• Korean Journal of Construction Engineering and Management
• /
• v.6 no.6 s.28
• /
• pp.115-123
• /
• 2005

Design of steel $bridge^{\circ}AEs$ temporary works has conducted relying on the experiences of engineers based on the previous similar projects. Consequently, there have been arguments against over-design of temporary bents to be required at the actual construction sites, and unnecessary design changes have been issued at the construction stage. In this study, we have developed an optimum design support system for temporary works of the steel bridge construction through establishing the database for the materials to be needed for implementation of temporary works. We've also improved the accuracy and efficiency of the works through the design optimization for temporary works, and contributed to reduce design changes as well as to utilize the design informations at the construction stage.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.42-49
• /
• 2022

In recent years, Owner, Architects, and Contractor are increasingly collaborating with each other from pre construction phase in construction projects, which is called Early Contractor Involvement (ECI). In Japan, the ECI method has been introduced in several public building projects since 2015. The purpose of this study is mainly to clarify the characteristics of the ECI method in Japan and to compare the contract clauses of the ECI method in the UK and the USA. The results of the survey are as follows. (1) the ECI method was supposed to make it possible to achieve appropriate quality, cost, and construction period by reflecting Contractor's technology and know-how in the design documents and specifications. (2) According to the database, there were 27 cases of the ECI method in Japan from 2015 to 2021, of which 13 cases for which bidding information could be obtained had a variety of technical proposals, mainly VE proposals, depending on the project characteristics. (3), Japan's ECI method has very much in common with SBC + PCSA in the UK. On the other hand, ECI Method in Japan differs from in the UK in that Owner, Architect, and Contractor enter into a partnership agreement, which is similar to ConsensusDocs CD541 in the USA. (4) The ECI method in Japan has the following problems: Owner depends on Contractor for cost control, the division of roles among project members is complicated, and more work from Owner than the DBB method are required.

• Korean Journal of Construction Engineering and Management
• /
• v.17 no.2
• /
• pp.31-38
• /
• 2016

In a construction project, the portion for maintenance costs for a building is considerable compared to the initial construction cost. As such, Life Cycle Cost (LCC) analysis is being increasingly utilized to assess the design value of engineering work in Korea. Additionally, the Public Procurement Service in Korea announced that it will be mandatory for all domestic construction projects to adopt BIM. Furthermore, the paradigm for architectural design has shifted from 2D to 3D, and to BIM, which includes a data management system. Within this background, however, there is currently no adequate BIM-based LCC analysis software and the requirements of cost estimation for repair and replacement cost for a building is not completely adequate in BIM tools such as Revit and Archicad. Therefore, this study suggests a process of cost estimation for repair and replacement (R&R) cost based on IFC data. First, we analyzed existing R&R criteria and defined BIM-based requirements when calculating R&R costs. These requirements were extracted from relevant IFC data. Subsequently, this was saved to a database and a BIM-based database was built for R&R cost estimation. Finally, this database was connected with external databases such as R&R Criteria DB and Cost Information DB to calculate R&R costs. This process is expected to improve upon the traditional process of cost estimation of R&R cost by applying a BIM model. The proposed process can contribute to a further standardizing of BIM-based LCC analysis thru application to initial construction costs, energy costs, and other maintenance costs.

• Molecules and Cells
• /
• v.40 no.9
• /
• pp.655-666
• /
• 2017

We constructed a large $na{\ddot{i}}ve$ human Fab library ($3{\times}10^{10}$ colonies) from the lymphocytes of 809 human donors, assessed available diversities of the heavy-chain variable (VH) and ${\kappa}$ light-chain variable (VK) domain repertoires, and validated the library by selecting Fabs against 10 therapeutically relevant antigens by phage display. We obtained a database of unique 7,373 VH and 41,804 VK sequences by 454 pyrosequencing, and analyzed the repertoires. The distribution of VH and VK subfamilies and germline genes in our antibody repertoires slightly differed from those in earlier published natural antibody libraries. The frequency of somatic hypermutations (SHMs) in heavy-chain complementarity determining region (HCDR)1 and HCDR2 are higher compared with the natural IgM repertoire. Analysis of position-specific SHMs in CDRs indicates that asparagine, threonine, arginine, aspartate and phenylalanine are the most frequent non-germline residues on the antibody-antigen interface and are converted mostly from the germline residues, which are highly represented in germline SHM hotspots. The amino acid composition and length-dependent changes in amino acid frequencies of HCDR3 are similar to those in previous reports, except that frequencies of aspartate and phenylalanine are a little higher in our repertoire. Taken together, the results show that this antibody library shares common features of natural antibody repertoires and also has unique features. The antibody library will be useful in the generation of human antibodies against diverse antigens, and the information about the diversity of natural antibody repertoires will be valuable in the future design of synthetic human antibody libraries with high functional diversity.

• Smart Structures and Systems
• /
• v.8 no.1
• /
• pp.119-137
• /
• 2011

A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.

• Journal of KIISE:Databases
• /
• v.36 no.2
• /
• pp.73-83
• /
• 2009

In this paper we propose an object similarity matching method based on shape characteristics of an object in an image. The proposed method extracts edge points from edges of objects and generates a log polar histogram with respect to each edge point to represent the relative placement of extracted points. It performs the matching in such a way that it compares polar histograms of two edge points sequentially along with edges of objects, and uses a well-known k-NN(nearest neighbor) approach to retrieve similar objects from a database. To verify the proposed method, we've compared it to an existing Shape-Context method. Experimental results reveal that our method is more accurate in object matching than the existing method, showing that when k=5, the precision of our method is 0.75-0.90 while that of the existing one is 0.37, and when k=10, the precision of our method is 0.61-0.80 while that of the existing one is 0.31. In the experiment of rotational transformation, our method is also more robust compared to the existing one, showing that the precision of our method is 0.69 while that of the existing one is 0.30.

• Journal of Intelligence and Information Systems
• /
• v.18 no.3
• /
• pp.53-77
• /
• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.