Objective: This study estimated the genetic parameters for productive and reproductive traits. Methods: The data included production and reproduction records of animals that have calved between 1979 and 2013. The genetic parameters were estimated using multivariate mixed models (DMU) package, fitting univariate and multivariate mixed models with average information restricted maximum likelihood algorithm. Results: The estimates of heritability for milk production traits from the first three lactation records were $0.03{\pm}0.03$ for lactation length (LL), $0.17{\pm}0.04$ for lactation milk yield (LMY), and $0.15{\pm}0.04$ for 305 days milk yield (305-d MY). For reproductive traits the heritability estimates were, $0.09{\pm}0.03$ for days open (DO), $0.11{\pm}0.04$ for calving interval (CI), and $0.47{\pm}0.06$ for age at first calving (AFC). The repeatability estimates for production traits were $0.12{\pm}0.02$, for LL, $0.39{\pm}0.02$ for LMY, and $0.25{\pm}0.02$ for 305-d MY. For reproductive traits the estimates of repeatability were $0.19{\pm}0.02$ for DO, and to $0.23{\pm}0.02$ for CI. The phenotypic correlations between production and reproduction traits ranged from $0.08{\pm}0.04$ for LL and AFC to $0.42{\pm}0.02$ for LL and DO. The genetic correlation among production traits were generally high (>0.7) and between reproductive traits the estimates ranged from $0.06{\pm}0.13$ for AFC and DO to $0.99{\pm}0.01$ between CI and DO. Genetic correlations of productive traits with reproductive traits were ranged from -0.02 to 0.99. Conclusion: The high heritability estimates observed for AFC indicated that reasonable genetic improvement for this trait might be possible through selection. The $h^2$ and r estimates for reproductive traits were slightly different from single versus multi-trait analyses of reproductive traits with production traits. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended.
Kim, Gisu;Park, Yeong-il;Ro, Yun-sik;Jung, Jae-wook
Journal of the Korea Academia-Industrial cooperation Society
/
v.17
no.8
/
pp.582-594
/
2016
Most studies on hybrid buses are on large-sized buses and not mid-sized low-floor buses. This study uses MATLAB simulation to evaluate the fuel efficiency of such buses powered by diesel. Based on the results, a hybrid electric vehicle system is recommended for the best combination of power and gear ratio. A parallel hybrid system was selected for the hybridization, which transmits front and rear wheel power independently. The necessary power to satisfy the target performance was calculated, and the applicable capacity area was designed. Dynamic programing was used to create and optimize a component sizing algorithm, which was used to scale the capacity of each component of the power source to satisfy the design criteria. The fuel efficiency rate, optimum power source capacity, and gear ratio can be improved by converting a conventional bus into a parallel hybrid bus.
Song Yong-Uk;Hong June-Seok;Kim Woo-Ju;Lee Sung-Kyu;Youn Suk-Hee
Journal of Intelligence and Information Systems
/
v.12
no.2
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pp.67-81
/
2006
While the existing Web focuses on the interface with human users based on HTML, the next generation Web will focus on the interaction among software agents by using XML and XML-based standards and technologies. The inference engine, which will serve as brains of software agents in the next generation Web, should thoroughly understand the Semantic Web, the standard language of the next generation Web. As abasis for the service, the W3C (World Wide Web Consortium) has recommended SWRL (Semantic Web Rule Language) which had been made by compounding OWL (Web Ontology Language) and RuleML (Rule Markup Language). In this research, we develop a backward chaining inference engine SMART-B (SeMantic web Agent Reasoning Tools -Backward chaining inference engine), which uses SWRL and OWL to represent rules and facts respectively. We analyze the requirements for the SWRL-based backward chaining inference and design analgorithm for the backward chaining inference which reflects the traditional backward chaining inference algorithm and the requirements of the next generation Semantic Web. We also implement the backward chaining inference engine and the administrative tools for fact and rule bases into Java components to insure the independence and portability among different platforms under the environment of Ubiquitous Computing.
Moon, Junghoon;Jang, Ikhoon;Choe, Young Chan;Kim, Jin Gyo;Bock, Gene
The Journal of Korean Institute of Communications and Information Sciences
/
v.40
no.5
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pp.903-913
/
2015
The Korea Agency of Education, Promotion and Information Service in Food, Agriculture, Forestry and Fisheries launched a public data portal service in January 2015. The service provides customized information for consumers through an agri-food recommendation system built-in portal service. The recommendation system has fallowing characteristics. First, the system can increase recommendation accuracy by using a wide variety of agri-food related data, including SNS opinion mining, consumer's purchase data, climate data, and wholesale price data. Second, the system uses segmentation method based on consumer's lifestyle and megatrends factors to overcome the cold start problem. Third, the system recommends agri-foods to users reflecting various preference contextual factors by using recommendation algorithm, dirichlet-multinomial distribution. In addition, the system provides diverse information related to recommended agri-foods to increase interest in agri-food of service users.
Objectives : Several factors, such as biological markers, clinical correlates, and course of the depressive disorders with psychotic symptoms differ from those without psychotic symptoms. Therefore, specification of a treatment algorithm for depressive disorder with psychotic symptoms is legitimated. This article provides a systematic review of somatic treatments for depressive disorder with psychotic symptoms. Methods : According to the search strategy of the Clinical Research Center for Depression of Korean Health 21 R & D Project, first, PubMed and EMBASE were searched using terms with regard to the treatment of depressive disorders with psychotic symptoms(until July 2006). Reference lists of related reviews and studies were searched. In addition, relevant practice guidelines were searched using PubMed. All identified clinical literatures were reviewed and summarized in a narrative manner. Results : Treatment options, such as a combination of an antidepressant and an antipsychotic versus an antidepressant or an antipsychotic alone are summarized. In addition, issues regarding the electroconvulsive therapy( ECT), combination therapy, and maintenance treatment are discussed. Conclusion : In former times, the combination of an antidepressant and an antipsychotic or ECT were recommended as the first line treatment for depressive disorder with psychotic symptoms. Recently, however, there was a suggestion that there was no conclusive evidence that the combination of an antidepressant and an antipsychotic drug is more effective than an antidepressant alone. More evidence regarding the pharmacological treatment for depressive disorder with psychotic symptoms is needed.
International Journal of Computer Science & Network Security
/
v.21
no.3
/
pp.245-256
/
2021
Poor logistical infrastructure and agri-food supply chain management leads to significant food waste in logistic system. The concept of the sustainable value added agri-food chains requires defined approach to the analysis of the existing situation, possible improving strategies and also assessment of these changes impact on further development. The purpose of research is to provide scientific substantiation of theoretical and methodological principles and develop practical recommendations for the improvement of the agri-food logistics distribution system. A case study methodology is used in this article. The research framework is based on 4 steps: Value Stream Mapping (VSM), Gap and Process Analysis, Validation and Improvement Areas Definition and Imitation Modelling. This paper presents the appropriateness of LEAN logistics tools using, in particular, Value Stream Mapping (VSM) for minimizing logistic losses and Simulation Modeling of possible logistics distribution system improvement results. The algorithm of VSM analysis of the agri-food supply chain, which involves its optimization by implementing the principles of sustainable development at each stage, is proposed. The methodical approach to the analysis of possible ways for optimizing the operation of the logistics system of the agri-food distribution is developed. It involves the application of Value Stream Mapping, i.e. designing of stream maps of the creation of the added value in the agri-food supply chain for the current and future state based on the minimization of logistic losses. Simulation modeling of the investment project on time optimization in the agri-food supply chain and economic effect of proposed improvements in logistics product distribution system functioning at the level of the investigated agricultural enterprise has been determined. Improvement of logistics planning and coordination of operations in the supply chain and the innovative pre-cooling system proposed to be introduced have a 3-year payback period and almost 75-80% probability. Based on the conducted VSM analysis of losses in the agri-food supply chain, there have been determined the main points, where it is advisable to conduct optimization changes for the achievement of positive results and the significant economic effect from the proposed measures has been confirmed. In further studies, it is recommended to focus on identifying the synergistic effect of the agri-food supply chain optimization on the basis of sustainable development.
KIPS Transactions on Computer and Communication Systems
/
v.12
no.2
/
pp.85-92
/
2023
Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.
Park, Seong Uk;Jung, Woo Sang;Moon, Sang Kwan;Go, Chang Nam;Cho, Ki Ho;Kim, Young Suk;Bae, Hyung Sup
The Journal of the Society of Stroke on Korean Medicine
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v.6
no.1
/
pp.25-32
/
2005
Background and purpose: Arterial stiffness is an important, independent determinant of cardiovascular risk. Pulse wave velocity (PWV) has been used as a valuable index of arterial stiffness and as a surrogate marker for atherosclerosis. The Framingham risk score was developed using categorized risk factors to predict the 10 year absolute risk of developing coronary heart disease (CHD). This algorithm is established using recommended guidelines for blood pressure, total cholesterol, and high density lipoprotein cholesterol in addition to age, smoking history and history of diabetes. Tongxinluo(TXL) has been shown to have anti hyperlipidemic activity and anti atherogenic effects. To determine its efficacy and safety, we examined whether TXL improves PWV, ABI, Framingham score, blood pressure, and lipid profile in high risk group of cardiovascular diseases. Subjects and methods: 49 subjects with the high risk of cardiovascular diseases were recruited. Subjects were administered TXL with the dose of 1110mg three times a day for 8 weeks. baPWV, ABI, Framingham risk score, Blood pressure and serum lipid profile were assessed at baseline and after 4 and 8weeks. Results: Total cholesterol, LDL cholesterol, triglyceride, total lipid and phospolipid significantly decreased after 4 weeks of medication. Total cholesterol, total lipid and phospolipid significantly decreased after 8 weeks of medication. There were no significant changes in Framingham risk scores, ABI, PWV and blood pressure. On safety assessment, there were no adverse effects, hepatic or renal toxicity. Conclusion: We suggest that TXL is a safe and useful herbal medicine for hyperlipidemia and as for anti-atherognic effects, further research would be necessary.
The ICAO (International civil aviation organization)recommended the implementation of the GANP (global air navigation plan) for strategic decision-making and air traffic management evaluation. In this study, we proposed a new method for finding the route distance from KPI (key performance indicator) 05 actual route extension presented for air traffic management evaluation. For this purpose, we collected trajectory data for one month and calculated the en-route distances using the methods presented in ICAO and the methods presented by this author. In the ICAO method, the intersection point must be estimated through the equation of a circle for radius 40 NM and the equation of a straight line for an inner and outer point close to a circle in the track data, and four flight distances are calculated to calculate the en-route distance. In the method presented in this study, two flight distances are calculated without estimating the intersection point to calculate the en-route distance. To determine the error between the two methods, we used the performance evaluation index RMSE (root mean square error) and the determination factor R2 of the regression model.
Sang-Hyeak Yoon;Yoon-Jin Choi;So-Hyun Lee;Hee-Woong Kim
Information Systems Review
/
v.22
no.4
/
pp.75-92
/
2020
As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.
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