Earticle

The nature accompanies with natural and ecological truth, worsening living environment without think using of our nature. Now, the sustainable researches to study peculiarities in ecological dwellings considered with nature and the development of human life's quality in housing itself, have been progressing. Also it is needed to show understanding about ecological dwellings in the user participant's consciousness such as, unification thought with nature, circulation thought of substance, and environment friendly thought of the traditional housing. Chose five examples which is applying ecological architectural concept by each Chungbuk, Chungnam, Jeonbuk, Gyeongbuk, Gyeonggi district and I investigated change of exterior or interior material, application of ecological system, and etc. With these background, this study will survey cases of ecological dwellings and find peculiar characteristics of ecological dwellings through researching the correlation between the concept in user's consciousness and application method.

Cities in Indonesia include diverse scattered industrial centers comprising industries that can sustain the existing economic pace. For industrial data collection, the city government still relies on census that consumes extensive time and money. The public are unfamiliar with industries owing to their lack of industry information; therefore, the market share is not optimal. In addition, the opportunity to procure investors for business development is limited. A Geographic Information System (GIS) is a computer system that can record, store, write, analyze, and display geographical data. Using the Rapid Application Development (RAD) method, GIS was developed on a website platform to provide information on industry profiles, types of production, investment values, industry maps, and industrial locations in each village and sub-district to a wider community. The RAD method was chosen compared to the waterfall method because it could accelerate website development process.

The main purpose of this paper is to establish the high temperature structural integrity evaluating procedures for the next generation reactors, which are to be operated at over 500$^{\circ}C$ and for 60 years. To do this, comparison studies of the high temperature structural design codes and assessment procedures such as the ASME-NH (USA), RCC-MR (France), DDS (Japan), and R5 (UK) are carried out in view of the accumulated inelastic strain and the creep-fatigue damage evaluations. Also the application procedures of the ASME-NH rules with the actual thermal and structural analysis results are described in detail. To overcome the complexity and the engineering costs arising from a real application of the ASME-NH rules by hand, all the procedures established in this study such as the time-dependent primary stress limits, total accumulated creep ratcheting strain limits, and the creep-fatigue damage limits are computerized and implemented into the SIE ASME-NH program. Using this program, the selected high temperature structures subjected to two cycle types are evaluated and the parametric studies for the effects of the time step size, primary load, number of cycles, normal temperature for the creep damage evaluations and the effects of the load history on the creep ratcheting strain calculations are investigated.

All the imputation techniques proposed so far in literature for data imputation are offline techniques as they require a number of iterations to learn the characteristics of data during training and they also consume a lot of computational time. Hence, these techniques are not suitable for applications that require the imputation to be performed on demand and near real-time. The paper proposes a computational intelligence based architecture for online data imputation and extended versions of an existing offline data imputation method as well. The proposed online imputation technique has 2 stages. In stage 1, Evolving Clustering Method (ECM) is used to replace the missing values with cluster centers, as part of the local learning strategy. Stage 2 refines the resultant approximate values using a General Regression Neural Network (GRNN) as part of the global approximation strategy. We also propose extended versions of an existing offline imputation technique. The offline imputation techniques employ K-Means or K-Medoids and Multi Layer Perceptron (MLP)or GRNN in Stage-1and Stage-2respectively. Several experiments were conducted on 8benchmark datasets and 4 bank related datasets to assess the effectiveness of the proposed online and offline imputation techniques. In terms of Mean Absolute Percentage Error (MAPE), the results indicate that the difference between the proposed best offline imputation method viz., K-Medoids+GRNN and the proposed online imputation method viz., ECM+GRNN is statistically insignificant at a 1% level of significance. Consequently, the proposed online technique, being less expensive and faster, can be employed for imputation instead of the existing and proposed offline imputation techniques. This is the significant outcome of the study. Furthermore, GRNN in stage-2 uniformly reduced MAPE values in both offline and online imputation methods on all datasets.

The direct position determination (DPD) approach is a single-step method which uses the Maximum Likelihood estimator to localize sources emitting electromagnetic energy using combined data from all available sensors. The DPD is known to outperform the traditional 2-step methods under low Signal to Noise Ratio (SNR) conditions. We propose an improvement to the DPD approach, using the well known minimum-variance-distortionless-response (MVDR) approach. Unlike Maximum Likelihood, the number of sources need not be known before applying the method. The combination of both the direct approach and MVDR yields unprecedented localization accuracy and resolution for weak sources. We demonstrate this approach on the problem of multistatic radar, but the method can easily be extended to general localization problems.

IBM (Immersed Boundary Method) with feedback momentum forcing was applied to stationary and moving bodies. The capability of IBM to treat the obstacle surfaces, especially with moving effect has been tested for two dimensional problems. Stationary and oscillating cylinders were simulated by using IBM based on finite volume method with Cartesian coordinates. For oscillating cylinder, lateral and vertical motions are considered, respectively. Present results such as time histories of drag and lift coefficients for both stationary and oscillating cases are in good agreement with previous numerical and experimental results. Also, the instantaneous wake patterns of oscillating cylinder with different oscillating frequency ratios well represented those of previous researches. More feasibility study for IBM has been carried out to two oscillating cylinders. Drag and lift coefficients are presented for two cylinders oscillating sinusoidally with phase difference of $180^{\circ}$.

Purpose: This study applied the Q method to identify and describe the various types of nurse perceptions that are crucially associated with their engagement in evidence-based nursing (EBN). Methods: The study participants were nurses at a medical center and a regional teaching hospital. A series of Q sorts was performed by nurses to subjectively rank the Q statements. Q statements were constructed based on the literature related to EBN adoption by nurses and face-to-face interviews. Results: A total of 60 participants were invited to rank 44 Q statements related to EBN. Factor analysis was conducted on the rankings of the Q statements. The following are the five prominent shared perspectives: (1) emphasized the obstacles to evidence searching and reading ability; (2) emphasized the organizational promotive strategies; (3) emphasized the available supportive resources; (4) emphasized the significance of EBN; and (5) emphasized the evidence-searching ability and external incentives. The five identified groups of perspectives can enhance hospital administrators to acknowledge the barriers and incentives associated with EBN practices. Conclusion: The exploration of clustering nurses' perceptions may facilitate the development of customized strategies to enable more appropriate training.

This paper introduces the equivalent frequency response method(EFRM) into runoff analysis. This EFRM originally had been developed to analyze dynamic behavior of nonlinear elements such as threshold and saturation in control engineering. Many runoff models are described by nonlinear ordinary of partial differential equations This paper presents that these nonlinear differential equations can be converted into semi-linear ones based on EFRM. The word of "a semi-linear equation" means that the coefficients of derived equations depend on average rainfall.

To secure the anticorrosive performance of structures in the oceanic environment it is necessary to select appropriate finishing materials and thickness of cover. However, airborne chloride deposition varies depending on the collector used, and it is difficult to select appropriate finishing materials. For this reason, an eight-directional collector is proposed in this study through reviewing the differences between existing airborne chloride collectors and the new one. To analyze airborne chloride deposition according to the direction from which it flows and verify the performance of the collector proposed in this study, airborne chlorides were deposited on the collector for one year at five different locations in an oceanic environment. From the experiment, it was verified that in terms of direction, there were differences in airborne chloride deposition of up to more than 1.5 times. Based on these research findings, the anti-corrosive method applied can be different for each side of a building's structure, and this is believed to serve as an effective and systemic chloride resistance design.

본 논문의 연구 목적은 다음의 2가지를 가지고 있다：(1) “개인 집단 관계 시스템(SPGR)에 대한 개관, (2) 한국, 일본, 노르웨이, 미국 등 4개 문화의 근무집단으로부터 수집된 자료에 대한 문화비교적 분석연구 실시. 이상 4개 이문화에서 수집된 집단 자료는 SPGR 분석 방법인 “ 장 분석” 및 “지배적 행동(벡터) 분석”을 통해서 사회적 상호 작용 유형을 비교하였다. 본연구에서 얻은 결과에 의하면 미국 문화를 제외한 3개 문화 즉 노르웨이, 일본 및 한국은 상호 유사한 대인 평가 유형을 보여주었다. 추가적으로 리더십, 전략개발, 팀 빌딩 그리고 갈등 관리를 SPGR모델에 입각해서 다루고 마지막으로 4개 문화 집단에 대한 집단 역동을 논의하였다.

The purpose of this paper is twofold：first it gives an overview of the “Systematizing Person-Group Relation” (SPGR) model and method, and second, it presents an empirical study based on data collected from Korean, Japanese, Norwegian and American workgroups. The samples of groups are compared by their pattern of social interaction using two different SPGR analyses：the field and predominant behavior (vector) analysis. THE FIDINGS INDICATE THAT THREE CULTURE GROUPS SHOW SIMILARITY OF INTERPERSONAL EVALUATION HOWEVER AMERICAN GROUPS SHOW AN EXCEPTION. The implications of these findings are discussed in relation to leadership, strategy development, teambuilding, and conflict resolution. In addition the typical group dynamics for the four different cultures is described.

The properties of pulsed photostimulated luminescence (PPSL) were measured to use as basis data for the detection of irradiated foodstuffs (34 different foods). Samples were packed in polyethylene bags and irradiated at 1, 5, and 10 kGy with a dose rate of 10 kGy/h. The samples irradiated were introduced in the sample chamber without other preparation and measured PPSL photon counts for 60 and 120 s. The PPSL photo counts of the irradiated samples were higher than the unirradiated, increased with increasing irradiation dose, and showed a good relationship between irradiation doses and photon counts in a multinomial expression. These results suggest that the detection of irradiated foodstuffs was possible by PPSL. Therefore, PPSL can be proposed as the method for the detection of irradiated foodstuffs.

Collaborative optimization (CO) is a multi-level decomposed methodology for a large-scale multidisciplinary design optimization (MDO). CO is known to have computational and organizational advantages. Its decomposed architecture removes a necessity of direct communication among disciplines, guaranteeing their autonomy. However, CO has several problems at convergence characteristics and computation time. In this study, such features are discussed and some suggestions are made to improve the performance of CO. Only for the system level optimization, genetic algorithm is used and gradient-based method is used for subspace optimizers. Moreover, response surface models are replaced as analyses in subspaces. In this manner, CO is applied to aero-structural design problems of the aircraft wing and its results are compared with the multidisciplinary feasible (MDF) method and the original CO. Through these results, it is verified that the suggested approach improves convergence characteristics and offers a proper solution.

Objective To present new classification methods of knee osteoarthritis (KOA) using machine learning and compare its performance with conventional statistical methods as classification techniques using machine learning have recently been developed. Methods A total of 84 KOA patients and 97 normal participants were recruited. KOA patients were clustered into three groups according to the Kellgren-Lawrence (K-L) grading system. All subjects completed gait trials under the same experimental conditions. Machine learning-based classification using the support vector machine (SVM) classifier was performed to classify KOA patients and the severity of KOA. Logistic regression analysis was also performed to compare the results in classifying KOA patients with machine learning method. Results In the classification between KOA patients and normal subjects, the accuracy of classification was higher in machine learning method than in logistic regression analysis. In the classification of KOA severity, accuracy was enhanced through the feature selection process in the machine learning method. The most significant gait feature for classification was flexion and extension of the knee in the swing phase in the machine learning method. Conclusion The machine learning method is thought to be a new approach to complement conventional logistic regression analysis in the classification of KOA patients. It can be clinically used for diagnosis and gait correction of KOA patients.

The existing electrical engineering design method and the dynamic objective function in the application process of automatic control system fail to meet the unbounded condition, which affects the control tracking accuracy. In order to improve the tracking control accuracy, this paper studies the electrical engineering design method based on neural network and the application of automatic control system. This paper analyzes the structure and working mechanism of electrical engineering automation control system by an automation control model with main control objectives. Following the analysis, an optimal solution of controllability design and fault-tolerant control is figured out. The automatic control power coefficient is distributed based on an ideal control effect of system. According to the distribution results, an automatic control algorithm is based on neural network for accurate control. The experimental results show that the electrical automation control method based on neural network can significantly reduce the control following error to 3.62%, improve the accuracy of the electrical automation tracking control, thus meeting the actual production needs of electrical engineering automation control system.

Mirtazapine is an antidepressant agent with dual action on both the noradrenergic and serotonergic neurotransmitter systems. A simple high performance liquid chromatographic method has been developed and validated for the quantitative determination of mirtazapine in human plasma. A reversed-phase Cl8 column was used for the determination of mirtazapine with a mobile phase composed of 0.01M ammonium acetate solution (pH 4.2) and acetonitrile (75:25, v/v%) at a flow rate of 1.2 mL/min. Terazosin hydrochloride was used as an internal standard. The fluorescence detector was set at excitation and emission wavelengths of 290 and 350 nm, respectively. Intra- and inter-day precision and accuracy were acceptable for all quality control samples including the lower limit of quantification of 3 ng/mL. Mirtazapine was stable in human plasma under various storage conditions. This method was used successfully for a pharmacokinetic study using plasma samples after oral administration of a single 30 mg dose as mirtazapine base to 8 healthy volunteers. The maximum plasma concentration of mirtazapine was $64.1{\pm}28.0ng/mL$ at 1.8 h, and the area under the curve and elimination half-life were calculated to be $674.1{\pm}218.5ng\;h/mL\;and\;23.4{\pm}3.8h$, respectively.

Prazosin hydrochloride is an antihypertensive drug with selective ${\alpha}_1$-adrenoreceptor blocking effects. A simple high performance liquid chromatographic method has been developed and validated for the quantitative determination of prazosin in human plasma. A reversed-phase C18 column was used for the separation of prazosin and terazosin (internal standard) with a mobile phase composed of water, acetonitrile and triethylamine(75:25:0.1, V/V;pH5.0) at a flow rate of 1.5 ml/min. the fluorescence detector was set at excitation and emissionwavelengths of 250 and 370 nm, respectively. Intra-and inter-day precision and accuracy were acceptable for all quality control samples including the lower limit of quantification of 0.5 ng/ml. Good recovery (>80%) was seen in plasma. Prazosin was stable in human plasma under various storage conditions. This method was used successfully for a pharmacokinetic study in plasma after oral administration of a single 2-mg dose as prazosin base to 16 healthy volunteers. The maximum plasma concentration of prazosin was 23.1 ${\pm}$ 16.5 ng/ml at 2.1 h, and the mean area under the curve and elimination half-life were calculated to be 108.4 ${\pm}$ 74.2 ng ${\cdot}$hr/ml and 2.5 ${\pm}$ 0.6 h, respectively.

This review study discusses the utilization of Terrestrial Laser Scanner (TLS) 3D point cloud data in representing geometry for structural health monitoring (SHM) applications, particularly the so-called Scan-to-FEM method. The existing studies related to the topic are intensively presented and discussed along with the advantages and disadvantages of the modelling methods: meshing by whole and cross-section. Two case studies are conducted to show both modelling methods used for geometry representation for Scan-to-FEM method. Meshing by whole and cross-section methods result in the relative errors of respective 2.79% and 1.4% in the maximum displacement vector sum, compared to their reference models constructed by ABAQUS. It is also seen that the density and clarity of 3D point cloud data can bring well-shaped geometry for FE analysis and consequently produce good accuracy.

Background: At nuclear facilities and decommissioning sites, monitoring radioactivity concentrations in airborne particulates is crucial to prevent worker exposure. To avoid internal exposure, alpha-decay radionuclides must be detected. When monitoring alpha-decay radionuclides in airborne dust, we want to measure the concentration of only artificial radionuclides (e.g. , 238Pu, 239Pu, 240Pu, 235U, 238U, 241Am, and 244Cm). The radioactivity concentration must be measured separately for artificial (4.3–5.8 MeV) and natural radionuclides (212Bi, 214Po, and 212Po at 6.0, 7.7, and 8.8 MeV, respectively). Materials and Methods: We created response functions for various alpha-ray energies using a radiation simulation toolkit. Utilizing these response functions, we deconvolved the alpha-ray energy spectra measured while collecting dust on filter paper. To ensure the precision of the response function, we prepared a model including the distance between the filter and the detector and the structure of the light shield in detail. Results and Discussion: The deconvolved spectra had three clear peaks at 6.0, 7.7, and 8.8 MeV. These energies were consistent with those of 212Bi, 214Po, and 212Po. The deconvolved energy spectra showed that only a few measurements (4.0–5.8 MeV) were included in the energy range due to artificial radionuclides. From these measurements, the decision threshold for artificial radionuclides was determined to be about 1.5×10−7 Bq/cm3. Conclusion: Our findings demonstrated that we could measure artificial and natural radionuclides separately with the deconvolved alpha-ray energy spectra. Specifically, we were able to monitor artificial radionuclides down to low radioactivity concentrations in 10-minute measurements.