• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1154-1154
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• 2001

Near infra-red (NIR) spectroscopy has been used for the non-invasive assessment of intact fruit for eating quality attributes such as total soluble solids (TSS) content. However, little information is available in the literature with respect to the robustness of such calibration models validated against independent populations (however, see Peiris et al. 1998 and Guthrie et al. 1998). Many studies report ‘prediction’ statistics in which the calibration and prediction sets are subsets of the same population (e. g. a three year calibration validated against a set from the same population, Peiris et al. 1998; calibration and validation subsets of the same initial population, Guthrie and Walsh 1997 and McGlone and Kawano 1998). In this study, a calibration was developed across 84 melon fruit (R$^2$= 0.86$^{\circ}$Brix, SECV = 0.38$^{\circ}$Brix), which predicted well on fruit excluded from the calibration set but taken from the same population (n = 24, SEP = 0.38$^{\circ}$Brix with 0.1$^{\circ}$Brix bias), relative to an independent group (same variety and farm but different harvest date) (n = 24, SEP= 0.66$^{\circ}$ Brix with 0.1$^{\circ}$Brix bias). Prediction on a different variety, different growing district and time was worse (n = 24, SEP = 1.2$^{\circ}$Brix with 0.9$^{\circ}$Brix bias). Using an ‘in-line’ unit based on a silicon diode array spectrometer, as described in Walsh et al. (2000), we collected spectra from fruit populations covering different varieties, growing districts and time. The calibration procedure was optimized in terms of spectral window, derivative function and scatter correction. Performance of a calibration across new populations of fruit (different varieties, growing districts and harvest date) is reported. Various calibration sample selection techniques (primarily based on Mahalanobis distances), were trialled to structure the calibration population to improve robustness of prediction on independent sets. Optimization of calibration population structure (using the ISI protocols of neighbourhood and global distances) resulted in the elimination of over 50% of the initial data set. The use of the ISI Local Calibration routine was also investigated.

• 한국미생물·생명공학회지
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• 제13권1호
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• pp.79-85
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• 1985

대두 경남 장려품종인 장백, 광교, 강림 및 남천등의 근류로부터 Rhizobium japonicum을 분리하여 그 중 질소고정력이 R. japonicum 61A 76이나 3 I1110보다 강한 JB 101을 선별하였다. 선별된 JB 101을 N-methy1-N'-nitro-N-nitrosoguanidine 처리 및 UV조사에 많은 돌연변이체를 얻고 이들로 부터 경남 장려품종인 장백에 접종시근류 생성력 및 질소고정력등 JB 101에 비하여 훨씬 높을 뿐만아니라 SM 35에 비해서도 다소 높은 JB 65를 선별하여 이 균주의 근류생성력, 질소고정력, 고정된 암모니아가 질소고정에 미치는 영향, hydrogenase 활성등 공생관련 제 특성과 아울러 이 균주 단백질의 아미노산 조성, 2D-polyacrylamide gel을 이용한 전기영동등의 생화학적 특성도 아울러 조사하였다.

• 한국산림과학회지
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• 제75권1호
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• pp.55-66
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• 1986

개암나무 10품종(品種)의 각(各) 특성(特性)에 대한 일반조합능력(一般組合能力)이 좋은 개체(個體)와 특수조합능력(特殊組合能力)이 좋은 교배조합(交配組合)을 선발(選拔)하기 위(爲)하여 완전대조교배(完全對照交配)를 실시(實施)하였다. ha 당(當) 인중생산량(仁重生産量)에서 일반조합능력(一般組合能力)이 가장 좋은 개체(個體)는 "Barcelona" 이었으며 특수조합능력(特殊組合能力)이 좋은 교배조합(交配組合)은 Kara${\times}$Badem, Badem${\times}$Barcelona, Sivri${\times}$Barcelona, Sirri${\times}$Barcelona, Palaz${\times}$Barcelona, Tombul${\times}$Kara, Barcelona${\times}$Sivri, Hukuken 2호(號)${\times}$Hukuken 3호(號), Hukuken 3호(號)${\times}$Hukuken 2호(號)이다. 교배조합간(交配組合間)의 결실율(結實率), 과우(果友)두께, 입중(粒重), 인중(仁重), 인중비(仁重比), 본당(本當) 혹은 ha당(當) 인중생산량(仁重生産量)의 특성(特性)에 대(對)하여도 비교분석(比交分析) 하였다.

• 한국자원식물학회지
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• 제31권6호
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• pp.714-718
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• 2018

A new Gomchwi cultivar 'Sammany' was developed by a cross between Gomchwi (Ligularia fischeri (Ledeb.) Turcz.) and Handaeri-gomchwi (Ligularia fischeri var. spiciformis Nakai). Gomchwi is a common Korean name referring wild edible plant species within Ligularia genus. 'Sammany' has purple colored petiole ears and petiole trichome is absent. It has 2nd degree leaf vein density. Plant height, leaf length, leaf width and petiole length were 46.2, 19.1, 19.5 and 32.1 cm, respectively. Plant height was higher than 'Gondalbi'. Bolting occurred in mid. July and it flowered from late August to early September. 'Gondalbi' bolted and flowered 26 days earlier than 'Sammany', and consequently has earlier flowering time more than 26 day. Leaf number of 'Sammany' was 156 per plant but 'Gondalbi' had 130. 'Sammany' had thicker leaves (0.61 mm) compared to 'Gondalbi' (0.46 mm). As a result, yield was higher in 'Sammany (1,077 g/plant)' than 'Gondalbi (798 g/plant)' and leaf hardness was lower in 'Sammany ($20.8kg/cm^2$)' compared to 'Gondalbi ($23.0kg/cm^2$)'. In addition, 'Sammany' was found to be moderately resistant to powdery mildew. With enhanced agronomic and pathology traits, 'Sammany' was newly registered as a new Gomchwi cultivar (variety protection no. 131 on May 2017).

• 원예과학기술지
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• 제33권1호
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• pp.143-148
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• 2015

'URI 2010-6'은 우리꽃종묘에서 2011년 종간 교잡종인 'Evergreen Emerald'을 자방친으로 D. chinensis 'Ruby'를 화분친으로 실시한 교잡의 $F_1$ 후대로부터 선발, 육성한 패랭이꽃속 신품종이다. 2007년 교배실생 개체를 획득하였고, 2008년부터 2010년까지 3년 동안의 생육특성검정을 통해 선발하여 2011년 국립종자원에 'URI 2010-6'로 신품종 등록하였다(품종보호: 제4431호). 'URI 2010-6'의 화색은 주로 밝은 적색(Red, N79C)이며, 2차색으로 백색(White, N155C)이 꽃잎 가장자리와 꽃잎에 반점형태로 발현되는 석죽형의 홑꽃이다. 또한 꽃의 직경은 2.7cm, 길이는 0.8cm이고, 개화 지속기간은 평균 150일 정도로 장기개화가 가능하며, 겨울철에도 상록성이 우수하다.

• 한국병원경영학회지
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• 제20권4호
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• pp.50-61
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• 2015

Advances in healthcare technology and rapid economic growth lead to the increased life expectancy and consequently the size of elderly population. Korea is one of the countries that are rapidly aging. Thus, it is particularly important to prepare for the aging society. Recently, the number of healthcare institutions for the elderly citizens has increased. The purpose of selecting a hospital for the elderly is, in general, maintenance of health rather than improvement of health receiving proper treatment. Unlike choosing a hospital for treatment, customers of a long term care hospital have a different set of factors to consider. Especially, when choosing a long term care hospital, the influence of patient's family is greater than the patient. This study examines the factors they consider for long term care hospital. A total of 198 questionnaires were collected from the families of actual patients of long term care hospitals. Twelve questionnaires were found to be non-usable because of missing and unsatisfactory responses. Consequently, 186 questionnaires were used for the analyses. Findings of this study are as follows. First, seven factors have been identified to consider when choosing a long term care hospital for the elderly. They include convenience of facilities, costs variety of facility programs, service hours, reputation, accessibility, quality of medical staff, medical facilities, and facility size. Second, This study measured both importance and satisfaction with these attributes and analyzed the difference between them. Satisfaction was lower than importance in the categories of convenience of facilities, costs, and programs, and accessibility. On the other hand, satisfaction was higher in terms of service hours, reputation, and quality of medical staff. Finally, the current study found positive impact of accessibility and quality of medical staff on reuse intention of a long term care hospital.

• Asian-Australasian Journal of Animal Sciences
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• 제10권2호
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• pp.215-222
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• 1997

Ten rice varieties were planted at two locations (lowland and highland), during the wet and dry seasons of different years. In vivo digestibility and voluntary intake of the straw, were determined in groups of fat-tail sheep, supplemented with $18g{\cdot}kg^{-0.75}$ concentrate DM, containing ~20% crude protein. Voluntary intake of digestible straw organic matter (DOMI) consistently varied from 15.2 to $20.9g{\cdot}kg^{-0.75}$ between straw varieties, averaged over locations, years and seasons, despite considerable variation between individual batches. This variation in the nutritive value of the straw was independent of straw and grain yield, so it would seem that there is scope for selection of rice varieties with straw of higher nutritive value. The variation in DOMI of straw among location of growth, year and season, was of a magnitude similar to the improvement brought about by urea-ammoniation. The in sacco degradation characteristics and digestibility of rice straw residues were superior to those of the offered straw. This can be attributed to a preference for rice straw leaves relative to stems. Averaged over location of growth, year and season, characteristics of in sacco degradation, i.e. the rate of fermentative degradation and the truly undegradable fraction, emerged as accurate predictors of the nutritive value of rice straw.

• 복식
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• 제48권
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• pp.183-196
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• 1999

The purpose of the Present research is to investigate the effect of fashion lifestyle on babies' clothing shopping attitude of housewives. In this study shopping attitude includes criteria for shop selection prefered types of shop and prefered shop atmosphere. Subjects are 447 housewives residing in Seoul Bundang Illsan and Pungchon and having child under 4 years old Data was analyzed by factor analysis cluster analysis analysis of variance and chi-square. The results of the study are as follows: 1. Housewives can be classified into four groups according to their fashion lifestyle the group of planned buying conservative/practical group the group of self-actualization/individuality and the high involved and care for shopping group. 2. Fashion lifestyle is different according to their age. The high involved and care for shopping group have the lager proportion in twenties than thirties. The conservative/practical group have a larger proportion in thirties. 3. The factors of shop selection which serve as criteria for shop the quality of service encironment anround shop quality of goods convenience to care about babies fashionable goods location of the shop and price of goods. The group of self actualization/personality prefers shops carrying fashionable and unique style of babies clothing and showing prestige. The conservative/practical group prefers shops carrying good quality clothing and having variety in size and design. The high involved and careful shopping group prefers shops having wide space as well as carrying fashionable goods. 4. Among the types of babies clothing shops. department stroe is the most preferred Low-price brand shop is followed by traditional open market. The conservative/practical group and the group of planned shopping use department strores national bran shops street shops and import shops more often than other groups. 5. The result of the study indicates there are considerable differences in housewives attitudes of babies clothing shopping acording to their own fashion lifestyle. Therefore the retailer of babies clothing should decide their marketing policy on the basis of the understanding and analysis of costomer's fashion lifestyle. And they have to reflect their costomer's shopping attitudes on their marketing policy to improve the satisfaction of both consumer and retailer as well.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.