• Nonlinear Functional Analysis and Applications
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• 제26권1호
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• pp.177-195
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• 2021

In this paper, we introduce the modification of a generalized (Ψ, L)-weak contraction and we prove some coincidence point results for self-mappings G, T and S, and some fixed point results for some maps by using a (c)-comparison function and a comparison function in the sense of a b-metric space.

• 전자공학회논문지C
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• 제36C권11호
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• pp.84-91
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• 1999

본 논문에서는 삼각함수와 양자화 된 삼각 퍼지함수를 가중퍼지평균(WFM: Weighted Fuzzy Mean)에 적용하여 비교하였다 또한 잡음의 특성에 따라서 영상에 포함된 잡음을 완전히 제거할 수 없는 단점을 개선하기 위하여, 계층적 구조의 결정기반 신경회로망(DBNN: Decision Based Neural Network)에 퍼지알고리즘을 적용하여서, 영상에 포함된 잡음을 제거하고 동시에 정보의 손실을 최소화하고 최적의 정보를 얻을 수 있는 고속 가중 퍼지결정 신경회로망(FDNN: fuzzy Decision Neural Network)을 구현하였다. 그리고 모의실험을 통하여 WFM과 FDNN의 성능을 비교하였으며, 보트(boats)의 영상에 대한 평균자승오차 (MSE:Mean Square Error)를 비교한 결과 제안된 FDNN이 우수함을 확인하였다.

• 한국자기공명학회논문지
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• 제2권2호
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• pp.131-140
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• 1998

The calcium-induced structural changes in the skeletal muscle regulatory protein troponin C (NTnC) involve a transition from a ‘closed’to an ‘open’structure with the concomitant exposure of a large hydrophobic interaction site for target proteins. Structural studies have served to define this conformational change and elucidate the mechanism of the linkage between calcium binding and the induced structural changes. There are now several structures of NTnC available from both NMR and X-ray crystallography. Comparison of the calcium bound structures reveals differences in the level of opening. We have considered the concept of a flexible open state of NTnC as a possible explanation for this apparent discrepancy. We also present simulations of the closed-to-open transition which are in agreement with the flexibility concept and with experimental energetics data.

• 대한통합의학회지
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• 제9권3호
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• pp.9-18
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• 2021

Purpose : In this study, we applied a computerized cognitive rehabilitation program (CoTras-C) for children with cerebral palsy. Research was conducted to investigate the impact of upper limb function, sensory function, and activities of daily living. Methods : The study period lasted 10 weeks from October 2019 to December 2019. The study subjects were 12 subjects according to the selection criteria, and a computerized cognitive rehabilitation program (CoTras-C) was conducted twice a week for 30 minutes before and after the application of basic occupational therapy. Results : As a result of the computerized cognitive rehabilitation program, scores of upper limb function (QUEST), sensory function (SSP-2), and daily life activity (WeeFIM) were significantly improved (p>.05). From the result of examining the motor area, improvement in fine-motor function and protective extension through touch pad or controller operation was found. It also showed improvement in activities of daily living including motor and activities of daily living including social cognition. In the sensory function evaluation, it was not significant in movement sensitivity. Significant differences were shown in the items excluding olfactory/taste sensitivity. Conclusion : The application of the computerized cognitive rehabilitation program (CoTras-C) showed significant results in upper limb function, sensory function, and daily life activities of children with brain lesions. Based on these results, future studies need to generalize the study by expanding the age or population of children with brain lesions, or by expanding the diversity of diseases and environments.

• Asian-Australasian Journal of Animal Sciences
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• 제12권3호
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• pp.331-335
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• 1999

The present study describes the analysis of the multiphasic growth function (MGF) to body weight in laboratory and wild mice. Three genetic groups of laboratory mice (Mus musculus domesticus) designated $CF_{{\sharp}1}$, C3H/HeNCrj and C57BL/6NCrj, and a genetic group of Yonakuni wild mice (Mus musculus molossinus yonakuni, Yk) were used. Mean body weights of each genetic group-sex subclass from birth to 69 days of age taken at 3-day intervals were analyzed by a monophasic, diphasic and triphasic functions for describing growth patterns. A comparison among the three functions of the MGF was based on the goodness-of-fit criteria: residual standard deviation (RSD), adjusted R-square (Adj $R^2$) and Akaike's information criterion (AIC). Result of this study indicated that body weight averaged heavier for males than for females. Among the four genetic groups within both sexes, $CF_{{\sharp}1}$ showed the highest, subsequent followed by C3H/HeNCrj, C57BL/6NCrj and Yk. Comparison among the three functions revealed that the triphasic function was the best fit to growth data, with the lowest RSD, the highest Adj $R^2$ and the lowest AIC, for the four genetic groups. For the triphasic function, RSD within each genetic group-sex subclass was similar for males and females. Adj $R^2$ was 0.999 for all genetic group-sex subclasses. AIC for laboratory mice males and females ranged from -70.48 to 66.50 and from -92.81 to -68.64, respectively; whereas for Yk wild mice males was -74.29 and females -78.42.

• International journal of advanced smart convergence
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• 제3권1호
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• pp.20-24
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• 2014

To compare body signal, was designed the F-B function system on the body movement for the comfortable state. To detect subject of the normal state, was decided on the base of physical signal in the body movement. There are to detect the condition of Vision, Vestibular, Somatosensory and CNS. Vision condition was verified a variation of greater average (Vi-${\Phi}_{AVG-AVG}$) was presented slightly greater at $17.424{\pm}9.65$ unit. Vestibular condition was identified a variation of slightly greater average (Ve-${\Phi}_{AVG-AVG}$) was presented at $9.068{\pm}1.478$ unit. Somatosensory condition was checked a variation of smaller average (So-${\Phi}_{AVG-AVG}$) was presented slightly smaller at $2.79{\pm}0.419$ unit. CNS condition was confirmed a variation of diminutive smaller average (C-${\Phi}_{AVG-AVG}$) was presented slightly larger at $0.557{\pm}0.153$ unit. As the model depends on the F-B function system of body movement, average values of these perturbation were computed F-B function comparison data. These systems will be to infer a data algorithm and a data signal processing system for the evaluation of the stability.

• 한국통신학회논문지
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• 제30권8C호
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• pp.754-761
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• 2005

본 논문에서는 나카가미-n(라이시안) 페이딩 채널 상에서 그레이 부호화된 직사각 QAM(Rectangular-QAM) 신호를 최대비 합성(maximal ratio combining) 다이버시티로 수신하는 경우 비트노율(Bit Error Rate, BER)을 계산하는 수식을 다양한 채널에 적용할 수 있도록 일반적 형태로 유도하고 그 성능 분석을 실시한다. 유도된 BER 수식은 휘태커 함수)Whittaker function)와 초기하 함수(confluent hypergeometric)로 표현된다. 또한 M-PSK와의 성능 비교를 통하여 나카가미-n 페이딩 채널의 특성을 확인한다. BER 수식이 일반적인 형태로 유도되었기 때문에 가시 경로(line-of-sight)를 가지는 통신채널이나 위성통신 채널의 성능분석에 본 논문에서 유도한 BER 수식을 쉽게 적용할 수 있다.

• 한국콘텐츠학회논문지
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• 제11권5호
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• pp.291-301
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• 2011

본 연구는 비교구매의 효과성 측정을 위한 모형을 제시하고 이를 통해 비교구매의 역할과 그 효과성을 설명한다. 또한 판매자 주도형 비교도전이 보다 효율적인 비교구매 정보의 제공 방법임을 증명한다. 구매자의 구매만족도(S)는 판매자의 제품경쟁력 벡터(P)와 구매자의 제품정보 인지수준 벡터(B)간의 상호작용으로 정의할 수 있으며, 구매자의 제품정보 인지수준은 제품 정보 분석을 통한 제품 간의 비교행렬(C)에 의해 변화된다. 비교구매 효과성은 비교 전과 후의 구매만족도의 변화량으로 측정되며, 비교구매의 역할은 비교행렬을 제공해 구매자의 제품정보 인지수준을 변화시키는 것이다. 보다 효율적인 방법은 판매자가 비교행렬의 구성요소 중에서 비교 효과성이 큰 경쟁 제품들에 능동적으로 비교하도록 하는 비교도전방법이다. 예제실험을 통해 일반적인 비교구매와 비교도전 전략이 모두 효과성 향상을 보였으며, 상대적으로 비교도전을 사용하는 비교구매 활용전략이 더 큰 효과성 향상을 보임을 확인하였다.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2005년도 e-Biz World Conference 2005
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• pp.130-134
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• 2005

This research describes the comparison broker's role and its effectiveness measurement using a developed logical framework of comparison shopping service. And verifies that seller-led comparison challenge method provide comparison information of products to buyers more efficiently. In electronic commerce, buyer's satisfaction of purchase (S) can be defined as an interactive function between seller's competitiveness vector (P) of products that supplied to the market, and buyer's informed level vector (B) of products that is known from a lot of sources. Then the buyer's informed level can be changed through the information analysis among products by transformation process using comparison matrix (C). So the role of comparison shopping is to construct a comparison matrix and to serve it to the buyers, and to change the buyer's informed level. The changed informed level influences a buyer's satisfaction, that improved satisfaction of purchase is defined as the effectiveness of comparison shopping. As a perfect provision and usage of comparison matrix is impossible cause of cognitive limit, the most efficient method for improving the comparison effectiveness is the comparison challenge that detects the comparison elements of the largest buyer's information efficiency, and then to be compared between elementary products selectively. This research verifies the substantial superiority of comparison challenge through television market data experiments.

• Journal of Electrical Engineering and Technology
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• 제7권4호
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• pp.636-645
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• 2012

This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the consequent part of the fuzzy rules is developed by using four types of polynomials, namely constant, linear, quadratic, and modified quadratic. Information granulation realized with C-Means clustering helps determine the initial values of the apex parameters of the membership function of the fuzzy neural network. To enhance the flexibility of neural network, we use the WLS learning to estimate the coefficients of the polynomials. In comparison with ordinary least square commonly used in the design of fuzzy radial basis function neural networks, WLS could come with a different type of the local model in each rule when dealing with the FRBFNN. Since the performance of the FRBFNN model is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules and the orders of the polynomials present in the consequent parts of the rules, we carry out both structural as well as parametric optimization of the network. The proposed IMSSA that aims at the simultaneous minimization of complexity and the maximization of accuracy is exploited here to optimize the parameters of the model. Experimental results illustrate that the proposed neural network leads to better performance in comparison with some existing neurofuzzy models encountered in the literature.