To design more efficient agricultural machinery, the accurately measuring system among many other factors is essential. A light-beam oscillographic recorder is generally used in measuring dynamic strain but it is not compatible with the extremely high speed measuring system such as 1,000 m/s, also is susceptable to damage due to vibration while using the system in field. The recorder used light sensitive paper for strip chart recording. The reading and analysis of data from the strip charts is very cumbersome, errorneous and time consuming. A microcomputer was interfaced with A/D converter, microcomputer program was developed for measuring, system calibration was done and the strain generated from a cantilever beam vibrator was measured. The results are summarized as follows. 1. Microcomputer program was developed to perform strain measuring of agricultural machine elements and could be controled freely the measuring intervals, no. of channels and no. of data. The maximum measuring speed was $62{\mu}s$. 2. Calibration the system was performed with triangle wave generated from a function generator and checked by an oscilloscope. The sampled data were processed using HP 3000 minicomputer of Chungnam National University computer center the graphical results were triangle same as input wave and so the system have been out of phase distorsion and amplitude distorsion. 3. The strain generated from a cantilever beam vibrator which has free vibration period of 0.019 second were measured by the system controlled to have l.0 ms of time interval and its computer output showing vibration curve which is well filted to theoretical value. 4. Using microcomputer on measuring the strain of agricultural machine elements could not only save analyzing time and recording papers but also get excellent adaptation to field experiment, especially in measurement requiring high speed and good precision.
Journal of Agricultural Extension & Community Development
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v.21
no.4
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pp.1093-1124
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2014
Studies on the role of agricultural science colleges are mostly divided into agricultural production, which is the primary function of agriculture, and other functions, which have recently begun to be emphasized as a result of social needs. With the green revolution and the aging of the farming population, there is a strong view that the role of agricultural science colleges should remain as it is. However, agriculture is expanding in terms of concept and content by converging with other industries not traditionally associated with agricultural production. Thus, the fields that now need to form part of agricultural science knowledge are becoming more detailed and expansive. The government's perception remains at the level of merely fostering farmers. This was evident in a survey on the employment rate, a factor used to evaluate colleges, in which the role of agricultural science colleges was limited to fostering farmers. Agro- industry fields, other than agriculturalists, include general industries in which the academic fields of agricultural science are combined with other academic fields. Thus, even when someone is employed in an industry that requires background knowledge of agricultural science, there is often a perception that he or she is employed in a field that is irrelevant to the major. This study examines the role of agricultural science colleges in agriculture and farm villages by focusing on the employment of graduates of these colleges within agro-industry. We categorize academic research on agricultural science into 16 fields, based on the medium level of the National Standard Science and Technology Classification Codes. Then, we categorize the employment fields into 168 fields, based on the small classification level of the inter-industry relations classification. Thus, we investigate 220 departments of 37 colleges, nationwide. Our findings show that the average employment rate of graduates of agricultural science colleges is 69.0%. Furthermore, 33.0% of all employees work in agro-industry fields that require background knowledge in agricultural science, which is one out of three job seekers. Then, 3.6% of employees work in business startups in agro-industry. The aforementioned government survey showed that only 0.1% of all college graduates in Korea were employed as agriculturalists in 2013. However, our results showed that 13.3% of graduates were working as agriculturalists, which is significantly different to the results of the government survey. These results confirm that agricultural science colleges contribute greatly to the employment of graduates, including farmers, agro-industry, and business startups in agro-industry fields.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.7
no.3
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pp.1-16
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2012
Under the international business circumstance, global supply chain management is considered a vital strategic challenge to small and medium-sized enterprises(SMEs) suffering from deficient resources and capabilities to exploit overseas markets comparing with large corporations. That is because they can expand their business domains into overseas markets by establishing strategic alliances with global supply chain partners. Although a wide range of previous researches have emphasized the cooperative networks in the chain, most are ignoring the importance of developing relational characteristics such as trust and reciprocity with the partners. Besides, verifying the relational factors influencing firms' export performances, some studies proposed different and inconsistent factors. According to the social capital theory, which is the social quality and networks facilitating close cooperation of inter-individual and inter-organization, provides the integrated view to identify the relational characteristics in the aspects of network, trust and reciprocal norm. Meanwhile, a number of researchers shows that global entrepreneurship is the internal and intangible resource necessary to promote SMEs' internationalization. Upon closer examination, however, they cannot explain clearly its influencing mechanism in the inter-firm cooperative relationships. This study is to verify the effect of social capital accumulated within global supply chain on SMEs' qualitative and quantitative export performance. In addition, we shed new light on global entrepreneurship expected to be concerned with the formation of social capital and the enhancement of export performances. For this purpose, the questionnaires, developed through literature review, were collected from 192 Korean SMEs affiliated in Korean Medium Industries Association and Global Chief Executive Officer's Club focusing on their memberships' international business. As a result of multi-regression analysis, the social capital - network, trust and reciprocal norm shared with global supply chain partner - as well as global entrepreneurship - innovativeness, proactiveness and risk-taking - have positive effect on SMEs' export performances. Also global entrepreneurship affects positively social capital which has mediating effect partially in the relationship between global entrepreneurship and performances. These results means that there is a structural process - global entrepreneurship(input), social capital(output), and export performances(outcome). In other words, a firm should consistently invest in and develop the social capital with global supply chain partners in order to achieve common goals, establish strategic collaborations and obtain long-term export performances. Furthermore, it is required to foster the global entrepreneurship in an organization so as to build up the social capital. More detailed practical issues and discussion are made in the conclusion.
The objectives of this study is to figure out the unknown image processing methods of commercial CR system. We have implemented the processing curve of each Look up table(LUT) in REGIUS 150 CR system by using virtual digital test pattern method. The characteristic of Dry Imager was measured also. First of all, we have generated the virtual digital test pattern file with binary file editor. This file was used as an input data of CR system (REGIUS 150 CR system, KONICA MINOLTA). The DICOM files which were automatically generated output files by the CR system, were used to figure out the processing curves of each LUT modes (THX, ST, STM, LUM, BONE, LIN). The gradation curves of Dry Imager were also measured to figure out the characteristics of hard copy image. According to the results of each parameters, we identified the characteristics of image processing parameter in CR system. The processing curves which were measured by this proposed method showed the characteristics of CR system. And we found the linearity of Dry Imager in the middle area of processing curves. With these results, we found that the relationships between the curves and each parameters. The G value is related to the slope and the S value is related to the shift in x-axis of processing curves. In conclusion, the image processing method of the each commercial CR systems are different, and they are concealed. This proposed method which uses virtual digital test pattern can measure the characteristics of parameters for the image processing patterns in the CR system. We expect that the proposed method is useful to analogize the image processing means not only for this CR system, but also for the other commercial CR systems.
This article was intended to survey whether Roy' Adapation model ('Roy Model') can be applied to family health assessment and to study whether application of the Roy Model to a Korean family is feasible. under the Roy Model, a family is viewed as an adaptation system having a series of process of input. process, feedback, and output. Further, the Roy Model indicates that a family contains Physiolosical, self-concept. role function and interdependent mode in respect of internal or external stimuli. In the event where the family health assessed, the adaptation mode of that family must be assess at the first stage. Then, the focal, contextual, residual stimuli affecting the family must be assessed. In 1984 Hanson suggested four types of family adaptation mode based upon the Roy Model and thereby enhanced the possibility for family health assessment. In order survey whether the Roy Model can be applied to the Korean family, the author of this article contracted adults of 169 who live in 'A' city to make open questions regarding family and then analyzed responses from them by utilizing Roy model. This study categorized family Adaptation mode based upon the' four types of family adaptation mode developed by Hanson. As a result of this study, family adaptation mode was categorized into 117 concepts. Those 117 concepts are consisted or Physiolosical mode of 47. selfconcept mode of 56, role function mode of 9 and interdependent mode of 5. Further. stimuli affecting family were classified based upon Roy's definition as to three types of stimuli. Stimuli on a family are comprised focal stimuli concept of 19, contextual stimuli concepts of 19, one residual stimuli concept. this result implies that the Roy's Model can be applied to Korean family. Physiological mode shows meaning of survival. while self-concept mode reflects meaning of growth and emphasizes harmony among the family based on the familism. The role function mode shows continuity rather control of family member. By contrast, interdependent mode shows interaction with community to which the family belongs. but the degree of interaction does not appear too high. The analysis of family stimuli led this study to conclude that troubles within a family. changes in family structure and diease of family member generate stimuli. However, an application of the Roy Model contains the following problems: First, Roy argued that the family adaptation mode should be assessed at the first level family health assessment and then stimuli affecting family adaptation should be adaptation assessed at the second stage. To the belief of the author of this article. however, for checking family adaptation level. focal, contextual, residual stimuli should be confirmed by assessing stimuli at first stage. Then, the family adaptation mode in respect of such stimuli should be assessed. The rationale for this is that the family adaptation level is determined depending on degree of strength of focal. contextual. residual stimuli. Second. Whall (1991) raised a question 'Does one assess family adaptation mode and intervene in the stimuli?' 'Likewise, assessment of the family adaptation should be made in the following manner in order for family health to be enhanced. Third. Roy believes that additional stimuli (such as contextual and residual) are same as internal process (including nurturance. support, and socialization). However, the basis for this Roy's belief is not too clear. In spite of these problems which the author indicated above, it can be concluded that the Roy Model can serve as a good device for an assessment of family health and that the Roy Model can be applied to a Korean family. Finally, further research of family adaptation theory and family nursing theory is required for a development of these theories.
The Transactions of the Korea Information Processing Society
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v.1
no.3
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pp.367-379
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1994
This paper describes scheduling algorithms of the UNIX operating system and shows an analytical approach to approximate the average conditional response time for a process in the UNIX operating system. The average conditional response time is the average time between the submittal of a process requiring a certain amount of the CPU time and the completion of the process. The process scheduling algorithms in thr UNIX system are based on the priority service disciplines. That is, the behavior of a process is governed by the UNIX process schuduling algorithms that (ⅰ) the time-shared computer usage is obtained by allotting each request a quantum until it completes its required CPU time, (ⅱ) the nonpreemptive switching in system mode and the preemptive switching in user mode are applied to determine the quantum, (ⅲ) the first-come-first-serve discipline is applied within the same priority level, and (ⅳ) after completing an allotted quantum the process is placed at the end of either the runnable queue corresponding to its priority or the disk queue where it sleeps. These process scheduling algorithms create the round-robin effect in user mode. Using the round-robin effect and the preemptive switching, we approximate a process delay in user mode. Using the nonpreemptive switching, we approximate a process delay in system mode. We also consider a process delay due to the disk input and output operations. The average conditional response time is then obtained by approximating the total process delay. The results show an excellent response time for the processes requiring system time at the expense of the processes requiring user time.
The optimization of supercritical water oxidation (SCWO) process for decomposing nitromethane was studied by means of a design of experiments. The optimum operating region for the SCWO process to minimize COD and T-N of treated water was obtained in a lab scale unit. The authors had compared the results from a SCWO pilot plant with those from a lab scale system to explore the problems of scale-up of SCWO process. The COD and T-N in treated waters were selected as key process output variables (KPOV) for optimization, and the reaction temperature (Temp) and the mole ratio of nitromethane to ammonium hydroxide (NAR) were selected as key process input variables (KPIV) through the preliminary tests. The central composite design as a statistical design of experiments was applied to the optimization, and the experimental results were analyzed by means of the response surface method. From the main effects analysis, it was declared that COD of treated water steeply decreased with increasing Temp but slightly decreased with an increase in NAR, and T-N decreased with increasing both Temp and NAR. At lower Temp as $420{\sim}430^{\circ}C$, the T-N steeply decreased with an increase in NAR, however its variation was negligible at higher Temp above $450^{\circ}C$. The regression equations for COD and T-N were obtained as quadratic models with coded Temp and NAR, and they were confirmed with coefficient of determination ($r^2$) and normality of standardized residuals. The optimum operating region was defined as Temp $450-460^{\circ}C$ and NAR 1.03-1.08 by the intersection area of COD < 2 mg/L and T-N < 40 mg/L with regression equations and considering corrosion prevention. To confirm the optimization results and investigate the scale-up problems of SCWO process, the nitromethane was decomposed in a pilot plant. The experimental results from a SCWO pilot plant were compared with regression equations of COD and T-N, respectively. The results of COD and T-N from a pilot plant could be predicted well with regression equations which were derived in a lab scale SCWO system, although the errors of pilot plant data were larger than lab ones. The predictabilities were confirmed by the parity plots and the normality analyses of standardized residuals.
The Korean central government has not appreciate the full extent of the impact of seaports on the national economy. As a consequence port investment has not been given sufficient priority and capacity has failed to keep pace with demand. The principal reason for this failure is the fact that the linkages (or relationships) of the port transport industry with other sectors have not been quantified and fully appreciated. To overcome this dificiency this paper developed a port input-output model to determine the economic impact of the port industry on the national economy. This impact study was conducted by analysing the impact of the Korean port industry upon the national economy from the macroeconomic viewpoint, and identifying the spreading effects of port investments upon the nation's economy. The analysis of the economic impact of the port industry suggests that its contribution to the Korean economy is substantial. What the model shows is, in quantifiable terms, there are the strong economic linkages between the port industry and the other sectors of the national economy. The contribution of the port industry to the Korean economy was summarised in the Conclusion section.
Taeyoon Eom;Kwangnyun Kim;Yonghan Jo;Keunyong Song;Yunjeong Lee;Yun Gon Lee
Korean Journal of Remote Sensing
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v.39
no.2
/
pp.207-221
/
2023
This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.
In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH3, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.
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