• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.427-436
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• 2015

This study aims to select an optimal site for the development of small-scaled artificial ground water recharge system with the purpose of 50ton/day pumping in dry season. First of all, the topography shape satisfying the numerous factors of a hydraulic model experiment is defined and an appropriate pumping efficiency is calculated through the model experiment of injection and pumping scenario. In next step, GIS(Geographic Information System) database are constructed by processing several geospatial data to explore the optimal site. In detail, watershed images are generated from DEM(Digital Elevation Model) with 5m cell size, which is set for the minimum area of the optimal site selection. Slope maps are made from DEM to determine the optimal hydraulic gradient to procure the proper aquifer undercurrent period. Finally, the suitable site for artificial recharge system is selected using an integration of overall data, such as an alluvial map, DEM, orthoimages, slope map, and watershed images.

• Korean Journal of Agricultural Science
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• v.25 no.2
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• pp.310-320
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• 1998

This study is aimed at identifying the socio-economic effects of storage of ginger in artificial caves. The gingers stored in artificial caves in Seochun, 12 sampled areas, were surveyed to get information on the socio-economic effects. The surveyed data were processed by TSP, Qbasic and B/C Ratio computer programs and analyzed the decision making criteria such as B/C ratio, NPV and IRR. The socio-economic effects of the storages of the gingers are as follows. 1. The storage benefits per ton was showed as 184,050won. 2. Considering 10% of the opportunity cost of capital, the uper limits of investments for the cave storages was analyzed as 6,784 thousand won for ginger. 3. The investment of the natural cave storages was revealed economically feasible considering the decision making criteria as B/C ratio = 1.33, NPV = 35.059 thousand won and IRR = more than 100%. The other socio-economic effects of the ginger storages was expected as ; 1. The cave storages will contribute to increase consumer's and producer's welfare through the control of supply and demand and price stability. 2. Long-term storage of ginger without damaging quality and grades will be made on account of the storage conditions as relatively low temperature, high humidity and indifferent affects from the outside climate. 3. Utilization of the underground space, the caves, for storage will maximize the land use and the sustainable environment considering the mountainous area, two third of the total national land area. 4. Construction costs of the underground storage facilities as caves are cheaper than the ground storage facilities by 15 to 20% in general. In conclusion, the underground space like natural and artificial caves are considered the most suitable for storage of ginger on account of the storage conditions as temperature, humidity and blocking the sun light. Accordingly a study on convenient utilization of new development of artificial caves should be made considering transportation and input-output of the farms. Financial support of the government should be institutionally rearranged for the successful implementation of storing farm products like ginger in natural and man-made caves.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.261-274
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• 2019

This paper aims to develop an appropriate methodology for establishing an investment strategy for 'demonstration of artificial rainfall technology using UAV' and that include establishment of a technology classification, set of indicators for technology evaluation, suggestion of final key technology as a whole study area. It is designed to complement the latest research trend analysis results and expert committee opinions using quantitative analysis. The key indicators for technology evaluation consisted of three major items (activity, technology, marketability) and 10 detailed indicators. The AHP questionnaire was conducted to analyze the importance of indicators. As a result, it was analyzed that the attribute of the technology itself is most important, and the order of closeness to the implementation of the core function (centrality), feasibility (feasibility). Among the 16 technology groups, top investment priority groups were analyzed as ground seeding, artificial rainfall verification, spreading and diffusion of seeding material, artificial rainfall numerical modeling, and UAV sensor technology.

• Imaging Science in Dentistry
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• v.53 no.3
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• pp.199-207
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• 2023

Purpose: The objective of this study was to evaluate the accuracy and effectiveness of an artificial intelligence (AI) program in identifying dental conditions using panoramic radiographs(PRs), as well as to assess the appropriateness of its treatment recommendations. Materials and Methods: PRs from 100 patients(representing 4497 teeth) with known clinical examination findings were randomly selected from a university database. Three dentomaxillofacial radiologists and the Diagnocat AI software evaluated these PRs. The evaluations were focused on various dental conditions and treatments, including canal filling, caries, cast post and core, dental calculus, fillings, furcation lesions, implants, lack of interproximal tooth contact, open margins, overhangs, periapical lesions, periodontal bone loss, short fillings, voids in root fillings, overfillings, pontics, root fragments, impacted teeth, artificial crowns, missing teeth, and healthy teeth. Results: The AI demonstrated almost perfect agreement (exceeding 0.81) in most of the assessments when compared to the ground truth. The sensitivity was very high (above 0.8) for the evaluation of healthy teeth, artificial crowns, dental calculus, missing teeth, fillings, lack of interproximal contact, periodontal bone loss, and implants. However, the sensitivity was low for the assessment of caries, periapical lesions, pontic voids in the root canal, and overhangs. Conclusion: Despite the limitations of this study, the synthesized data suggest that AI-based decision support systems can serve as a valuable tool in detecting dental conditions, when used with PR for clinical dental applications.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.697-700
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• 2003

The SASW method is a promising and effective way of profiling ground stiffness nondestructively. This method has been successfully applied to many geotechnical sites, but significant lateral variability, embedded obstacles, and pavement lead to the low reliability. To improve these problems, the horizontal wave component has been introduced to improve the reliability of the stiffness profile determined by the SASW method. To understand dispersion character of the horizontal component wave propagation in artificial profiles, FEM analysis had been performed. Used models are homogeneous half-space and two layered half- spaced layers.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.1
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• pp.163-167
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• 2010

Square reefs of 2 groups installed at 1984 on mud and sandy-mud seafloor were compared with settlment conditions of those at Goheong coastal in middle-south sea of Korea at 2007. Reefs installed on mud and sandy-mud seafloor were settled to 1.9m and 2.4m, respectively. It suggest that a function of square reefs group installed on soft seafloor decrease over 50% after 20 years.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.05a
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• pp.222-227
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• 2005

This paper presents study on the electric potential distribution when have a short in skeet lamp. In order to measure electric potential testing ground is built in. A experiment is conducted to simulate dry and submerged situation of street lamp. The street lamp is leaked by artificial means. And electric potential is measured in grounded street lamp and street lamp alone. The results show that touch voltage of grounded street lamp is possible to more high than street lamp alone. And the electric shock hazard is high because high electric potential is distributed near submerged street lamp. Also if street lamp is submerged ground is not useful to decrease electric shock hazard.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.280-281
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• 2006

This paper was analyzed fundamental about electrical characteristic of concrete to practical use base of building as Substitution Ground Electrode and Artificial Ground Electrode. 1) Gravel or Sand has a function that makes increase Resistivity of Concrete and Cement has a function that makes decrease Resistivity of Concrete. 2) Moisture Increase Work is so hard because of dry of Block but the Resistivity was decreased when the moisture of Concrete Block was gradually increased. 3) According to the measurement result of moltar and concrete block, ratio relation of Resistance and Resistivity of each block was thirty-fold difference.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05b
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• pp.217-220
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• 2006

This paper describes a study undertaken to determine the effect of ground calcium carbonate(GCC) cement mortar with respect to sulfate attack. It were investigated visual appearance and expansion of cement mortars with GCC immersed in artificial solution of 5% sodium sulfate during 510days. According to increasing replacement of GCC, the expansion ratio was comparatively superior to GCC0 mortar specimen. The test results indicated that cement mortars with GCC was benefit the resistance of sulfate attack due to micro filler effect.