• Anatomy and Cell Biology
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• v.56 no.1
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• pp.86-93
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• 2023

Age at death estimation has always been a crucial yet challenging part of identification process in forensic field. The use of human skeletons have long been explored using the principle of macro and micro-architecture change in correlation with increasing age. The clavicle is recommended as the best candidate for accurate age estimation because of its accessibility, time to maturation and minimal effect from weight. Our study applies pre-trained convolutional neural network in order to achieve the most accurate and cost effective age estimation model using clavicular bone. The total of 988 clavicles of Thai population with known age and sex were radiographed using Kodak 9000 Extra-oral Imaging System. The radiographs then went through preprocessing protocol which include region of interest selection and quality assessment. Additional samples were generated using generative adversarial network. The total clavicular images used in this study were 3,999 which were then separated into training and test set, and the test set were subsequently categorized into 7 age groups. GoogLeNet was modified at two layers and fine tuned the parameters. The highest validation accuracy was 89.02% but the test set achieved only 30% accuracy. Our results show that the use of medial clavicular radiographs has a potential in the field of age at death estimation, thus, further study is recommended.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.70-79
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• 2015

With the rise of the interest in a renewable system, the importance of the Life Cycle Cost Analysis(LCCA), an economic evaluation tool, has been increasing. However, there is an inevitable gap between a real cost and an estimation from LCCA because of the uncertainty of the external environment in real world. As the input variables in an analysis, such as a real discount rate and an energy cost, ares subject to change as time goes by, strategic decision on the current operating system is made depending on the real cost. Current economic evaluation approaches have treated only the fluctuation of input variables without consideration of the flexibility in operation, which has consequently led to the impairment on the reliability of LCCA. Therefore, new approach needs to be proposed to consider both the uncertainty of input variables and operational flexibility. To address this issue, the application of the Real Option to LCCA is presented in this study. Through a case analysis of LCCA of a solar heating system, the limits and current status of LCCA are identified. As a result, quantitative presentation of strategic decisions has been added in the new approach to implement the traditional approach.

• Journal of the Korea Society of Computer and Information
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• v.9 no.3
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• pp.27-34
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• 2004

As software developing paradigm has been changing to complicate Web environment, study of complexity becomes vigorous. Yet still it seems that general agreement has not to be reached to architecture or complexity measure of Web application. And so traditional complexity metrics - program size(LOC) and Cyclomatic Complexity can be derived from the source code after implementation. it is not helpful to the early phase of software development life cycle - analysis and design phase. In this study 6 Web projects has been used for deriving applications with possible errors suited by Complexity Indicator. Using 61 programs derived, linear correlation between complexity, number of classes and number of methods has been proposed. As Web application complexity could be estimated before implementation, effort and cost management will be processed more effectively.

• Journal of the Korean housing association
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• v.23 no.6
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• pp.31-38
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• 2012

In this paper, we draws tendency of the electricity consumption in residential buildings according to inhabitants Composition types and the level of incomes. it is necessary to reduce energy cost and keep energy security through the electricity demand forecasting and management technology. Progressive social change such as increases of single household, the aging of society, increases in the income level will replace the existing residential electricity demand pattern. However, Only with conventional methods that using only the energy consumption per-unit area are based on Energy final consumption data can not respond to those social and environmental change. To develop electricity demand estimation model that can cope flexibly to changes in the social and environmental, In this paper researches propensity of electricity consumption according to the type of residents configuration, the level of income. First, we typed form of inhabitants in residential that existed in Korea. after that we calculated hourly electricity consumption for each type through National Time-Use Survey performed at the National Statistical Office with considering overlapping behavior. Household appliances and retention standards according to income level is also considered.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.90-96
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• 2008

This paper presents an algorithm of a single chip acoustic speech enhancement for telematics device. The algorithm consists of two stages, i.e. noise reduction and echo cancellation. An adaptive filter based on cross spectral estimation is used to cancel echo. The external background noise is eliminated and the clear speech is estimated by using MMSE log-spectral magnitude estimation. To be suitable for use in consumer electronics, we also design a low cost, high speed and flexible hardware architecture. The performance of the proposed speech enhancement algorithms were measured both by the signal-to-noise ratio(SNR) and recognition accuracy of an automatic speech recognition(ASR) and yields better results compared with the conventional methods.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• Korean Journal of Computational Design and Engineering
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• v.20 no.2
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• pp.182-192
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• 2015

In recent years, numerous studies have attempted to extract quantity data by using Building Information Modeling (BIM). In terms of open-BIM based quantity take-off at the early design stage, only few studies were conducted in the field of cost engineering. A lack of compatibility of open BIM for information exchange is postulated as the cause. The Industry Foundation Classes (IFC) extension model has been developed to accommodate the interoperability with quantity take-off software. Improvement of open BIM for quantity take-off needs exchange requirements and model guidelines. For this purpose, the quantity data of IFC models were analyzed using BIM analysis tools. This paper also provides a proposal of requirements on open BIM based quantity take-off at the early design stage. Further this study have been develop the interface system for open BIM based quantity take-off requirements with the results on this study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.509-517
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• 2001

Full-search algorithm requires large amount of computation which causes time delay or very complex hardware architecture for real time implementation. In this paper, we propose a fast motion estimator based on bit-plane matching, which reduce the computational complexity and the hardware cost. In the proposed motion estimator, the conventional motion estimation algorithms are applied to the binary images directly extracted from the video sequence. Furthermore, in the proposed VLSI motion estimator, we employ a Pair of processing cores that calculate the motion vector continuously By controlling the data flow in a systolic fashion using the internal shift registers in the processing cores, we avoid using SRAM (local memory) so that we remove the time overhead for accessing the local memory and adopt lower-cost fabrication technology. We modeled and tested the proposed motion estimator in VHDL, and then synthesized the whole system which has been integrated in a 0.6-$\mu$m triple-metal CMOS chip of size 8.15 X 10.84$\textrm{mm}^2$.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.9-16
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• 2016

The project schedule risk in the engineering and facility construction industry is increasingly considered as important management factor because the risks in terms of schedule or deadline may significantly affect the project cost. Especially, the project-based operating companies attempt to find the best estimate of the project completion time for use at their proposals, and therefore, usually have much interest in accurate estimation of the duration of the projects. In general, the management of projects schedule risk is achieved by modeling project schedule with PERT/CPM techniques, and then performing risk assessment with simulation such as Monte-Carlo simulation method. However, since these approaches require the accumulated executional data, which are not usually available in project-based operating company, and, further, they cannot reflect various schedule constraints, which usually are met during the project execution, the project managers have difficulty in preparing for the project risks in advance of their occurrence in the project execution. As these constraints may affect time and cost which role as the crucial evaluation factors to the quality of the project result, they must be identified and described in advance of their occurrence in the project management. This paper proposes a Bayesian Net based methodology for estimating project schedule risk by identifying and enforcing the project risks and its response plan which may occur in storage tank engineering and construction project environment. First, we translated the schedule network with the project risks and its response plan into Bayesian Net. Second, we analyzed the integrated Bayesian Net and suggested an estimate of project schedule risk with simulation approach. Finally, we applied our approach to a storage tank construction project to validate its feasibility.

• Journal of The Korean Digital Architecture Interior Association
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• v.10 no.3
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• pp.19-28
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• 2010

The construction projects are recently having changes in their magnitude and complexity. Therefore, the amount of information created and managed by participants over project phases is enormous and this may cause difficulties in consistent and integrated data management. Because of the change in construction projects, there is a need to apply more logical and systematic ways to deal integrated data management. For the solution to this, BIM(Building Information Modeling), a new paradigm for integrated management of the information over project life-cycle, has been seriously considered. Also, the Korean Public Procurement Service announced that project over 50 billion Korean Won should introduce BIM into procurement starting from 2012. However, the studies and development have lack on studies of applying BIM and managing the data made using BIM in pre-design and maintenance stage. In pre-design stage, the concept of schematic design model is made to support for making major decisions concerning the size, shape and cost of the project. To decide the cost for the building in this stage by making use of BIM, estimating the amount of building materials used for constructing should be preceded. In this study, the pre-design BIM is explained to gain a better understanding of its process, since this paper focused on space programming stage. Finally, the paper suggests the concept process of estimating the amount of materials in building interior finishing from selecting the type for the elements of each space made to support the client for making decisions in space programming stage based on pre-design BIM.