• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.63-68
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• 2018

The establishment of Ground Control Points (GCPs) in UAV-Photogrammetry is a working process that requires the most time and expenditure. Recently, the rapid developments of navigation sensors and communication technologies have enabled Unmanned Aerial Vehicles (UAVs) to conduct photogrammetric mapping without using GCP because of the availability of new methods such as RTK (Real Time Kinematic) and PPK (Post Processed Kinematic) technology. In this study, an experiment was conducted to evaluate the potential of RTK-UAV mapping with no GCPs compared to that of non RTK-UAV mapping. The positioning accuracy results produced by images obtained simultaneously from the two different types of UAVs were compared and analyzed. One was a RTK-UAV without GCPs and the other was a non RTK-UAV with different numbers of GCPs. The images were taken with a Canon IXUS 127 camera (focal length 4.3mm, pixel size $1.3{\mu}m$) at a flying height of approximately 160m, corresponding to a nominal GSD of approximately 4.7cm. As a result, the RMSE (planimetric/vertical) of positional accuracy according to the number of GCPs by the non-RTK method was 4.8cm/8.2cm with 5 GCPs, 5.4cm/10.3cm with 4 GCPs, and 6.2cm/12.0cm with 3 GCPs. In the case of non RTK-UAV photogrammetry with no GCP, the positioning accuracy was decreased greatly to approximately 112.9 cm and 204.6 cm in the horizontal and vertical coordinates, respectively. On the other hand, in the case of the RTK method with no ground control point, the errors in the planimetric and vertical position coordinates were reduced remarkably to 13.1cm and 15.7cm, respectively, compared to the non-RTK method. Overall, UAV photogrammetry supported by RTK-GPS technology, enabling precise positioning without a control point, is expected to be useful in the field of spatial information in the future.

• Journal of Technology Innovation
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• v.26 no.3
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• pp.37-68
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• 2018

Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers. For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.4
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• pp.407-414
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• 2010

Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.161-173
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• 2020

As ICT convergence technology has spread and applied to various industrial fields and society in general, interest in rural entrepreneurship using smart farm as a means for solving many pending problems in agriculture is increasing. In this context, this study is to look at the influential factors in terms of perceived usefulness associated with the rural entrepreneurial intention using smart farm and suggest a proposal for spreading smart farms. The subjects were 296 general adults over 20 years old who were selected by simple random sampling method. The research method was exploratory factor analysis and multiple regression analysis using IBM SPSS 22.0. The perceived usefulness of smart farm, which are availability, reliability and economic efficiency were selected as independent variables to analyze the influential factors on rural entrepreneurial intention using smart farm and the moderating effect of personal innovation was observed. As a result, reliability and economic efficiency have a positive(+) influence on rural entrepreneurial intention using smart farm. And personal innovation moderates the relationship between the availability, reliability of smart farm and rural entrepreneurial intention using smart farm. The results of this study have significance in that we devised and empirically revealed factors affecting rural entrepreneurship intentions from the perspective of perceived usefulness of smart farms, away from studies of general entrepreneurship intention factors such as internal personal characteristics and external environmental factors. The implications of the study are expected to be utilized at the seeking direction of policy for potential entrepreneur using smart farm, the training and consulting in actual field of smart farm.

• Asia pacific journal of information systems
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• v.22 no.2
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• pp.21-38
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• 2012

Until recently, successful implementation of ERP systems has been a popular topic among ERP researchers, who have attempted to identify its various contributing factors. None of these efforts, however, explicitly recognize the need to identify disparities that can exist between organizational information requirements and ERP systems. Since ERP systems are in fact "packages" -that is, software programs developed by independent software vendors for sale to organizations that use them-they are designed to meet the general needs of numerous organizations, rather than the unique needs of a particular organization, as is the case with custom-developed software. By adopting standard packages, organizations can substantially reduce many of the potential implementation risks commonly associated with custom-developed software. However, it is also true that the nature of the package itself could be a risk factor as the features and functions of the ERP systems may not completely comply with a particular organization's informational requirements. In this study, based on the organizational memory mismatch perspective that was derived from organizational memory theory and cognitive dissonance theory, we define the nature of disparities, which we call "mismatches," and propose that the mismatch between organizational information requirements and ERP systems is one of the primary determinants in the successful implementation of ERP systems. Furthermore, we suggest that customization efforts as a coping strategy for mismatches can play a significant role in increasing the possibilities of success. In order to examine the contention we propose in this study, we employed a survey-based field study of ERP project team members, resulting in a total of 77 responses. The results of this study show that, as anticipated from the organizational memory mismatch perspective, the mismatch between organizational information requirements and ERP systems makes a significantly negative impact on the implementation success of ERP systems. This finding confirms our hypothesis that the more mismatch there is, the more difficult successful ERP implementation is, and thus requires more attention to be drawn to mismatch as a major failure source in ERP implementation. This study also found that as a coping strategy on mismatch, the effects of customization are significant. In other words, utilizing the appropriate customization method could lead to the implementation success of ERP systems. This is somewhat interesting because it runs counter to the argument of some literature and ERP vendors that minimized customization (or even the lack thereof) is required for successful ERP implementation. In many ERP projects, there is a tendency among ERP developers to adopt default ERP functions without any customization, adhering to the slogan of "the introduction of best practices." However, this study asserts that we cannot expect successful implementation if we don't attempt to customize ERP systems when mismatches exist. For a more detailed analysis, we identified three types of mismatches-Non-ERP, Non-Procedure, and Hybrid. Among these, only Non-ERP mismatches (a situation in which ERP systems cannot support the existing information needs that are currently fulfilled) were found to have a direct influence on the implementation of ERP systems. Neither Non-Procedure nor Hybrid mismatches were found to have significant impact in the ERP context. These findings provide meaningful insights since they could serve as the basis for discussing how the ERP implementation process should be defined and what activities should be included in the implementation process. They show that ERP developers may not want to include organizational (or business processes) changes in the implementation process, suggesting that doing so could lead to failed implementation. And in fact, this suggestion eventually turned out to be true when we found that the application of process customization led to higher possibilities of failure. From these discussions, we are convinced that Non-ERP is the only type of mismatch we need to focus on during the implementation process, implying that organizational changes must be made before, rather than during, the implementation process. Finally, this study found that among the various customization approaches, bolt-on development methods in particular seemed to have significantly positive effects. Interestingly again, this finding is not in the same line of thought as that of the vendors in the ERP industry. The vendors' recommendations are to apply as many best practices as possible, thereby resulting in the minimization of customization and utilization of bolt-on development methods. They particularly advise against changing the source code and rather recommend employing, when necessary, the method of programming additional software code using the computer language of the vendor. As previously stated, however, our study found active customization, especially bolt-on development methods, to have positive effects on ERP, and found source code changes in particular to have the most significant effects. Moreover, our study found programming additional software to be ineffective, suggesting there is much difference between ERP developers and vendors in viewpoints and strategies toward ERP customization. In summary, mismatches are inherent in the ERP implementation context and play an important role in determining its success. Considering the significance of mismatches, this study proposes a new model for successful ERP implementation, developed from the organizational memory mismatch perspective, and provides many insights by empirically confirming the model's usefulness.

• The Korean Journal of Pesticide Science
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• v.20 no.3
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• pp.271-279
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• 2016

To evaluate exposure characteristics of the insecticide imidacloprid to apple orchard workers during treatment on orchard fields and evaluate its potential risk using a whole body dosimetry (WBD) method, 1,000-time diluted acephate+imidacloprid 25(20+5)% solutions were sprayed on 10 apple orchard fields in Cheongju with a speed sprayer at a rate of 3,000 L/ha/person, after put on clothes such as inner/outer clothes, personal air pump with a IOM sampler, nitrile glove and mask. Exposure test included mixing, loading and application steps. The test pesticide imidacloprid residues in the collected samples were analyzed with a HPLC-DAD. Recoveries ranged from 81.5 to 108.6% for analytical method validation and from 73.8 to 86.7% for field recovery. Total exposed amounts to mixer/loader and applicator were found to be 0.0014-0.0279% of total applied active ingredient of imidacloprid. Glove exposure of both mixer/loader and applicator was higher than the other parts. Margins of safety of mixer/loader and applicator were calculated to be 97-355 and 46-196, respectively, indicating that exposure risk of imidacloprid to apple orchard workers by spraying with a speed sprayer was very low.

• Journal of Distribution Science
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• v.9 no.4
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• pp.43-50
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• 2011

Concerning the risk factors of the outbreak of a fire in a traditional market, most of those markets are located in downtown areas or residential areas; thus, although their location may be favorable in terms of marketability, they face a potential risk in that a fire may develop into a large blaze owing to poor environment or the absence of facilities prepared for disaster during a fire. Moreover, as many people are densely poised in the markets, it is very probable that a fire may occur owing to the excessive use of heaters in the winter as well as the reckless use of electric and gas facilities. It seems that traditional markets encounter difficulty being insured against fire, because of their vulnerability and that the vast majority of small-scale sellers are likely to suffer mental anguish and tremendous physical injury in case of a fire. However, most of those sellers in the traditional markets are hand-to-mouth sellers, and they lack awareness of safety concerns and have insufficient experience in safe facility management. As small-scale sellers constitute the majority in the traditional market, the subscription rate of fire insurance in most of the traditional markets is low for the reasons of their needy circumstances and their financial burden. Statistically, the subscription by street vendors is non-existent; therefore, these vendors have a fairly limited access to indemnification after fire damage. Because of these problems, this study's purpose is to identify the current level of insurance subscription by these markets, which are exposed to poor facilities and vulnerability to fire. In order to fix this, it appears that shop owners and consumers will have to band together. For this study, we executed a fire policyholder fact-finding mission at traditional markets with approximately 108 and 981 stores. The research method was executed by an investigation using one-on-one individual interviews using a questionnaire. The contents investigated current insurance subscriptions. The method of analysis looked at the difference of insured amount according to volume size through cross-tabulation of the difference of insured amount by possession form, difference of insured amount by market form, difference of insured amount by category of business, difference of insured amount by market size, etc. Furthermore, the study should be used to propose solutions for problems through theoretical review with the use of a literature research, because the field case study was through interviews with the persons concerned, and the survey of the current insurance subscriptions by traditional market shopkeepers. The traditional market would generally have difficulty affording fire insurance. Fire insurance subscription rates of most of the market proved to be inactive, because of the economic burden of payment. Lack of funds is thought to be the main factor that causes a lack of realization about the necessity of fire insurance. In addition to expensive insurance premiums, sometimes, the companies' valuation of the businesses is lower than their actual valuations, and they do not pay out enough during a claim. The research presents an improvement plan that, when presented at the traditional markets, may strengthen their ability to procure fire insurance through the help of the central government. Researchers connected with the traditional market mainly accomplish the initial research. However, although this research has its limitations, it offers considerable benefits. For future researchers, I would suggest looking at several regions for comparison.

• Composites Research
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• v.36 no.1
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• pp.1-15
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• 2023

Demand for energy consumption reduction is increasing according to the development expectations of future mobility. Lightweight structural materials are known as a method to reduce greenhouse gas emissions and improve energy efficiency. In particular, fiber reinforced polymer composite (FRP) is attracting attention as a material that can replace existing metal alloys due to its excellent mechanical properties and light weight. In this paper, industrial applications and research trends of carbon fiber reinforced composites (CFRP, carbon FRP) and self-reinforced composites (SRC) were reviewed based on the reinforcement, polymer matrix, and manufacturing process. In order to overcome the expensive process cost and long manufacturing time of the epoxy resin-based autoclave method, which is mainly used in the aircraft field, mass production of CFRP-applied electric vehicles has been reported using a high-pressure resin transfer molding process including fast-curing epoxy. In addition, thermoplastic resin-based CFRP and interface enhancement methods to solve the recycling issue of carbon fiber composites were reviewed in terms of materials and processes. To form a perfect matrix-reinforcement interface, which is known as the major factor inducing the excellent mechanical properties of FRP, studies on SRC impregnated with the same matrix in polymer fibers have been reported. The physical and mechanical properties of SRC based on various thermoplastic polymers were reviewed in terms of polymer orientation and composite structure. In addition, a copolymer matrix strategy for extending the processing window of highly drawn polypropylene fiber-based SRC was discussed. The application of CFRP and SRC as lightweight structural materials can provide potential options for improving the energy efficiency of future mobility.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.4
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• pp.386-408
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• 1988

A study was conducted to develop a model for estimating evapotranspiration and yield of Chinese cabbages from meteorological factors from 1981 to 1986 in Suweon, Korea. Lysimeters with water table maintained at 50cm depth were used to measure the potential evapotranspiration and the maximum evapotranspiration in situ. The actual evapotranspiration and the yield were measured in the field plots irrigated with different soil moisture regimes of -0.2, -0.5, and -1.0 bars, respectively. The soil water content throughout the profile was monitored by a neutron moisture depth gauge and the soil water potentials were measured using gypsum block and tensiometer. The fresh weight of Chinese cabbages at harvest was measured as yield. The data collected in situ were analyzed to obtain parameters related to modeling. The results were summarized as followings: 1. The 5-year mean of potential evapotranspiration (PET) gradually increased from 2.38 mm/day in early April to 3.98 mm/day in mid-June, and thereafter, decreased to 1.06 mm/day in mid-November. The estimated PET by Penman, Radiation or Blanney-Criddle methods were overestimated in comparison with the measured PET, while those by Pan-evaporation method were underestimated. The correlation between the estimated and the measured PET, however, showed high significance except for July and August by Blanney-Criddle method, which implied that the coefficients should be adjusted to the Korean conditions. 2. The meteorological factors which showed hgih correlation with the measured PET were temperature, vapour pressure deficit, sunshine hours, solar radiation and pan-evaporation. Several multiple regression equations using meteorological factors were formulated to estimate PET. The equation with pan-evaporation (Eo) was the simplest but highly accurate. PET = 0.712 + 0.705Eo 3. The crop coefficient of Chinese cabbages (Kc), the ratio of the maximum evapotranspiration (ETm) to PET, ranged from 0.5 to 0.7 at early growth stage and from 0.9 to 1.2 at mid and late growth stages. The regression equation with respect to the growth progress degree (G), ranging from 0.0 at transplanting day to 1.0 at the harvesting day, were: $$Kc=0.598+0.959G-0.501G^2$$ for spring cabbages $$Kc=0.402+1.887G-1.432G^2$$ for autumn cabbages 4. The soil factor (Kf), the ratio of the actual evapotranspiration to the maximum evapotranspiration, showed 1.0 when the available soil water fraction (f) was higher than a threshold value (fp) and decreased linearly with decreasing f below fp. The relationships were: Kf=1.0 for $$f{\geq}fp$$ Kf=a+bf for f$$I{\leq}Esm$$ Es = Esm for I > Esm 6. The model for estimating actual evapotranspiration (ETa) was based on the water balance neglecting capillary rise as: ETa=PET. Kc. Kf+Es 7. The model for estimating relative yield (Y/Ym) was selected among the regression equations with the measured ETa as: Y/Ym=a+bln(ETa) The coefficients and b were 0.07 and 0.73 for spring Chinese cabbages and 0.37 and 0.66 for autumn Chinese cabbages, respectively. 8. The estimated ETa and Y/Ym were compared with the measured values to verify the model established above. The estimated ETa showed disparities within 0.29mm/day for spring Chinese cabbages and 0.19mm/day for autumn Chinese cabbages. The average deviation of the estimated relative yield were 0.14 and 0.09, respectively. 9. The deviations between the estimated values by the model and the actual values obtained from three cropping field experiments after the completion of the model calibration were within reasonable confidence range. Therefore, this model was validated to be used in practical purpose.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.