• 농업과학연구
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• 제47권3호
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• pp.667-672
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• 2020

It is well known that intensive selection caused a decline in reproductive performance in dairy cattle. Interestingly, the reproductive performances including fertility and calving interval of Korean native beef cattle have declined in the last 20 years, suggesting that a breeding program focusing on carcass weight and intramuscular fat may affect the reproductive physiology in Korean native beef cattle, too. In this study, we analyzed the calving interval (CI) and selection index (SI) based on genome-wide association studies (GWAS) of Hanwoo cows for seven years (2013 - 2019). Multiparous cows (4.5 ± 0.11) were analyzed, which were bred by artificial insemination (AI). We first examined the distribution of the AIs and calving dates. About 40% of the AIs were carried out in May to June and October to December; subsequently, calving was observed from March to April and August to October, respectively, indicating the cows were seasonally bred. No correlation between CI and SI was found (y = 0.0459x - 17.64; R² = 0.0356), but the ratio of cows with a positive SI was higher in the longer CI group compared to the shorter group, suggesting that the selection for meat quality and quantity may affect the reproductive performances. In addition, the average value of SI was - 3.42 in the CI < 400 while + 5.79 in the CI > 400 although the values were not statistically significant. However, our results suggest that reproductive indices such as fertility and CI should be considered for sustainability in the Hanwoo breeding selection program.

• 융합보안논문지
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• 제22권1호
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• pp.159-166
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• 2022

본 연구는 물리보안전공 대학생들의 전공 선택 동기가 전공만족도 및 진로결정에 미치는 영향을 파악하기 위해 설문조사를 수행하였다. 설문내용은 "첫째, 선택 동기, 둘째, 전공만족도, 셋째, 진로결정"으로 작성하였다. 본 연구에서는 변수의 신뢰도 및 중요도 분석, 탐색적 요인 등을 살펴보기 위해 Chronbach's Alpha 수치를 산출하고 베리맥스(Berimax) 방식을 실시하였다. 측정항목들의 AVE 값과 CR 값 모두 기준치 0.7 이상으로 산출되어 각 항목들의 집중타당성이 우호적인 것으로 조사되었다. 가설검증결과에서 표준화계수를 보면 '선택 동기 ⇨ 전공만족도'는 0.653으로, '전공만족도 ⇨ 진로결정'은 0.403으로 산출되어 두 연구가설은 채택되었으나 '선택 동기 ⇨ 진로결정'은 0.392로 기각되었다. 향후 경호전공 대학생들의 진로결정을 향상시키기 위해서는 선택 동기와 전공만족도를 동시에 높여주기 위해 대학과 관련 교수들의 노력이 더욱 필요해 보인다.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.904-914
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• 2008

An action-selection-mechanism(ASM) has been proposed to work as a fully connected finite state machine to deal with sequential behaviors as well as to allow a state in the task program to migrate to any state in the task, in which a primitive node in association with a state and its transitional conditions can be easily inserted/deleted. Also, such a primitive node can be learned by a shortest path-finding-based reinforcement learning technique. Specifically, we define a behavioral motivation as having state-dependent value as a primitive node for action selection, and then sequentially construct a network of behavioral motivations in such a way that the value of a parent node is allowed to flow into a child node by a releasing mechanism. A vertical path in a network represents a behavioral sequence. Here, such a tree for our proposed ASM can be newly generated and/or updated whenever a new behavior sequence is learned. To show the validity of our proposed ASM, experimental results of a mobile robot performing the task of pushing- a- box-in to- a-goal(PBIG) will be illustrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권10호
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• pp.3409-3422
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• 2014

The frequency spectrum available for the wireless communication is extremely crowded. In order to improve the spectral efficiency, the two-way relay networks have aroused great attention. A simple $N^{th}$ best-relay selection criterion for the opportunistic two-way relay networks is proposed, which can be implemented easily by extending the distributed timer technique in practice, since the proposed criterion is mainly based on the channel gains. The outage performance of the proposed relay selection scheme is analyzed under the outdated channel state information (CSI), and a tight closed-form lower bound and asymptotic value of the outage probability over Rayleigh fading channels are obtained. Simulation results demonstrate that the tight closed-form lower bound of the outage probability very closely matches with simulated ones in the whole SNR region, and the asymptotic results provide good tight approximations to the simulation ones, especially in the high SNR region.

• 한국정보전자통신기술학회논문지
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• 제8권5호
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• pp.384-393
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• 2015

본 논문은 두 가지 속성 삭제 방법인 ReliefF와 SVM-REF를 조합하여 유전자 선택을 위한 속성 삭제에 기반을 둔 최적화된 분류법(OCFE)을 제안한다. ReliefF 알고리즘은 데이터의 중요도에 따라 데이터 순위를 매기고 필터(filter) 속성 선택 알고리즘이다. SVM-RFE 알고리즘은 속성의 가중치 기반으로 데이터 순위를 매기고 데이터를 감싸는 래퍼(wrapper) 속성 선택 알고리즘이다. 이러한 두 가지 기법을 조합함으로써, 우리는 SVM-RFE는 0.3096779이고 OCFE는 0.3016138으로 에러율 평균이 좀 더 낮게 나타났다. 또한, 제안된 기법은 SVM-RFE가 69%이고 OCFE는 70%으로 좀 더 정확한 것으로 나타났다.

• ETRI Journal
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• 제41권5호
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• pp.626-636
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• 2019

A novel algorithm for joint user selection and optimal power allocation for Stackelberg game-based revenue maximization in a downlink non-orthogonal multiple access (NOMA) network is proposed in this study. The condition for the existence of optimal solution is derived by assuming perfect channel state information (CSI) at the transmitter. The Lagrange multiplier method is used to convert the revenue maximization problem into a set of quadratic equations that are reduced to a regular chain of expressions. The optimal solution is obtained via a univariate iterative procedure. A simple algorithm for joint optimal user selection and power calculation is presented and exhibits extremely low complexity. Furthermore, an outage analysis is presented to evaluate the performance degradation when perfect CSI is not available. The simulation results indicate that at 5-dB signal-to-noise ratio (SNR), revenue of the base station improves by at least 15.2% for the proposed algorithm when compared to suboptimal schemes. Other performance metrics of NOMA, such as individual user-rates, fairness index, and outage probability, approach near-optimal values at moderate to high SNRs.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.153-160
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• 2009

The demand for super tall building construction is increasing worldwide. There has been a constant request for achieving early payback on investment by shortening the construction time. This pertains especially for the case of huge investment projects such as super tall building construction. It is very important to shorten the construction time for the building framework, which requires substantial construction time and cost, and this is directly related to the establishment of an optimum lift plan for construction. When there is a problem in the selection of the lift equipment, it is almost impossible to revise the selection, resulting in a possible failure of the project. Thus, the purpose of this study is to analyze the function and logic for the development of the process for the selection of lift equipment for super tall building projects and further development of making the analyzed process into a system. In line with this research objective, the process of selecting the optimum lift equipment by domestic construction company was investigated and analyzed as well as collecting the actual field data. The actual data were obtained by sensors installed on tower cranes at three construction sites with the help from the construction company.

• 한국임상약학회지
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• 제34권1호
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• pp.62-70
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• 2024

Background: Drug-related problems have the potential to threaten patient health, and pharmacists are in a position to prevent such problems through prescription reviews and patient counseling, actively engaging in pharmaceutical care activities. This study aims to categorize and analyze the intervention activities of pharmacists in community pharmacies concerning drug-related problems, following international criteria. Methods: Over a six-month period, prescription interventions completed in a community pharmacy in Seoul were selected as the research subjects. The causes of interventions were classified according to the Pharmaceutical Care Network Europe (PCNE) drug-related problems (DRPs) classification system and the types and frequencies of DRPs were identified. Results: Among a total of 49,334 prescriptions, 527 interventions were completed, constituting approximately 1.07% of the daily average filled prescriptions. Individuals over 60 years of age represented more than 50%. The primary cause of DRPs was prescribing and drug selection issues, comprising 256 cases (48.58%), with specific subcategories including 109 cases of drug selection, 79 cases of treatment duration errors, 47 cases of dose selection, and 21 cases of inappropriate dosage form selection. Patient-related issues accounted for 204 cases (38.71%). Conclusion: The study demonstrated that the pharmacists' intervention in community pharmacies contributes to the safe use of medication by patients.

• 대한간호학회지
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• 제37권3호
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• pp.414-421
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• 2007

Background: Nursing intervention studies often suffer from a selection bias introduced by failure of random assignment. Evaluation with selection bias could under or over-estimate any intervention's effects. PS matching (PSM) can reduce a selection bias through matching similar Propensity Scores (PS). PS is defined as the conditional probability of being treated given the individual's covariates and it can be reused to balance the covariates of two groups. Purpose: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. Method: An intervention study for patients with some baseline individual characteristic differences between two groups was used for this demonstration. The result of a t-test with PSM was compared with a t-test without matching. Results: The level of HbA1c at 12 months after baseline was different between the two groups in terms of matching or not. Conclusion: This study demonstrated the effects of a quasi-random assignment. Evaluation using PSM can reduce a selection bias impact that affects the result of the nursing intervention. Analyzing nursing research more objectively to reduce selection bias using PSM is needed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.