• 대한토목학회논문집
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• 제38권3호
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• pp.417-428
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• 2018

본 연구의 목적은 상하수도 시설을 중심으로 한 물 인프라의 지속가능성을 평가하는 지수들을 활용하여 경제, 사회, 환경적 측면에서의 지속가능성을 평가하고 지속가능성 확보 필요성을 제고하기 위함이다. 경제, 사회, 환경적 지수 중 중요하게 고려해야할 세부지수들을 파악하고, 전국 지자체를 유형화하여 집단 간 특성을 비교분석하였다. 세부 지수의 가중치 산출은 주성분 분석을 활용하였으며, 지자체를 유형화하는 과정에는 K-평균 군집분석을 시행하였다. 가중치 분석 결과, 전체 12개의 지수 중 재정자립도, 자본수입비율, 보조금비율, 서비스보급률, 노후화율, 수생태건강성, 하천수질이 지속가능성을 평가하기 위한 주요한 변수로 분석되었으며, 특히, 경제부문 지수의 영향력이 가장 높은 것으로 나타났다. 다음으로는 군집분석 결과를 통해 지자체를 크게 두 가지 유형으로 분류하였고, 각 유형 별 특징을 살펴보았다. 먼저 경제부문의 지속가능성이 우수한 집단에서는 환경부문에 대한 개선이 필요한 것으로 나타났지만, 대체로 지속가능성 상태가 우수한 것으로 나타났다. 환경부문이 우수한 집단에서는 지속가능성 상태가 열악한 지자체가 많이 포함되어 있으며, 특히, 경제부문 상태를 향상시키기 위한 집중적인 노력이 필요한 것으로 보인다.

• The Korean Journal of Pain
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• 제30권3호
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• pp.197-206
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• 2017

Background: Pain with neuropathic characteristics is generally more severe and associated with a lower quality of life compared to nociceptive pain (NcP). Short form of the Douleur Neuropathique en 4 Questions (S-DN4) is one of the most used and reliable screening questionnaires and is reported to have good diagnostic properties. This study was aimed to cross-culturally validate the Hindi version of the S-DN4 in patients with various chronic pain conditions. Methods: The S-DN4 is already translated into the Hindi language by Mapi Research Trust. This study assessed the psychometric properties of the Hindi version of the S-DN4 including internal consistency and test-retest reliability after 3 days' post-baseline assessment. Diagnostic performance was also assessed. Results: One hundred sixty patients with chronic pain, 80 each in the neuropathic pain (NeP) present and NeP absent groups, were recruited. Patients with NeP present reported significantly higher S-DN4 scores in comparison to patients in the NeP absent group (mean (SD), 4.7 (1.7) vs. 1.8 (1.6), P < 0.01). The S-DN4 was found to have an AUC of 0.88 with adequate internal consistency (Cronbach's ${\alpha}=0.80$) and a test-retest reliability (ICC = 0.92) with an optimal cut-off value of 3 (Youden's index = 0.66, sensitivity and specificity of 88.7% and 77.5%). The diagnostic concordance rate between clinician diagnosis and the S-DN4 questionnaire was 83.1% (kappa = 0.66). Conclusions: Overall, the Hindi version of the S-DN4 has good internal consistency and test-retest reliability along with good diagnostic accuracy.

• 대한불안의학회지
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• 제16권2호
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• pp.83-90
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• 2020

Objective : Heart rate variability (HRV) is known to reflect autonomic nervous system activity. Individuals with posttraumatic stress disorder (PTSD) are reported to have lower HRVs. We attempted to find HRV indices with head up tilt position that reflect the symptoms well in order to evaluate PTSD symptoms. Methods : Sixty-seven patients with PTSD and 72 patients without PTSD were assessed using the PTSD Checklist for DSM-5 (PCL-5), the Beck Depression Inventory, the Beck Anxiety Inventory and the Pittsburgh Sleep Quality Index. HRV was measured in the head-up tilt position. We collected data regarding heart rate (HR), standard deviation of the NN intervals (SDNN), the square root of the mean squared differences of successive NN intervals (RMSSD), log low-frequency (LNLF) and log high-frequency (LNHF). Results : The value of LNHF was different according to presence or absence of PTSD after head-up tilt position. In the findings of the association between PTSD symptoms and HRV indices as based on head-up tilt, LNHF had a significant correlation with the total score of PCL-5. Conclusion : The reduction of the high-frequency component of HRVs in the PTSD group might reflect more PTSD symptoms.

• 대한약침학회지
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• 제21권2호
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• pp.112-119
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• 2018

Contents of compounds in Rehmanniae Radix change depending on the number of steaming and drying and the drying method. In this study, as an impregnation method for dried Rehmanniae Radix, takju impregnation and cheongju impregnation were carried out and steaming and drying were repeated for 9 times. The changes of 5-HMF and catalpol contents were analyzed according to the number of repetition times to investigate which stage of steaming and drying is preferable. Also, total nitrogen, crude fat, ash, and crude fiber were measured to analyze changes in general components. 5-HMF was not detected in dried Rehmanniae Radix. As a result of repetitive steaming and drying, the content of 5-HMF increased only slightly from 1 to 4-times steaming and drying but increased significantly from 5-times. The catalpol in dried Rehmanniae Radix was not detected after 5 times of steaming and drying. Sucrose, maltose, and glucose were included in dried Rehmanniae Radix before steaming and drying. However, after the process in both Takju impregnation and Cheongju impregnation, galactose and fructose tended to decrease after production and sucrose and glucose tended to decrease after the increase. In this study condition, 6-times and more steaming and drying were appropriate process which met the content criteria (not less than 0.1%) of the Korean Pharmacopoeia (8th edition) for 5-HMF, an index component for quality control of Rehmanniae Radix Preparata.

• 복식
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• 제57권7호
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• pp.1-14
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• 2007

This study investigates the differences between the satisfaction factors of store characteristics depending on on-line clothing store type and its satisfaction index. The collected data were analyzed by using SPSS 10.0 software with various techniques such as paired t-test, T-test, Cronbach's ${\alpha}$ reliability and factor analysis that use principal component analysis and Varimax orthogonal rotation were used. The results are summarized as follows: 1. By categorizing the level of on-line store characteristics satisfaction depending on its type, clarifies the differences between its satisfaction. The satisfaction rank of general merchandise store was as followed: searching and approaching system, buying process service, screen-displayed design, product, store credit. On the other hand, the satisfaction rank of general store was as followed: screen-displayed design, store credit, buying process service. 2. By analyzing the difference of satisfaction depending on the store type, it was found that general merchandise store was more satisfied with screen-displayed design, approaching and searching, whole payment process, the safety of payment and shipping service, security service when compared to specialty store. It was also found that specialty store was more satisfied with the variety of product, update of rare items, quality and price of product. 3. By analyzing the difference between the type of on-line clothing store satisfaction depending on age, in the case of general merchandise store, the result showed that people in their thirties were more satisfied with buying process service, store credit, customer management system when compared to twenties. In the case of specialty store, the result showed that people in their twenties were more satisfied with customer management service when compared to thirties, and when it came to buying process service, it was vice versa.

• Investigative Magnetic Resonance Imaging
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• 제20권4호
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• pp.207-214
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• 2016

Purpose: The purpose of this study was to investigate the effect of the number of measurement points on the calculation of transverse relaxation time (T2) with a focus on muscle T2. Materials and Methods: This study assumed that muscle T2 was comprised of a single component. Two phantom types were measured, 1 each for long ("phantom") and short T2 ("polyvinyl alcohol gel"). Right calf muscle T2 measurements were conducted in 9 healthy male volunteers using multiple-spin-echo magnetic resonance imaging. For phantoms and muscle (medial gastrocnemius), 5 regions of interests were selected. All region of interest values were expressed as the mean ${\pm}$ standard deviation. The T2 effective signal-ratio characteristics were used as an index to evaluate the magnetic resonance image quality for the calculation of T2 from T2-weighted images. The T2 accuracy was evaluated to determine the T2 reproducibility and the goodness-of-fit from the probability Q. Results: For the phantom and polyvinyl alcohol gel, the standard deviation of the magnetic resonance image signal at each echo time was narrow and mono-exponential, which caused large variations in the muscle T2 decay curves. The T2 effective signal-ratio change varied with T2, with the greatest decreases apparent for a short T2. There were no significant differences in T2 reproducibility when > 3 measurement points were used. There were no significant differences in goodness-of-fit when > 6 measurement points were used. Although the measurement point evaluations were stable when > 3 measurement points were used, calculation of T2 using 4 measurement points had the highest accuracy according to the goodness-of-fit. Even if the number of measurement points was increased, there was little improvement in the probability Q. Conclusion: Four measurement points gave excellent reproducibility and goodness-of-fit when muscle T2 was considered mono-exponential.

• 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.

• 한국식품영양과학회지
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• 제44권9호
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• pp.1347-1355
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• 2015

본 연구는 참외 착즙액을 동결농축 하여 열수 처리 및 아스코르브산 처리 후 갈변 억제에 의한 이화학적인 품질 특성과 휘발성 향기 성분을 분석하였다. 동결농축 공정에 의한 참외 와인은 발효 과정에서 열수 처리가 아스코르브산 처리에 비해 가용성 고형분 함량 및 환원당 감소가 빠르며, 알코올 생성 또한 빠른 것으로 나타났다. 갈변도와 색차 측정 결과 갈변 억제 효과가 열수/아스코르브산 병용 처리구> 아스코르브산 처리구> 열수 처리구> 대조구 순이었으며, 아스코르브산 처리 참외와인은 숙성 후에도 갈변 억제 효과가 유지되고 있는 것으로 나타났다. 유리당은 fructose만 검출되었으며, 유기산은 citric acid, malic acid, succinic acid 모두 아스코르브산 처리구에서 함량이 많게 나타났다(P<0.05). 항산화능은 DPPH 라디칼 소거 활성, FRAP 활성이 아스코르브산 처리구에서 높았으며, 총 페놀성 화합물의 함량은 아스코르브산 처리구에서 가장 높았고, 총 플라보노이드 함량은 대조구에서 가장 높게 나타났다. SPME head-space 법에 의한 비동결농축 및 동결농축 참외와인의 휘발성 향기 성분 분석 결과 총 33종의 향기 성분이 동정되었으며, ester 류가 10종으로 가장 많이 검출되었다. 동결농축 참외와인에서는 총 29종의 향기 성분이 동정되었으며, 비동결농축 참외와인에서는 총 23종이 동정된 것으로 나타났다. 과일 향을 나타내는 ethyl formate, ethyl butyrate, butyl alcohol 등의 향기 성분이 비동결농축 참외와인에서 검출되지 않은 것으로 보아 동결농축 참외와인은 비동결농축 참외와인에 비해 과일 특유의 향과 같은 다양한 향기 성분을 가지는 것으로 나타났다. 본 연구에서 열수 처리 및 아스코르브산 병용 처리는 동결농축 참외와인의 갈변 억제에 효과적이며, 항산화 활성을 증가시키는 것으로 나타났다.

• 한국측량학회지
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• 제40권4호
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• pp.275-292
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• 2022

기후변화 감시에 위성 자료 활용을 위해 GCOS (Global Climate Observing System)는 시공간 해상도, 시간 변화에 따른 안정성, 불확실도 등의 요구사항을 제시하고 있다. 천리안위성 2A호의 경우, 센서의 한계로 인해 산출물들이 공간해상도 조건에 충족하지 못하는 경우가 많다. 따라서 본 연구에서는 영상융합 기법들을 천리안위성 2A호 영상에 적용하여 산출물 생성 시 활용될 수 있는 최적의 기법을 찾고자 한다. 이를 위해 CS (Component Substitution), MRA (Multiresolution Analysis), VO (Variational Optimization), DL (Deep Learning)에 포함되는 총 6가지 영상융합 기법을 활용하였다. DL의 경우 합성적(Synthesis) 특성 기반 방법을 훈련자료 구축에 사용하였다. 합성적 특성 기반 방법의 과정은 PAN (Panchromatic)과 MS (Multispectral) 영상의 공간해상도 차이만큼 두 영상의 해상도를 낮춰 융합 영상을 생성한 후 원본 MS 영상과 비교한다. 합성적 특성 기반 방법은 공간해상도를 저하시킨 PAN 영상과 MS 영상 간 기하 특성이 같아야 사용자가 원하는 수준의 융합 영상을 제작할 수 있다. 하지만, 훈련자료 구축 시 비유사성이 존재하기에 이를 최소화하는 방법으로 무작위 비율을 활용한 PSGAN 모델(PSGAN_RD)을 추가로 활용하였다. 융합 영상의 검증은 일관성(consistency) 및 합성적 특성 기반 정성적, 정량적 분석을 수행하였다. 분석 결과, 영상융합 알고리즘 중 GSA가 공간 유사도를 나타내는 평가지수에서 가장 높은 수치를 보였으며, 분광 유사도를 나타내는 지수들은 PSGAN_RD 모델의 정확도가 가장 높았다. 융합 영상의 공간 및 분광 특성을 모두 고려한다면 PSGAN_RD 모델이 천리안위성 2A호 산출물 제작에 가장 최적일 것으로 판단하였다.