• The Journal of Industrial Distribution & Business
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• v.13 no.5
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• pp.15-26
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• 2022

Purpose: There has been a consistent failure of businesses that are run by a single person. Most of these collapse at infancy prematurely and those that survive continue to operate at minimal capacity. The study thus sought to enhance growth of sole proprietors from being small entities to large corporates. Financial determinants of business growth were earmarked for research as they were amongst the grey areas of business growth research. Research design, data and methodology: The target population of the study was made up of groceries retail sole proprietors operating in Epworth, Zimbabwe. Questionnaires were used in a once-off cross-sectional survey using stratified random sampling. Through a deductive research approach, four financial determinants of business growth were established namely financial availability, financial management, financial evaluation and financial investment (AMEI). These constructs formulated the basis for the development of the model which linked financial factors to business growth. Results: The study found out that all four financial determinants were statistically significant (P < 0.05) in predicting business growth. Conclusions: The study concludes that the model tested was useful in explaining sole proprietor's business growth. Sole proprietors should have access to funding, manage received funds in an appropriate manner, invest into the business and evaluate their business processes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.4
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• pp.352-359
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• 2012

An experiment was carried out to figure out the turbulence flow characteristics in the wake of the transom stern's 2-dimensional section by 2-frame grey level cross correlation PIV method at Re= $3.5{\times}10^3$, Re= $7.0{\times}10^3$. The angles of transom stern are $45^{\circ}$(Model "A"), $90^{\circ}$(Model "B") and $135^{\circ}$(Model "C") respectively. The depth of wetted surface is 40mm from free surface. Strong turbulence intensity appears at the interaction between the flow separation of the bottom of a model and the free surface. This study provides statistic flow information such as turbulence intensity, Reynolds stress and turbulence kinetic energy. Model C type (Raked transom) has low Reynolds stress and turbulence kinetic energy.

• Korean Journal of Agricultural Science
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• v.7 no.2
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• pp.131-144
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• 1980

The Linear Regression Model to extend the monthly runoff data in the short-recorded river was proposed by the author in 1979. Here in this study generalization precedure is made to apply that model to any given river basin and to any given station. Lengthier monthly runoff data generated by this generalized model would be useful for water resources assessment and waterworks planning. The results are as follows. 1. This Linear Regression Model which is a transformed water-balance equation attempts to represent the physical properties of the parameters and the time and space varient system in catchment response lumpedly, qualitatively and deductively through the regression coefficients as component grey box, whereas deterministic model deals the foregoings distributedly, quantitatively and inductively through all the integrated processes in the catchment response. This Linear Regression Model would be termed "Statistically deterministic model". 2. Linear regression equations are obtained at four hydrostation in Geum-river basin. Significance test of equations is carried out according to the statistical criterion and shows "Highly" It is recognized th at the regression coefficients of each parameter vary regularly with catchment area increase. Those are: The larger the catchment area, the bigger the loss of precipitation due to interception and detention storage in crease. The larger the catchment area, the bigger the release of baseflow due to catchment slope decrease and storage capacity increase. The larger the catchment area, the bigger the loss of evapotranspiration due to more naked coverage and soil properties. These facts coincide well with hydrological commonsenses. 3. Generalized diagram of regression coefficients is made to follow those commonsenses. By this diagram, Linear Regression Model would be set up for a given river basin and for a given station (Fig.10).

• Fashion & Textile Research Journal
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• v.7 no.3
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• pp.291-300
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• 2005

The purpose of this study is to investigate, analyze the purchasing behavior of fashion goods according to life style and role model of preteen generation, and provide manager or marketing planner for the reference data so that they can understand preteen generation and make proper strategy efficiently. So called, preteen market focusing on 1014 generation (from ten to fourteen years old) is highlighted. This generation created between the year 1989 to 1993 after Seoul Olympic monopolize parent's love in abundant economic environment and rise to the core of consumption subject. Products aiming at this preteen generation continuously though consumption mind was shrunk greatly due to recession. Only 2~3 years before preteen market was regarded as grey zone which doesn't belong to not only children (between six and nine years old) but also teenagers (between fifteen to eighteen years old). But in recent day their purchasing powers have increased rapidly and age group is divided on details, so that preteen market has become a niche market. Subjects were 333 persons consisting of students in the 4th~6th grade of primary school and the 1st~2nd grade of middle school in Daegu city. Measuring instruments are as follows: 5questions to differentiate preteen generation, 22 questions to measure life style, 17questions (which have six sub-factors such as purchase motive, factor of product selection, utilization of informant, purchase time, purchase place, and purchase method) to measure the purchase behavior of fashion goods measurement, and 16 questions (which have four sub-factors such as parent, entertainer & sports stars, brothers and sisters, friends) to measure model of role. Statistical data were processed by SPSS 10.0 programs. Frequencies, Factor analysis, Cluster analysis, ANOVA, Cross analysis, Multiplex regression analysis, and Duncan's multiple range test were carried out.

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.805-810
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• 2011

An experiment was carried out to figure out the instantaneous flow characteristics in the wake of the transom stern's 2-dimensional section by 2-frame grey level cross correlation PIV method at $Re=3.5{\times}103$, $Re=7.0{\times}103$. The stern angles of models were learning at $45^{\circ}$(Model "A"), $90^{\circ}$(Model "B") and $135^{\circ}$(Model "C") respectively based on the survey results of real ships. The depth of wetted surface is 40mm from free surface. As Reynolds number increases, vortices increase in volume and move their way to the downstream. Flow separation appeared at the end of model's bottom.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.187-194
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• 2019

Traditional demand forecasting methods are difficult to meet the needs of companies due to rapid changes in the market and the diversification of individual consumer needs. In a diversified production environment, the right demand forecast is an important factor for smooth yield management. Many of the existing predictive models commonly used in industry today are limited in function by little. The proposed model is designed to overcome these limitations, taking into account the part where each model performs better individually. In this paper, variables are extracted through Gray Relational analysis suitable for dynamic process analysis, and statistically predicted data is generated that includes characteristics of historical demand data produced through ARIMA forecasts. In combination with the LSTM model, demand forecasts can then be calculated by reflecting the many factors that affect demand forecast through an architecture that is structured to avoid the long-term dependency problems that the neural network model has.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.477-486
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• 2008

Facial expression, which changes face geometry, usually has an adverse effect on the performance of a face recognition system. To improve the face recognition rate, we propose a normalization method of facial expression to diminish the difference of facial expression between probe and gallery faces. Two approaches are used to facial expression modeling and normalization from single still images using a generic facial muscle model without the need of large image databases. The first approach estimates the geometry parameters of linear muscle models to obtain a biologically inspired model of the facial expression which may be changed intuitively afterwards. The second approach uses RBF(Radial Basis Function) based interpolation and warping to normalize the facial muscle model as unexpressed face according to the given expression. As a preprocessing stage for face recognition, these approach could achieve significantly higher recognition rates than in the un-normalized case based on the eigenface approach, local binary patterns and a grey-scale correlation measure.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.4
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• pp.371-377
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• 2012

This paper presents an experimental investigation to figure out slamming impact pressure and flow characteristics of a rectangular Marine structure($800{\times}250{\times}50mm^3$) in free fall. The flow field has been obtained by 2-frame grey level cross correlation PIV(Particle Image Velocimetry) method, the impact pressure of the free fall model by a pressure acquisition system(Dewatron). The angles between a model and the free surface are adapted $10^{\circ}$ and $20^{\circ}$ respectively. Velocity field of water exit has higher better than water entry. The highest point, P2 of impact pressure under the bottom of the model has been appeared about 6 % higher values at 20 degrees than 10 degrees.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.363-372
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• 2017

This paper presents a novel face recognition algorithm based on the deep convolution neural network and key point detection jointed local binary pattern methodology to enhance the accuracy of face recognition. We firstly propose the modified face key feature point location detection method to enhance the traditional localization algorithm to better pre-process the original face images. We put forward the grey information and the color information with combination of a composite model of local information. Then, we optimize the multi-layer network structure deep learning algorithm using the Fisher criterion as reference to adjust the network structure more accurately. Furthermore, we modify the local binary pattern texture description operator and combine it with the neural network to overcome drawbacks that deep neural network could not learn to face image and the local characteristics. Simulation results demonstrate that the proposed algorithm obtains stronger robustness and feasibility compared with the other state-of-the-art algorithms. The proposed algorithm also provides the novel paradigm for the application of deep learning in the field of face recognition which sets the milestone for further research.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.3
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• pp.68-77
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• 1989

The surface rolling for cylindrical surface of a grey cast iron was carried out using a lathe with a simple newly-designed tool system. A surface rolling tool used was steel ball whose diameter was 3/8 inch (9.525mm) The effects of rolling feeds and number of rolling on surface rolling were investigated. The contact pressure between ball and workpiece which was considered as Hertz's contact problem was examined and the track of motion of a ball on the cylindrical surface of a work- piece was measured according to the rolling feed. The results obtained were as follows; 1. The roughness of the machined surface which was originally 5.3 .approx. 28 umRz decreased to 1.2 .approx. 5 umRz according to rolling feeds and numbers of rolling. 2. The hardness increased from Hv 260 to Hv 290 .approx. 310 through 2 .approx. 4 rollings according to the roughness of machined surfaces. 3. The reduction of diameter was found to be proportional to the variations of roughness of previous machined surfaces. About 60% to 90% of reduction in diameter was made during the first rolling process. 4. An equation relating the reduction of diameter and the variation of surface roughness after surface rolling was presented using a geometric surface model. 5. An equation for the calculation of dynamic contact area between pressure ball and workpiece according to the rolling feed was presented.