• Management Science and Financial Engineering
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• v.8 no.2
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• pp.33-45
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• 2002

This study suggests an approach for determining fleet size for LTL (less -than-truckload) transportation with dynamic demand for on-time supply of the parts between the assembly line in an automobile company and its part suppliers in Korea. The vehicles operated by the transportation trucking companies in Korea in general can be classified into three types depending on the ways how their expenses occur; company -owned truck, mandated truck which is owned by outsider who entrusts the company with its operation, and rented truck (outsourcing) . With the forecasted monthly production data a year, a heuristic algorithm is developed to determine the number of company-owned trucks, mandated trucks, and rented trucks in order to minimize the expected annual operating cost, which is based on the solution technologies used in the aggregate production planning and vehicle routing problem. Finally the algorithm is tested for the problem how the trucking company transports parts for the automobile company.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.101-121
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• 2009

The research literature presents that Total Quality Management (TQM) has been successfully embraced by firms for strategic and operational management in the last decades. However few studios analyze the role of TQM practices in the R&D environment. The objective of this study is to evaluate TQM practices implemented in manufacturing-based R&D organizations with respect to R&D performance. Our research model is primarily based on Malcolm Baldrige Criteria for Performance Excellence framework, including three moderating variables (industry type, organization size, quality management system certification), to propose hypotheses on the relationships between leadership practice, management practice and R&D performance. Results of canonical correlation analysis using data from 130 R&D organizations show that in aggregate leadership practice is positively related to management practice which is, in turn, positively related to R&D performance. These relationships are, however, affected by the moderating variables. Our results imply that TQM practices can be strategically adopted in the R&D organization.

• Steel and Composite Structures
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• v.29 no.1
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• pp.67-75
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• 2018

High performance concrete (HPC) depends on various parameters such as the type of cement, aggregate and water reducer amount. Generally, the ready concrete company in various regions according to the requirements and costs, mix design of concrete as well as type of cement, aggregates, and, amount of other components will vary as a result of moment decisions or dynamic optimization, though the ideal conditions will be more applicable for the design of mix proportion of concrete. This study aimed to apply dynamic optimization for mix design of HPC; consequently, the objective function, decision variables, input and output variables and constraints are defined and also the proposed dynamic optimization model is validated by experimental results. Results indicate that dynamic optimization objective function can be defined in such a way that the compressive strength or performance of all constraints is simultaneously examined, so changing any of the variables at each step of the process input and output data changes the dynamic of the process which makes concrete mix design formidable.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.824-826
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• 1999

In this paper, we design an Fuzzy-Neural Networks(FNN) by means of divisions of fuzzy input space with multi-input variables. Fuzzy input space of Yamakawa's FNN is divided by each separated input variable, but that of the proposed FNN is divided by mutually combined input variables. The membership functions of the proposed FNN use both triangular and gaussian membership types. The parameters such as apexes of membership functions, learning rates, momentum coefficients, weighting value, and slope are adjusted using genetic algorithms. Also, an aggregate objective function(performance index) with weighting value is utilized to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the data of sewage treatment process.

• Structural Engineering and Mechanics
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• v.52 no.1
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• pp.97-113
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• 2014

In the present work appropriate concrete material models have been proposed to predict drying shrinkage and specific creep of High-performance concrete (HPC) using Artificial Neural Network (ANN). The ANN models are trained, tested and validated using 106 different experimental measured set of data collected from different literatures. The developed models consist of 12 input parameters which include quantities of ingredients namely ordinary Portland cement, fly ash, silica fume, ground granulated blast-furnace slag, water, and other aggregate to cement ratio, volume to surface area ratio, compressive strength at age of loading, relative humidity, age of drying commencement and age of concrete. The Feed-forward backpropagation networks with Levenberg-Marquardt training function are chosen for proposed ANN models and same implemented on MATLAB platform. The results shows that the proposed ANN models are more rational as well as computationally more efficient to predict time-dependent properties of drying shrinkage and specific creep of HPC with high level accuracy.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05b
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• pp.81-84
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• 2006

Currently, natural aggregates of good quality are hard to use because of continuous decrease of internal aggregate resource and regulation of gathering. So, use of crushed sand was being increased. On the other hand, skyscraper projects with 100 stories are being planned within the country and high strength concrete must be used to construct a skyscraper with 100 stories. High strength concrete is necessary to use crushed sand too because we are still unable to secure natural aggregates of good quality. So, This study indicated basic data necessary for mix design of high strength concrete through valuation of concrete property by quality variation of crushed sand.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.57-58
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• 2009

This paper reports experimental data on the structural performance of reinforced concrete beams with recycled aggregates. Reinforced concrete beams with recycled coarse aggregate and recycled sands were tested to evaluate their failure modes, flexural behavior and compared with a standard.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.821-824
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• 2008

This paper presents a systematic approach for estimating material performance of concrete mixture design based on satisfaction curves developed from statistical evaluation of existing or newly obtained material property related data. In performance based material design (PBMD) method, concrete material used for construction of a structure is designed considering a structure's specified performance requirements based on its usage and characteristics such as environmental conditions, structure types, expected design life, etc.Satisfaction curves express the probabilities that one component of substrates (i.e., aggregate size, cement content, etc) of concrete mixture will sustain different criterion value for a given concrete mixture design. This study presents a statistical analysis method for setting up concrete material parameter versus concrete criterion relationships in the form of satisfaction curves and for estimating confidence bounds on these satisfaction curves. This paper also presents an analysis method to combine multiple satisfaction curves to form one unique satisfaction curve that can relate the performance of concrete to a single evaluating value. Based on several evaluated mixture design examples for various material properties, the validity of the proposed method is discussed in detail.

• International journal of advanced smart convergence
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• v.6 no.1
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• pp.1-8
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• 2017

Diverse types of malicious code such as evasive Server-side Polymorphic are developed and distributed in third party open markets. The suspicious new type of polymorphic malware has the ability to actively change and morph its internal data dynamically. As a result, it is very hard to detect this type of suspicious transaction as an evidence of Server-side polymorphic mobile malware because its C&C server was shut downed or an IP address of remote controlling C&C server was changed irregularly. Therefore, we implemented Simulated C&C Server to aggregate activated events perfectly from various Server-side polymorphic mobile malware. Using proposed Simulated C&C Server, we can proof completely and classify veiled server-side polymorphic malicious code more clearly.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.11a
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• pp.19-22
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• 2003

This study is carried out (1) checking the development of compressive strength of high flowing concrete at early age, changing water-binder ratio, curing temperature, and type of aggregate, and (2) suggesting basic date that helping cost and schedule plan in future construction. As the result of this study, we find that high curing temperature is effective for the development of compressive strength of concrete at early age on the condition of each water-binder ratio, and after making the compressive prediction formula related to the curing temperature by maturity, the result of the formular is similar to the temperature-compressive strength-age measured data