• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.1C
• /
• pp.1-8
• /
• 2008

Recently, there have been many construction projects on soft ground with growth of industry and economy. Therefore foundation piles of abutments and(or) buildings had been suffering from a lot of stability problems of inordinary displacement due to lateral flow of soft ground. Although many researches about lateral flow have been carried out, it is still difficult to assess the mechanism of lateral flow in soft ground quantitatively. And reasonable design method for judgement of lateral flow occurrence in soft ground is not established yet. In this study, six PNN (Probabilistic Neural Network) models were developed according to input variables and database compiled from Korea and Japan for the judgment of lateral flow occurrence. PNN models were compared with present empirical methods. It was found that the developed PNN models can give more precise and reliable judgment of lateral flow occurrence than empirical methods.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.1D
• /
• pp.157-167
• /
• 2006

During the first and second NGIS projects by the Korean government, The first one (1995~2000) was limited on constructing geographic information and the second (2001~2005) was focused on circulation and practical use of geoinformation from the result of the first project. In the latter half of 2nd NGIS project, However, the geographic information from the NGIS projects have not been renewed even though there were significant geographical changes. The accurate renewal of geoinformation is a matter of great importance to the next generation industry (e.g. LBS, Ubiquitous, Telematics). In this respect, it is time to update the geographic information in the latter half of the second NGIS project. Therefore, It is not only important to build an accurate geoinformation but also rapid and correct renewal of the geoinformation. NGII (National Geographic Information Institute) has been studying for improvement of digital map that was constructed by the result of the 1st NGIS project. Through the construction of clean digital map, NGII constructed Framework Data to three kinds of formats (NGI, NDA, NRL). Framework Data was contained to other database, and provided the reference system of location or contents for combining geoinformation. Framework Data is consist of Data Set, Data Model and UFID (Unique Feature Identifier). It will be achieved as national infrastructure data. This paper attempts to explore a method of the update to practical framework data with realtime geoinformation on feature's creation, modification and destruction managed by 'Feature management agency' using UFID's process. Furthermore, it suggests a method which can provide important data in order to plan the Framework update with the land change ratio.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.6B
• /
• pp.551-560
• /
• 2009

This paper describes a newly developed pollutant transport model named ARPTM which was designed to simulate the transport and characteristics of pollutant materials after an accidental spill in upstream of river system up to a given position in the downstream. In particular, the ARPTM incorporated ADCP data to compute longitudinal dispersion coefficient and advection velocity which are necessary to apply one-dimensional advection-dispersion equation. ARPTM was built on top of the geographic information system platforms to take advantage of the technology's capabilities to track geo-referenced processes and visualize the simulated results in conjunction with associated geographic layers such as digital maps. The ARPTM computes travel distance, time, and concentration of the pollutant cloud in the given flow path from the river network, after quickly finding path between the spill of the pollutant material and any concerned points in the downstream. ARPTM is closely connected with a recently developed GIS-based Arc River database that stores inputs and outputs of ARPTM. ARPTM thereby assembles measurements, modeling, and cyberinfrastructure components to create a useful cyber-tool for determining and visualizing the dynamics of the clouds of pollutants while dispersing in space and time. ARPTM is expected to be potentially used for building warning system for the transport of pollutant materials in a large basin.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.5D
• /
• pp.797-804
• /
• 2006

A development of regression model for asphalt concrete pavements using Falling Weight Deflectometer deflections is presented in this paper. A backcalculation program based on layered elastic theory was used to generate the synthetic modulus database, which was used to generate 95% confidence intervals of modulus in each layer. Using deflection basins of FWD data used in developing this procedure were collected from Pavement Management System in flexible pavements. Assumptions of back-calculation are that one is 3 layered flexible pavement structure and another is depth to bedrock is finite. It is found that difference of between 95% confidence intervals and modulus ranges of other papers does not exist. So, the data of 95% confidence intervals in each layer was used to develop multiple regression models. Multiple regression equations of each layer were established by SPSS, package of Statics analysis. These models were proved by regression diagnostics, which include case analysis, multi-collinearity analysis, influence diagnostics and analysis of variance. And these models have higher degree of coefficient of determination than 0.75. So this models were applied to predict modulus of domestic asphalt concrete pavement at FWD field test.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.1D
• /
• pp.115-123
• /
• 2006

Recently, construction claims have been increased for protecting the rights of construction participants and effectively adjusting the changes under the contract. Thus, the importance of claim management has been emphasized in the construction industry. In domestic construction industry, some claim issues involved in construction activities are often being developed into disputes and even litigations because of the absence of methods or systems for the dispute resolution, and the lack of judicial precedents which can be provided as the references for resolving a particular dispute. In general, the judicial precedents related to the disputes and litigations occurred among construction participants would be extremely valuable in evaluating and analyzing current claims issues. However, such useful information has not been effectively accumulated and utilized in resolving the similar or sometimes identical types of disputes, thus requiring a large amount of additional costs, time and efforts. The primary objective of this study is to propose a web-based decision support system for construction claim management, which enables contractual participants to easily access and use the information of the judicial precedents related to the current construction claims. The decision support system is composed of 'prevention' and 'settlement' modules for avoiding and systematically resolving the construction claims.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.6D
• /
• pp.951-960
• /
• 2006

Structural pavement analysis considering lateral loads of moving vehicle was carried out in order to simulate passing vehicle loads under various interface conditions. To verify of existing multi-layer elastic analysis of layer interface effect parameters, this study compared outputs by using ABAQUS, a three dimensional finite element program and KENLAYER, multi-layer elastic analysis as vertical load was applied to the surface of asphalt pavements. Pavement performance depending on interface conditions was quantitatively evaluated and fundamental study of layer interface effect parameters was performed in this study. As results of the study, if only vertical loads of moving vehicle is applied, subdivision of either fully bonded or fully unbonded is enough to indicate interface effect parameters. On the other hand, when lateral loads are applied with vertical loads, pavement behavior and performance are greatly changed with respect to layer interface conditions. The thinner thickness of the asphalt layer is and the smaller elastic moduli of the asphalt layer is, the more pavement behavior is influenced by interface conditions. In addition, regression analysis equation analytically computing tensile strain which was considered thicknesses and elastic moduli of the asphalt layer and layer interface effect parameters at the bottom of the asphalt layer was presented using database from numerical analyses on national pavement model sections.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.6
• /
• pp.536-543
• /
• 2023

Speaker diarization, which labels for "who spoken when?" in speech with multiple speakers, has been studied on a deep neural network-based end-to-end method for labeling on speech overlap and optimization of speaker diarization models. Most deep neural network-based end-to-end speaker diarization systems perform multi-label classification problem that predicts the labels of all speakers spoken in each frame of speech. However, the performance of the multi-label-based model varies greatly depending on what the threshold is set to. In this paper, it is studied a speaker diarization system using single-label classification so that speaker diarization can be performed without thresholds. The proposed model estimate labels from the output of the model by converting speaker labels into a single label. To consider speaker label permutations in the training, the proposed model is used a combination of Permutation Invariant Training (PIT) loss and cross-entropy loss. In addition, how to add the residual connection structures to model is studied for effective learning of speaker diarization models with deep structures. The experiment used the Librispech database to generate and use simulated noise data for two speakers. When compared with the proposed method and baseline model using the Diarization Error Rate (DER) performance the proposed method can be labeling without threshold, and it has improved performance by about 20.7 %.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.6
• /
• pp.1001-1006
• /
• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• Journal of fish pathology
• /
• v.36 no.2
• /
• pp.251-261
• /
• 2023

Photobacterium sp. YW2207 was isolated from rainbow trout raised in a fish farm located in Yeongwol-gun, Gangwon Province, South Korea. Based on 16S rRNA sequence analysis and phylogenetic analysis, it was confirmed that Photobacterium sp. YW2207 showed 100% similarity with Photobacterium piscicola and Photobacterium phosphoreum, and 94.6% similarity with P. damselae subsp. damselae. Biochemical analysis revealed that Photobacterium sp. YW2207 is a Gram-negative, motile bacterium with a cell size of 1.5~3×3~5 ㎛. The bacteria were cultured on nutrient agar, brain heart infusion agar, Muller-Hinton agar, tryptic soy agar, and thiosulfate citrate bile sucrose agar with NaCl concentrations ranging from 0 to 2.5%. The API50CHE and API20E tests indicated lower utilization capabilities compared to the P. damselae strains provided in the API database. Furthermore, unlike most Photobacterium species, Photobacterium sp. YW2207 presented negative for catalase test. Results from the flow cytometric measurement indicated that Photobacterium sp. YW2207 exhibited a more diverse distribution of cell sizes and had larger cell sizes compared with P. damselae subsp. damselae. Minimum inhibitory concentration tests showed that Photobacterium sp. YW2207 had low susceptibility to β-Lactam and aminoglycoside antibiotics, while having high susceptibility to tetracycline, doxycycline, and quinolone antibiotics. Pathogenicity on rainbow trout revealed that an immersion of 1×10⁵ CFU/ml did not cause mortality or clinical symptoms.

• Journal of the Korea Institute of Building Construction
• /
• v.23 no.6
• /
• pp.785-796
• /
• 2023

The adoption of Environmental, Social, and Governance(ESG) practices in domestic construction firms is predominantly driven by major corporations. These companies not only publish reports on their ESG management but also engage in a meticulous process of identifying key issues and setting priorities. This process entails an in-depth evaluation of the severity of various issues and the gathering of insights from experts in the field. Interestingly, a comparative analysis of ESG assessments for construction companies, both domestically and internationally, reveals significant discrepancies in outcomes. These differences stem from the varied evaluation methodologies and criteria employed by different assessing bodies. Addressing this gap, our study proposes a suite of strategies aimed at bolstering ESG management within the construction sector. We advocate for enhanced policy support and financial backing, especially targeting small and medium-sized enterprises(SMEs) to facilitate their engagement in ESG practices. A critical step forward involves the standardization and transparent disclosure of ESG evaluation criteria, tailored to reflect the unique aspects of the construction industry. Moreover, the standardization and publication of ESG assessments for subcontractors are essential, equipping them with the necessary tools for effective ESG management and evaluation. Given the global nature of construction projects, particularly those commissioned by the European Union in regions like Africa and East Asia, adherence to ESG standards is imperative. Our long-term vision includes the development of a comprehensive database detailing ESG regulations and their impacts, segmented by region and country. This repository will serve as a valuable resource for companies venturing into international construction projects.