The PoN (Proof of Nonce) distributed consensus algorithm basically uses a non-competitive consensus method that can guarantee an equal opportunity for all nodes to participate in the block generation process, and this method was expected to resolve the first trilemma of the blockchain, called the decentralization problem. However, the decentralization performance of the PoN distributed consensus algorithm can be greatly affected by the network transaction transmission delay characteristics of the nodes composing the block chain system. In particular, in the consensus process, differences in network node performance may significantly affect the composition of the congress and committee on a first-come, first-served basis. Therefore, in this paper, we presented a problem by analyzing the decentralization performance of the PoN distributed consensus algorithm, and suggested a fairness control algorithm using a learning-based probabilistic acceptance rule to improve it. In addition, we verified the superiority of the proposed algorithm by conducting a numerical experiment, while considering the block chain systems composed of various heterogeneous characteristic systems with different network transmission delay.

In recent years, there has been an increase in the morbidity of gastritis in Korea due to lifestyle factors mostly changes in eating habits and stress. Gastritis is more likely to progress to gastric cancer, and therefore it is important to prevent and manage gastritis through lifestyle adjustment and treatment at an early stage. In this study, cabbage, which was found to be effective in gastritis, was mixed and fermented with other crucifer plants such as kale and broccoli to evaluate the overall efficacy of fermented brassica puree on alcoholic acute gastritis. Based on our results, fermented brassica puree alleviated gastric injury induced by 150 mM HCl/60% ethanol. In addition, it was confirmed that PGE2, a gastric mucosal protective factor, was increased, and other positive effects such as an increase of MUC1 and regulation of PKC were observed. The results of this study suggest that fermented brassica puree can relieve acute alcoholic gastritis by regulating PGE and the expression of MUC1, a gene related to mucus secretion, and activating PKC, which is related to mucosal cell activity.

In recent years, importance of blockchain systems has been grown after success of bitcoin. Distributed consensus algorithm is used to achieve an agreement, which means the same information is recorded in all nodes participating in blockchain network. Various algorithms were suggested to resolve blockchain trilemma, which refers conflict between decentralization, scalability, security. An algorithm based on Byzantine Agreement among Decentralized Agents (BADA) were designed for the same manner, and it used limited committee that enables an efficient consensus among considerable number of nodes. In addition, election of committee based on Proof-of-Nonce guarantees decentralization and security. In spite of such prominence, application of BADA in actual blockchain system requires further researches about performance and essential features affecting on the performance. However, performance assessment committed in real systems takes a long time and costs a great deal of budget. Based on this motivation, we designed and implemented a simulator for measuring performance of BADA. Specifically, we defined a simulation framework including three components named simulator Command Line Interface, transaction generator, BADA nodes. Furthermore, we carried out response surface analysis for revealing latent relationship between performance measure and design parameters. By using obtained response surface models, we could find an optimal configuration of design parameters for achieving a given desirable performance level.

Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.

Probiotics improve the immune system. However, the effects of its lactic acid bacteria on atopic dermatitis relief and inflammation improvement is not fully understood. Recently, one of the probiotics, Lactobacillus helveticus HY7801 (HY7801), was found to have an anti-inflammatory effect. In this study, we investigated the effects of HY7801 on atopic dermatitis-induced animal models. After four weeks of oral administration, the group treated with HY7801 showed amelioration of the atopic dermatitis compared to the group receiving placebo. In the HY7801 treated group, the epidermal hyper-proliferation and collagen deposition were inhibited compared to the placebo group, and the secretion amount of the inflammatory factors, such as TNF-α, IL-4 were reduced. In conclusion, these results suggest that HY7801 acts as a functional probiotic via amelioration of the atopic dermatitis such as a decrease of epidermal hyper-proliferation, and collagen deposition and anti-inflammatory effects.

본 연구에서는 특별관리해역인 시화호 유역의 산업단지 하천에 강우 시 비점오염의 형태로 유입되는 중금속의 유출 특성 파악 및 오염원 파악을 하천 토구를 통해 배출되는 강우유출수 내 용존 및 입자성 중금속 (Cr, Co, Ni, Cu, Zn, As, Cd, Pb)을 조사하였다. 용존성 Co와 Ni은 강우 초반에 고농도로 유출된 후 시간에 따라 감소하는 결과를 보였으나, 대부분의 원소는 조사시기별 강우량 및 유량 변화에 따라 각각 다른 특징을 보였다. 입자성 중금속의 경우, 시간에 따른 부유물질의 농도 변화와 유사한 경향을 보였다. 강우유출수 내 존재하는 중금속 중 Co, Ni, Zn는 용존 상태로 유출되는 비율이 높았고, Cr, Cu, Pb은 입자상 유출 비율이 상대적으로 높았다. 입자 상태로 유출되는 중금속의 인위적 오염도를 평가하기 위해 농집지수를 계산한 결과, Cu, Zn, Cd은 very highly polluted에 해당하는 심각한 오염수준으로 나타났다. 연구지역인 3간선수로 유역 인근의 도로먼지 중 125 μm 이하에서의 중금속 농도와 비교한 결과, 강우유출수 내 Cu, Zn, Cd의 중금속이 금속제조관련 시설에서 절삭 혹은 가공 중에 발생하여 산업시설 표면에 축적되어 있는 금속물질이 강우유출수와 함께 수환경으로 유출된 것을 알 수 있었다. 강우유출수 내 총중금속 평균 유출부하량은 1회 강우 시 Cr 128g, Co 12.35 g, Ni 98.5 g, Cu 607.5 g, Zn 8,429.5 g, As 6.95 g, Cd 3.7 g, Pb 251.75 g으로 금속제조와 관련된 산업시설이 주로 존재하는 유역의 특성을 잘 반영한 것으로 판단된다

Process mining is an analytical technique aimed at obtaining useful information about a process by extracting a process model from events log. However, most existing process models are deterministic because they do not include stochastic elements such as the occurrence probabilities or execution times of activities. Therefore, available information is limited, resulting in the limitations on analyzing and understanding the process. Furthermore, it is also important to develop an efficient methodology to discover the process model. Although genetic process mining algorithm is one of the methods that can handle data with noises, it has a limitation of large computation time when it is applied to data with large capacity. To resolve these issues, in this paper, we define a stochastic process tree and propose a tabu search-genetic process mining (TS-GPM) algorithm for a stochastic process tree. Specifically, we define a two-dimensional array as a chromosome to represent a stochastic process tree, fitness function, a procedure for generating stochastic process tree and a model trace as a string of activities generated from the process tree. Furthermore, by storing and comparing model traces with low fitness values in the tabu list, we can prevent duplicated searches for process trees with low fitness value being performed. In order to verify the performance of the proposed algorithm, we performed a numerical experiment by using two kinds of event log data used in the previous research. The results showed that the suggested TS-GPM algorithm outperformed the GPM algorithm in terms of fitness and computation time.

본 연구는 행동 풍부화 프로그램을 적용한 반려견의 문제행동 해결방안을 제시하여 반려견과 보호자가 함께 행복한 삶을 영위하는 데 목적을 둔다. 이 연구는 논문, 서적 및 기사들을 대상으로 문헌 조사를 통해 총설 연구를 수행하였다. 조사방법은 원광대학교 중앙도서관과 DBpia, RISS, 및 Google에서 검색된 것 중에서 동물 행동 풍부화, 반려견 문제행동 관련 논문과 자료만을 선정하였다. 그 결과 첫째, 동물복지의 5가지 원칙 중 ‘기본 적인 환경 제공’, ‘동물 본연의 행동 양식대로 살아갈 자유’에 의거한 물리적 환경 풍부화로 산책하기, 산책로 변경 등 다양하게 환경을 변화시켜 문제행동이 교정되는 효과를 기대할 수 있다. 둘째, 동물복지의 5가지 원칙 중 ‘배고픔과 목마름으로부터의 자유’에 의거 한 일상적 사양 관리 풍부화로 음식의 맛과 질감 변화주기, 퍼즐 장난감과 같은 일상적 사양 관리 풍부화를 통하여 분리불안, 이식증, 식분증 등의 문제행동이 교정되는 효과를 기대할 수 있다. 셋째, 동물복지의 5가지 원칙 중 ‘동물 본연의 행동양식 그대로 살아갈 자유’에 의거한 사회그룹 풍부화로 산책, 애견카페, 애견 놀이터 등 다른 개체들 그리고 사람들이 많이 모여 있는 공간과 접촉하는 시간을 꾸준히 가져 문제행동이 교정되는 효과를 기대할 수 있다. 넷째, 동물복지의 5가지 원칙 중 ‘두려움과 스트레스로부터의 자유’, ‘동물 본연의 행동양식 그대로 살아갈 자유’에 의거한 감각자극 풍부화로 터그놀이, 노즈 워크, 공 던지기와 같은 활동을 통해 에너지 발산의 기회를 늘려주는 것으로 문제행동이 교정되는 효과를 기대할 수 있다. 현재 유기견 문제가 사회적으로 대두되고 있는 시점에서 반려견의 욕구를 해소시키는 활동을 통해 문제행동을 줄이고 사람들과 조화롭게 공존 할 수 있도록 하여 유기견 문제가 감소될 것으로 기대한다.

Heavy metals in stream water and sediments around industrial complex were studied in order to assess the contamination and to identify the potential source of metals. High variability has been observed for both dissolved and particulate phases in stream water with coefficient of variation (CV) ranging from 1.3 to 2.8. The highest metal concentrations in both phases were observed in Gunja for Ni and Cu, in Jungwang for Zn and Pb and in Shiheung for Cd, respectively. These results indicate that the different metal sources could be existing. The concentrations of the heavy metals in sediments decreased in the order of Cu>Zn>Pb>Cr>Ni>As>Cd>Hg, with mean of 2,549, 1,742, 808, 539, 163, 17.1, 5.8, 0.07 mg kg-1, respectively. Mean of metal concentrations (except for As) in sediments showed the highest values at Shiheung stream comparing with other streams. In sediments, the percent exceedance of class II grade that metal may potentially harmful impact on benthic organism for Cr, Ni, Cu, Zn, Cd, Pb was about 57%, 62%, 84%, 60%, 68%, 81% for all stream sediments, respectively. Sediments were classified as heavily to extremely polluted for Cu and Cd, heavily polluted for Zn and Pb, based on the calculation of Igeo value. About 59% and 35% of sediments were in the categories of “poor” and “very poor” pollution status for heavy metals. Given the high metal concentrations, industrial wastes and effluents, having high concentrations of most metals originated from the manufacture and use of metal products in this region, might be discharged into the stream through sewer outlet. The streams receive significant amounts of industrial waste from the industrial facilities which is characterized by light industrial complexes of approximately 17,000 facilities. Thus, the transport of metal loads through streams is an important pathway for metal pollution in Shihwa Lake.

분재는 우리나라의 주요 수출 임산물이다. 외국으로의 분재수출 요구도는 증가하고 있지만 수출을 위해서는 검역적 위해 요소가 제거 되어 야 하는데 식물기생선충도 검역의 중요 대상이다. 우리나라 6개 분재원에서 활엽수 분재[단풍나무(Acer palmatum), 백일홍(Zinnia elegans), 쥐똥나무(Ligustrum obtusiflium), 소사나무(Carpinus turcaninowii), 애기사과(Malus sieboldii)]를 대상으로 발생하는 선충을 조사하였다. 세 종의 식물기생선충[미국검선충(Xiphinema americanum), 둥근꼬리붙이나선선충(Rotylenchus blothrotylus), 한국껍질선충(Hemicycliophora koreana)] 과 세 종의 비기생 선충 [등화육각창선충(Aporclaimellus donghwaens), 둥근꼬리붙이나선선충(Egtitus andhricus), 계룡중간창선충(Mesodorylaimus usitatus)]들이 분재로부터 분리되었다. 비기생선충인 계룡중간창선충은 모든 조사 수종에서 검출되었고, 미국과 EU연합 검역대상 선충으로는 한국껍질선충과 미국검선충의 두 종만 발견되었다. 등화육각창선충과 계룡중간창선충은 분재목 뿌리에서 분리되었고, 나머지 선충들은 토양에서 분리되었다.

Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.

OLED Display fabrication system is one of the most complicated discrete processing systems in the world. As the glass size grows from 550×650mm to 1,500×1,850mm in recent years, the efficiency of Automated Material Handling System (AMHS) has become very important and OLED glass manufacturers are trying to improve the overall efficiency of AMHS. Aiming to meet the demand for high efficiency of transportation, various kind of approaches have been applied for improving dispatching rules and facility layout, while simultaneously considering the system parameters such as glass cassettes due date, waiting time, and stocker buffer status. However, these works did not suggest the operational policy and conditions of distribution systems, especially for handling unnecessary material flows such as detour. Based on this motivation, in this paper, we proposed an efficient algorithm for improving detour transportation in OLED FAB. Specifically, we considered an OLED FAB simplifying OLED production environment in a Korean company, where four stockers are constructed for the delivery of Lot in a bay and linked to processing equipments. We developed a simulation model using Automod and performed a numerical experiment using real operational data to test the performance of three operation policies under considerations. We showed that a competitive policy for assigning alternative stocker in case of detour was superior to the current dedicated policy using a specified stocker and other considered policies.

In this study, we analyzed the whole design of the necklace in detail, which reflects the artistic sense of handicraft in couture. The purpose of the study was to identify the characteristics of the design based on the analysis findings and to provide basic data to help fashion designers. The research method entailed analyzing trends in necklace design - viewed in fashion magazines and on websites - by year, season, brand, kind, material, color, and image. The identified necklace design characteristics were as follows. First, artistry and originality are dramatically expressed through the use of a broad range of materials. Second, due to the necklace’s role as an object of perfect beauty, in a number of images, the necklaces were presented in convergence and contrast with overall costumes. Third, the dramatic effects of layering revealed a strong presence and individualized styling. Necklaces are created with diverse sculptures by realizing the creative imagination of fashion designers. Even though they looked a little different every year, there were designs in the collections constantly. Round shape and princess length were preferred. In particular, the mix type was used to express dramatic effect by focusing neck part in entire styling which different length of necklaces were layered and worn. As a result, it meets the needs of consumers who emphasize brand differentiation and diversity, and it is believed that the role of necessities in fashion will continue and it creates economic demand in the fashion industry.

In recent years, imbalanced data is one of the most important and frequent issue for quality control in industrial field. As an example, defect rate has been drastically reduced thanks to highly developed technology and quality management, so that only few defective data can be obtained from production process. Therefore, quality classification should be performed under the condition that one class (defective dataset) is even smaller than the other class (good dataset). However, traditional multi-class classification methods are not appropriate to deal with such an imbalanced dataset, since they classify data from the difference between one class and the others that can hardly be found in imbalanced datasets. Thus, one-class classification that thoroughly learns patterns of target class is more suitable for imbalanced dataset since it only focuses on data in a target class. So far, several one-class classification methods such as one-class support vector machine, neural network and decision tree there have been suggested. One-class support vector machine and neural network can guarantee good classification rate, and decision tree can provide a set of rules that can be clearly interpreted. However, the classifiers obtained from the former two methods consist of complex mathematical functions and cannot be easily understood by users. In case of decision tree, the criterion for rule generation is ambiguous. Therefore, as an alternative, a new one-class classifier using hyper-rectangles was proposed, which performs precise classification compared to other methods and generates rules clearly understood by users as well. In this paper, we suggest an approach for improving the limitations of those previous one-class classification algorithms. Specifically, the suggested approach produces more improved one-class classifier using hyper-rectangles generated by using Gaussian function. The performance of the suggested algorithm is verified by a numerical experiment, which uses several datasets in UCI machine learning repository.

In the painting process of automotive factory, color changeover cost is incurred every time the color of vehicle is changed. To solve this problem, automotive company usually uses storage space such as Selectivity Banks(SB) or Car Rescheduling Storage and carries out sequence planning so that vehicles of the same color are consecutive, which is called Car Resequencing Problem (CRP). So far, research works for CRP has focused on algorithms finding optimal or approximated optimal solutions under the condition that the number of vehicles is fixed in SB. However, these results cannot be directly applied to the actual automotive paint shops since they have continuous flows of cars into SB to be handled in a day. Therefore, in this paper, we propose an efficient cyclic scheduling method that starts the painting process using the result of Accelerated Dynamic Programming (ADP) and then reapplies the ADP to the vehicles in SB for renewing the painting schedule whenever a certain number of vehicles is painted, represented as a threshold. To show the effectiveness of the proposed method, we performed a numerical experiment by designing system configurations, based onthe actual vehicle painting process, and proposed a good threshold that can reduce overall color changeover cost.

In order to verify the quality characteristics of soybean milk added chickpeas, the following characteristics were investigated: pH, solid contents, color, DPPH radical scavenging, as well as electric nose and sensory evaluation. Physicochemical and the sensory characteristics were analyzed based on the experimental data. The pH value was different in the control and the treatments (p<0.005). As the quantity of chickpea content increased, the solid content was augmented (p<0.0001). The L value was 56.86 in the control, and with the amount of chickpea addition increasing, the L value increased to 57.43 in 100% chickpea soybean milk (p<0.0001). The a value and b value also increased significantly (p<0.0001). However, the DPPH radical scavenging in the control was the lowest but the antioxidant activity of 100% chickpea milk was more than 2.5 higher than that of the control (p<0.0001). In the electric nose experiment, the flavor component of 20%, 30% and 100% chickpea treatment showed a significant difference compared to the control in the flavor components. In the sensory evaluation, for the score of flavor (p<0.001) and taste (p<0.0001), the score was higher in the treatments where 20% and 30% of chickpeas were added. In the sensory test of texture, there was no significant difference in the different experimental conditions except for the 100% chickpea addition treatment. In the overall acceptability test, the scores of 20% and 30% chickpea treatment were the highest results, compared to other treatments (p<0.0001). According to the correlation analysis, both antioxidant activity (0.797) and solid content (0.834) had shown high correlation to pH among the physiochemical characteristics (p<0.01). In the sensory evaluation, color, flavor, taste, texture and overall acceptability had shown a positive correlation to the amount of the soy bean milk added chickpea (p<0.01). In particular, the overall acceptability had shown the highest correlation to the taste (0.803), and it was the texture which resulted in the next highest correlation for overall acceptability (0.666).

The global small and mid-sized display market is changing from thin film transistor-liquid crystal display to organic light emitting diode (OLED). Reflecting these market conditions, the domestic and overseas display panel industry is making great effort to innovate OLED technology and incease productivity. However, current OLED production technology has not been able to satisfy the quality requirement levels by customers, as the market demand for OLED is becoming more and more diversified. In addition, as OLED panel production technology levels to satisfy customers’ requirement become higher, product quality problems are persistently generated in OLED deposition process. These problems not only decrease the production yield but also cause a second problem of deteriorating productivity. Based on these observations, in this study, we suggest TRIZ-based improvement of defects caused by glass pixel position deformation, which is one of quality deterioration problems in small and medium OLED deposition process. Specifically, we derive various factors affecting the glass pixel position shift by using cause and effect diagram and identify radical reasons by using XY-matrix. As a result, it is confirmed that glass heat distortion due to the high temperature of the OLED deposition process is the most influential factor in the glass pixel position shift. In order to solve the identified factors, we analyzed the cause and mechanism of glass thermal deformation. We suggest an efficient method to minimize glass thermal deformation by applying the improvement plan of facilities using contradiction matrix in TRIZ. We show that the suggested method can decrease the glass temperature change by about 23% through an experiment.

To increase the collagen recovery rate, bromelain (PB) and a microbial enzyme (PM) were used to treat to pork skin with single agent or combinations. The quality of collagen from the pork skin was evaluated by enzymatic treatments. The highest results for the solid contents and pork skin recovery rate obtained with the microbial-enzyme-bromelain mixtue (PMB) were 13.60% and 18.05% respectively. The result also showed that the color was affected by different types of enzyme treatments. Although PM treatment showed the highest result in the protein content of 251.30 mg/100 g, PMB treatment was the highest in the test of collagen content of 37.73 g/100 g among the treatments. However bands of the pork skin were detected widely at 130 kDa and 170 kDa ranges in SDS-PAGE. The band of PB treatment showed at the range of below 17 kDa, changed into a smaller molecular weight. The collagen content test of the pork skin by the treatments, collagen contents with combination treatment of pork skin with PMB (0.5%) resulted the highest in 43.76 g/100 g. Also the fat content at the above treatment was reduced to 11.12% compared to the other treatments. With these results of this experiment, we conclude that the enzymatic treatments were effective for the processing property of pork skin like enhancing the yield of collagen