligustrum japonicum, Smilax china, Cinnamomum japonicum, Viburnum erosum in shrub layer and Trachelospermum asiaticum var. intermedium, Ardisia japonica, Carex lanceolata, Camellia japonica(seedlings), Quercus acuta(seedlings) in herb layer, all in descending orders. 3. Quercus acuta could be suggested as shade intolerant tree, considering the distribution in southern, western, nothern and eastern slopes in the descending orders. 4. Mean relative illumination in the forest is 0.89 % and it is relatively low in brightness. 5. Sustainment of Quercus acuta community couldn't be confirmed by judging from their reverse J curve in even-aged forest, as shown in D.B.H. distribution analysis. 6. The result of annual ring width analysis(mean ; 2.44 mm) showed three stages, such as a gentle increasing(1~12 year ; 2.04 mm), a relatively steep increasing(13~22 year ; 2.95 mm) and decreasing or stagnating(23 year after ; 2.41 mm).

• Journal of KIISE:Software and Applications
• /
• v.30 no.9
• /
• pp.829-842
• /
• 2003

In this Paper, we propose the new face detection and tracking method based on template matching for real-time applications such as, teleconference, telecommunication, front stage of surveillance system using face recognition, and video-phone applications. Since the main purpose of paper is to track a face regardless of various environments, we use template-based face tracking method. To generate robust face templates, we apply wavelet transform to the average face image and extract three types of wavelet template from transformed low-resolution average face. However template matching is generally sensitive to the change of illumination conditions, we apply Min-max normalization with histogram equalization according to the variation of intensity. Tracking method is also applied to reduce the computation time and predict precise face candidate region. Finally, facial components are also detected and from the relative distance of two eyes, we estimate the size of facial ellipse.

• Journal of Korean Ophthalmic Optics Society
• /
• v.14 no.4
• /
• pp.65-69
• /
• 2009

Purpose: Recently incidence of VDT syndrome has gradually increased as extensive use of computers. VDT syndrome reported by VDT workers include musculoskeletal disorder, neuropsychiatric disoders and eye symptoms such as eye strain, tired eyes, irritation and blurred vision. The environmental factors of VDT syndrome include electromagnetic waves, size, brightness and lighting of computer screen, height of a monitor and a worktable, working hours, kind of task, distance between screen and workers, indoor humidity and temperature, indoor air contamination and ventilation. In this study, we investigated the environmental factors related to body symptoms and health effects included in VDT syndrome. Methods: Study subjects were total 120 persons (54 male, 66 female) with age from 19 to 28. We surveyed the body symptoms and physical discomfort when doing an activity in a short distance such as reading book or paper, computer work. The questionnaire included main body symptoms, self-consciousness symptoms of eye, satisfaction of working environment, pain of the wrist when using keyboard and mouse. Results: Most of people (70%) felt physical pain from long time work of computer, paper, electrical apparatus. They mainly complained pain of neck and low back (57.1%), eye (45.2%) and head (31%). With the environmental factors, 78.3% of the subjects complaint pain of eye from inappropriate illumination. Most of the symptoms included 'eye fatigue'(38.3%), 'dryness of eye'(31.9%) and 'blurred vision'(23.7%). Subjects in this study complained discomfort of their chairs and most of them experienced pain in the wrist when using keyboard or mouse. Conclusions: When people use electrical apparatus or work with paper, people would get their eye fatigue and feeling of physical fatigue because of not harmonizing various environmental factors such as light, space, posture, worktable with theirselves. Therefore, workers should develop preventive method such as self-control of adequate break time to avoid fatigue while VDT work. Work environment should be changed to ergonomic design for optimal visual environment to prevent musculoskeletal disorder through constant research.

• Journal of Korean Home Economics Education Association
• /
• v.19 no.3
• /
• pp.61-76
• /
• 2007

The purpose of the study is to identify and understand problems existing in the middle school home economics practice rooms in Jeju Special Self-Governing Province. The findings are based on the examination and the analysis of the indoor environment and the condition of the facilities and equipment. Study method employs on-site research and a survey. The on-site research was conducted about temperature, humidity, intensity of illumination, and status of teaching instrument in 10 out of 41 middle schools in Jeju Special Self-Governing Province from August 16 to September 30, 2006. Meanwhile, the survey was implemented by mail for 95 teachers in charge of manual training and home economics education in 41 middle schools in Jeju from November 1 to 23, 2005. 64 questionnaires out of total 95 were collected, including those collected during the period of on-site research. Finally, 61 questionnaires which were effective among the answered ones were used for analysis. Collected materials were analyzed with the SPSS Win.12.0 program for frequency, percentile analysis. In conclusion, the study determines that the condition of the home economics practice rooms of the middle school in JSSGP in terms of temperature, humidity, lighting and ventilation is very inadequate. The structure of the practice room represents an inefficient work flow pattern. Further, the facilities and equipment are in a very poor condition because the facilities are old and the retention rate of teaching tools is low. Therefore, to address these problems, the study suggests that improvements on the facilities and equipment should be made and teaching tools should be replenished in accordance with the industry standard.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.5
• /
• pp.71-78
• /
• 2021

Green areas and the area of available horizontal surfaces are gradually decreasing due to the overcrowding of buildings. It is adversely affecting the urban climate and ecosystem. However, the recognition of the importance of green areas is gradually increasing. As a result, the importance of wall greening using vertical surfaces is growing. However, despite the fact that domestic wall greening guidelines and institutions related to orientations restrict planting. there was no study to determine whether there were actual differences in plant growth due to orientations. Therefore, this study compared and analyzed the plant growth characteristics by orientations to apply actual wall greening to cities. The experiment was conducted from May to September 2020. First of all, three octave walls were constructed to measure the temperature, the illumination, and the length of the plants once a week. The plants included Parthenocissus tricuspidata, Hedera rhombea, and Euonymus radicans cv. Aueonmarinata Rehd plants. As a result of the study, Parthenocissus tricuspidata was prolific in the north, and Hedera rhombea, and Euonymus radicans cv. Aueonmarinata Rehd plants were prolific in the south. All three types of plants were prolific in June-July, and the Parthenocissus tricuspidata was prolific in grass-growing, and in August, all the walls were 100% covered. Hedera rhombea had the lowest rate of herbaceous growth, and the vertical coverate was also lower at an average of 45%, but among the three plants, the sheath of the horizontal surface coverate was the highest. Euonymus radicans cv. Aueonmarinata Rehd was low in the speed of herbaceous growth, and finally, the walls were 100% covered except for the north and northwest directions. It was found that not all plants used for wall greening show the same growth, and the difference in growth varies more depending on plants than the effect of orientations. Therefore, it is better to identify the characteristics of plant growth and plant suitable plants for each directions.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.26 no.2
• /
• pp.129-152
• /
• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.