• Journal of Digital Convergence
• /
• v.10 no.11
• /
• pp.565-577
• /
• 2012

Various factors affecting teachers' self-confidence exist in math class using technology such as graphic calculators. For example, internal factors such as teachers' attitude and external factors such as school administrators or colleague's support can be considered. Pedagogical Technology Knowledge(PTK) is the very important factor which determines teacher's self-confidence in educational technology, and the development of PTK is composed of teacher's perception on the technology and its application and instrumentation. This study investigated 19 pre-service and current middle and high school teachers in the respect of their change of self-confidence, attitude, expertise on pedagogical technology, and quality of math class. These are anlayzed with the concept of instrumentation and instrumentalization through various experiences like graphic calculator, GPS and AutoGraph. The result indicated that constraints or obstacles did not affect much if teachers' attitude and self-confidence were strong. Particularly teachers' firm will to learn about technology and their confidence on its value are the critical factors in using technology for mathematics class.

• The Journal of Society for e-Business Studies
• /
• v.14 no.4
• /
• pp.1-17
• /
• 2009

E-Catalogs which describe products or services are one of the most important data for the electronic commerce. E-Catalogs are created, updated, and removed in order to keep up-to-date information in e-Catalog database. However, when the number of catalogs increases, information integrity is violated by the several reasons like catalog duplication and abnormal classification. Catalog search, duplication checking, and automatic classification are important functions to utilize e-Catalogs and keep the integrity of e-Catalog database. To implement these functions, probabilistic models that use statistics of index words extracted from e-Catalogs had been suggested and the feasibility of the methods had been shown in several papers. However, even though these functions are used together in the e-Catalog management system, there has not been enough consideration about how to share common data used for each function and how to effectively manage statistics of index words. In this paper, we suggest a method to implement these three functions by using simple SQL supported by relational database management system. In addition, we use materialized views to reduce the load for implementing an application that manages statistics of index words. This brings the efficiency of managing statistics of index words by putting database management systems optimize statistics updating. We showed that our method is feasible to implement three functions and effective to manage statistics of index words with empirical evaluation.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.1
• /
• pp.1-16
• /
• 2020

The APEX model has been developed for assessing agricultural management efforts and their effects on soil and water at the field scale as well as more complex multi-subarea landscapes, whole farms, and watersheds. Recently, a key component of APEX application, named APEX-Paddy, has been modified for simulating water quality by considering paddy rice management practices. In this study, the performance of the APEX-Paddy model was evaluated using field data at Iksan experimental paddy sites in Korea. The discharge and pollutant load data during 2013 and 2014 were used to both manually and automatically calibrate the model. The APEX auto-calibration tool (APEX-CUTE 4.1) was used for model calibration and sensitivity analysis. Results indicate that APEX-Paddy reasonably performs in predicting runoff discharge rate and nitrogen yield. However, sediment and phosphorus yield is not correctly predicted due to the limitation of model schemes. With APEX-Paddy, the performance in reproducing the discharge and nitrogen yield is found to be a satisfactory level after manual calibration. The manually calibrated model performed better than the automatically calibrated model in nearly all comparisons. For runoff, manual calibration reduced PBIAS while R² and NSE values of the automatically calibrated model were the same as the manual calibration. For T-N, NSE and PBIAS were reduced when using manual calibration, whereas R² value was the same as manual calibration. The limitation of the APEX-Paddy model for predicting sediment, as well as the phosphorous yield, was discussed in this study.

• Journal of Navigation and Port Research
• /
• v.32 no.6
• /
• pp.499-503
• /
• 2008

As the conference result of MEPC in IMO, development of ballast water management system corresponding to newly established ballast water management standard (D2 regulation) of shipping is being made an active progress over the whole world. The ballast water management system should treat particular material of more than $10{\mu}m$ in high capacity of more than 500t per hour in the event of filtration process. Also, it is very difficult to develop a practical management system since a limited element which a narrow space of the ship should be designed in the minimal volume is assumed. Therefore, the study promoted a study on the next generation auto back wash media filter to overcome such a limited element. Also, the study performed pressure and flux measurement test followed by thickness of each filter medium for filtration by each size to grasp a relation between absorption and pressure at the time of vacuum filtration and mechanical analysis and turbidity change observation of filtered water after vacuum filtration.

• The Journal of Engineering Geology
• /
• v.32 no.2
• /
• pp.221-239
• /
• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.307-325
• /
• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• 월간산업보건
• /
• s.8
• /
• pp.4-30
• /
• 1988

Examination of working environments was conducted to get more detailed data about harmful working environments and to make a contribution to more effective management. Study was carried out on 722 factories located in Taegu city and eight counties in Kyungpook Province, Korea, for a period of one year, from February 1 to December 30, 1986. The total number and proportion of workers exposed to harmful material was 37,697, 45.2% among 83,368 workers. The results according to exposed material were as follows: 1. In the case of noise, proportion of exceeding the 8-hour TLV was 59%, Included were nail-cutting in assembly metal manufacturing industry and weaving process in textile. 2. Dust in mill process of coal manufacturing industries exceeded the TLV of second class of dust at all parts and exceeded the TLV at 6% as a whole.: 3. The fields of industry lower than 70 lux of illumination were storage equipment of food, auto-winder of textile, painting of wood wares and coal mixing, and 44% of all cases was lower than standard. 4. As a result of temperature index investigation(WBGT), about 12% of all sujects exceeded limit value. Included parts were rolling machine and reducing room. 5. In the case of organic solvents, TLV was exceeded at about 8%, The parts exceeded TLV according to materials belonged to this category were as follows. 1) Toluene: adhesive work in assembly metal manufacturing 2) Xylene: printing and paint mixing in chemical manufacturing 3) Methyl ethytl ketone: paint mixing in all parts examined and coating machine partially in chemical manufacturing 4) Methyl isobutyl ketone: printing in chemical manufacturing 5) Acetone: vapor polishing in assembly metal manufacturing 6. Among specified chemical materials, the concentration of HC1 in the air in metal assembly manufacturing factory exceeded TLV. in one of three assembly metal manufacturing examined. Others, such as benzene, acetic acid, formic acid, sodium hydroxide, formalin, ammonia, copper, chromate etc. were lower than TLV in its indoor atmospheric concentration. As a whole, the proportion of exceeding TLV was about 0.8% 7. The concentrations of inorganic lead were lower than TLV in all parts examined. The results of this investigation show the fact that current management of working environments is not satisfactory, and so more active management is needed.

• Korean Journal of Construction Engineering and Management
• /
• v.14 no.5
• /
• pp.35-43
• /
• 2013

Nowadays the widely used media in architecture include visualizations, animations and three-dimensional models. 3D digital methods using active CAM(Computer Aided Manufacturing) and CNC(Computerized Numerical Control) imaging have been developed for accurate shape and 3D measurements in freeform buildings. In contrast to a conventional building using auto CAD system and others, the proposed digital optimization method is based on a combination of 3D numerical data and parametric 3D model for design and construction. The objective of this paper is therefore to present digital optimization process for constructability of freeform building. The method can be useful in the effective implementation of an error-proofing process of freeform building during design and construction phase. 3D digital coordinate data can be used effectively to identify correct size of structural and finish members and installation location of each members in construction field. In addition, architects, engineers and contractors can evaluate design, materials, constructability and identify error-proofing opportunities. Other project participants can also include representatives from all levels of management, departments as well as workers and key subcontractors' personnel, if necessary. The 3D digital optimization process is therefore appropriate to serious variations in freeform shape. For future study, the developed digital optimization method is necessary to be carried out to verify the robustness and accuracy for constructability in construction field.

• Journal of the Korea Society for Simulation
• /
• v.31 no.1
• /
• pp.1-9
• /
• 2022

As the automobile market has grown steadily in recent years, consumer expectations have also risen. Therefore, it is necessary for automobile sales offices to create innovative customer value that is different from the past. Auto sales offices are making efforts to select salespeople who fit their management strategies, but they are having difficulties in evaluating their actual internal capabilities. Therefore, in this paper, based on the study of Spencer & Spencer (2008), we reconstruct the core competencies required for salesperson selection, and analyze the core competencies required for today's automobile salespersons by deriving the hierarchical importance between those competencies using AHP analysis. As a result, it was possible to derive the importance of core competencies different from previous studies. This is believed to be mainly due to the modern social market, the characteristics of existing car salespeople, and the tendency of recent customers. This study showed that it is possible to set selection criteria according to the ease and importance of calculating the required competency through AHP analysis. In addition, if the existing research is based on job specifications, this study is different in that it analyzed the actual group of experts.

• Journal of the Korean Society for Railway
• /
• v.17 no.3
• /
• pp.216-222
• /
• 2014

In general, the rail transportation recognized as a better transportation mode than road transportation in terms of the environment. However, due to a lack of quantitative analysis based on Korean data, foreign cases for environmental advantages of the railway have often been cited in Korea. To address this issue, we estimated the energy consumption of passenger and freight transportation using certified activity data from Korea Railroad Statistics and the Electrical Work Report for railway and the Energy Consumption Survey for road. We estimated the Green House Gas emission of passenger and freight transportation on a Tier 1 level by applying the IPCC 2006 Guideline. Finally, we calculated the energy consumption unit and GHG emission unit to determine the environmental impact of rail and road transportation. We also compared the analyzed results of high-speed rail and auto as typical means of rail and road transportation.