• Journal of the Korean Professional Engineers Association
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• v.16 no.3
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• pp.41-53
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• 1983

The Dangri Crushed Stone Quarry is located in Dangridong, Busan City, and around the estuary of the Nagdong River. The quarry is considered to be a very promised one in the urban area from the standpoints of the assessment of the aggregate rank, the environmental impacts and the transportation distance. The crushed stones for aggregate of the quarry marks the higher rank in the gravity, the absorption ratio, the abrasion ratio, and the stability in comparison with the JISA 5005. The basement vibrations of the residential section in the vicinity of the quarry, which are arised by the millisecond blasting at the quarry site using the gelatin dynamites less than 39kg in weight, are measured to assess the vibration nuisance. The values of acceleration and the magnitudes are less than eight gals and O on the Richter scale respectively, the vibration nuisance thus can be ignored in such scales of the experiments. The traffic vibrations of the residential section are slightly susceptible. In the experiments, the traffic vibrations appears to be sensibler to the basement than the explosion vibration. The explosion noises in the experiments are not checked not only on the RION Sound Level Meter but also to our ears. The values of traffic noises also are in the safety values of the noise nuisance. The crush dust suspends in the air toward the upper valley in the opposite side of the residential area because of the influences of the sea breeze and the valley wind in the daytime, and the monsoon and the topographic disposition. the dust nuisance thus would not be remained in problem. The quarry is operated in the daytime only. The traffic dust in the residential area will be reduced by the faultless pavement and the careful driving. The elaborate survey on the ridges and peaks surrounded the quarry is recommended to prevent in advance the accidents of the rock slide. Moreover, it is required to make an advisory committee to develop the industry and to save the techniques. The most important matter is the accomodation between the attitude of the enterprising man for the social responsibility to the public nuisance and the cooperative spirit of the inhabitants for the industry.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.827-830
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• 2013

Due to strong wind of smartphone, change in human life is facing 21 Century's new revolution. The end of 2012, The record rate of supply of smartphone is up to 58.8 percent. So the reputation of IT power are continuing. Korea is boasting IT infrastructure, and the reputation of IT power with rapidly evolving. But Korea is one of OECD country with the longest working hours and in labor productivity, yet is located in the lower rank. Now, common social issues such as low-carbon, green growth, low birthrate, graying, labor productivity growth, the reduce greenhouse gas is constantly increasing in worldwide. So Smart Work is getting attention as a way to resolve this. In this paper, we study the impact of small business on local economy and the status information of small business on statistical point of view. And we offer the smart work countermeasures of small business through detailed action elements and the model proposed fot driving factor for the promotion of smart work. Through this, we propose the IT system model for The SMEs-type smart work system.

• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.110-122
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• 2010

The emergence of the field of organizational buying behavior in the mid-1960’s with the publication of Industrial Buying and Creative Marketing (1967) set the stage for a new paradigm of thinking about how business was conducted in markets other than those serving ultimate consumers. Whether it is "industrial marketing" or "business-to-business marketing" (B-to-B), organizational buying behavior remains the core differentiating characteristic of this domain of marketing. This paper explores the impact of several dynamic factors that have influenced how organizations relate to one another in a rapidly increasing interdependence, which in turn can impact organizational buying behavior. The paper also raises the question of whether or not the major conceptual models of organizational buying behavior in an interdependent world are still relevant to guide research and managerial thinking, in this dynamic business environment. The paper is structured to explore three questions related to organizational interdependencies: 1. What are the factors and trends driving the emergence of organizational interdependencies? 2. Will the major conceptual models of organizational buying behavior that have developed over the past half century be applicable in a world of interdependent organizations? 3. What are the implications of organizational interdependencies on the research and practice of organizational buying behavior? Consideration of the factors and trends driving organizational interdependencies revealed five critical drivers in the relationships among organizations that can impact their purchasing behavior: Accelerating Globalization, Flattening Networks of Organizations, Disrupting Value Chains, Intensifying Government Involvement, and Continuously Fragmenting Customer Needs. These five interlinked drivers of interdependency and their underlying technological advances can alter the relationships within and among organizations that buy products and services to remain competitive in their markets. Viewed in the context of a customer driven marketing strategy, these forces affect three levels of strategy development: (1) evolving customer needs, (2) the resulting product/service/solution offerings to meet these needs, and (3) the organization competencies and processes required to develop and implement the offerings to meet needs. The five drivers of interdependency among organizations do not necessarily operate independently in their impact on how organizations buy. They can interact with each other and become even more potent in their impact on organizational buying behavior. For example, accelerating globalization may influence the emergence of additional networks that further disrupt traditional value chain relationships, thereby changing how organizations purchase products and services. Increased government involvement in business operations in one country may increase costs of doing business and therefore drive firms to seek low cost sources in emerging markets in other countries. This can reduce employment opportunitiesn one country and increase them in another, further accelerating the pace of globalization. The second major question in the paper is what impact these drivers of interdependencies have had on the core conceptual models of organizational buying behavior. Consider the three enduring conceptual models developed in the Industrial Buying and Creative Marketing and Organizational Buying Behavior books: the organizational buying process, the buying center, and the buying situation. A review of these core models of organizational buying behavior, as originally conceptualized, shows they are still valid and not likely to change with the increasingly intense drivers of interdependency among organizations. What will change however is the way in which buyers and sellers interact under conditions of interdependency. For example, increased interdependencies can lead to increased opportunities for collaboration as well as conflict between buying and selling organizations, thereby changing aspects of the buying process. In addition, the importance of communication processes between and among organizations will increase as the role of trust becomes an important criterion for a successful buying relationship. The third question in the paper explored consequences and implications of these interdependencies on organizational buying behavior for practice and research. The following are considered in the paper: the need to increase understanding of network influences on organizational buying behavior, the need to increase understanding of the role of trust and value among organizational participants, the need to improve understanding of how to manage organizational buying in networked environments, the need to increase understanding of customer needs in the value network, and the need to increase understanding of the impact of emerging new business models on organizational buying behavior. In many ways, these needs deriving from increased organizational interdependencies are an extension of the conceptual tradition in organizational buying behavior. In 1977, Nicosia and Wind suggested a focus on inter-organizational over intra-organizational perspectives, a trend that has received considerable momentum since the 1990's. Likewise for managers to survive in an increasingly interdependent world, they will need to better understand the complexities of how organizations relate to one another. The transition from an inter-organizational to an interdependent perspective has begun, and must continue so as to develop an improved understanding of these important relationships. A shift to such an interdependent network perspective may require many academicians and practitioners to fundamentally challenge and change the mental models underlying their business and organizational buying behavior models. The focus can no longer be only on the dyadic relations of the buying organization and the selling organization but should involve all the related members of the network, including the network of customers, developers, and other suppliers and intermediaries. Consider for example the numerous partner networks initiated by SAP which involves over 9000 companies and over a million participants. This evolving, complex, and uncertain reality of interdependencies and dynamic networks requires reconsideration of how purchase decisions are made; as a result they should be the focus of the next phase of research and theory building among academics and the focus of practical models and experiments undertaken by practitioners. The hope is that such research will take place, not in the isolation of the ivory tower, nor in the confines of the business world, but rather, by increased collaboration of academics and practitioners. In conclusion, the consideration of increased interdependence among organizations revealed the continued relevance of the fundamental models of organizational buying behavior. However to increase the value of these models in an interdependent world, academics and practitioners should improve their understanding of (1) network influences, (2) how to better manage these influences, (3) the role of trust and value among organizational participants, (4) the evolution of customer needs in the value network, and (5) the impact of emerging new business models on organizational buying behavior. To accomplish this, greater collaboration between industry and academia is needed to advance our understanding of organizational buying behavior in an interdependent world.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.27 no.4
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• pp.296-313
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• 1982

At a time when world population and food supply are in a delicate balance, it is essential that we look at factors to improve this balance. We can alter the environment to better fit the plant's needs, or we can alter the plant to better fit the environment. Improved technology has allowed us to increase the yield level. For moderately detrimental weather events technology has generally decreased the yield variation, yet for major weather disasters the variation has increased. We have raised the upper level, but zero is still the bottom level. As we concentrate the production of particular crops into limited areas where the environment is closest to optimum, we may be increasing the risk of a major weather related disaster. We need to evaluate the degree of variability of different crops, and how weather and technology can interact to affect it. The natural limits of crop production are imposed by important ecological factors. Production is a function of the climate, the soil, and the crop and all activities related to them. In looking at the environment of a crop we must recognize these are individuals, populations and ecosystems. Under intensive agriculture we try to limit the competition to one desired species. The environment is made up of a complex of factors; radiation, moisture, temperature and wind, among others. Plant response to the environment is due to the interaction of all of these factors, yet in attempting to understand them we often examine each factor individually. Variation in crop yields is primarily a function of limiting environmental parameters. Various weather parameters will be discussed, with emphasis placed on how they impact on crop production. Although solar radiation is a driving force in crop production, it often shows little relationship to yield variation. Water may enter into crop production as both a limiting and excessive factor. The effects of moisture deficiency have received much more attention than moisture excess. In many areas of the world, a very significant portion of yield variation is due to variation in the moisture factor. Temperature imposes limits on where crops can be grown, and the type of crop that can be grown in an area. High temperature effects are often combined with deficient moisture effects. Cool temperatures determine the limits in which crops can be grown. Growing degree units, or heat accumulations, have often been used as a means of explaining many temperature effects. Methods for explaining chilling effects are more limited.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.821-828
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• 2011

This paper developed the algorithm for improving the performance the auto pilot in the autonomous vehicle system consisting of the Track keeping control, the Automatic steering, and the Automatic mooring control. The automatic steering is the control device that could save the voyage distance and cost of fuel by reducing the unnecessary burden of driving due to the continuous artificial navigation, and avoiding the route deviation. During the step of the ship autonomic navigation control, since the wind power or the tidal force could make the ship deviate from the fixed course, the automatic steering calculates the difference between actual sailing line and the set course to keep the ship sailing in the vicinity of intended course. first, we could get the transfer function for the modeling of ship according to the Nomoto model. Considering the maneuverability, we propose it as linear model with only 4 degree of freedoms to present the heading angle response to the input of rudder angle. In this paper, the model of ship is derived from the simplified Nomoto model. Since the proposed model considers the maximum angle and rudder rate of the ship auto pilot and also designs the Fuzzy controller based on existing PID controller, the performance of the steering machine is well improved.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.41-55
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• 2017

This study predicts the average scores of top 150 PGA golf players on 132 PGA Tour tournaments (2013-2015) using data mining techniques and statistical analysis. This study also aims to predict the Top 10 and Top 25 best players in 4 different playoffs. Linear and nonlinear regression methods were used to predict average scores. Stepwise regression, all best subset, LASSO, ridge regression and principal component regression were used for the linear regression method. Tree, bagging, gradient boosting, neural network, random forests and KNN were used for nonlinear regression method. We found that the average score increases as fairway firmness or green height or average maximum wind speed increases. We also found that the average score decreases as the number of one-putts or scrambling variable or longest driving distance increases. All 11 different models have low prediction error when predicting the average scores of PGA Tournaments in 2015 which is not included in the training set. However, the performances of Bagging and Random Forest models are the best among all models and these two models have the highest prediction accuracy when predicting the Top 10 and Top 25 best players in 4 different playoffs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• Journal of Astronomy and Space Sciences
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• v.25 no.2
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• pp.157-166
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• 2008

We have investigated a statistical relationship between sawtooth oscillations and geomagnetic storms during 2000-2004. First of all we selected a total of 154 geomagnetic storms based on the Dst index, and distinguished between different drivers such as Coronal Mass Ejection (CME) and Co-rotating Interaction Region (CIR). Also, we identified a total of 48 sawtooth oscillation events based on geosynchronous energetic particle data for the same 2000-2004 period. We found that out of the 154 storms identified, 47 storms indicated the presence of sawtooth oscillations. Also, all but one sawtooth event identified occurred during a geomagnetic storm interval. It was also found that sawtooth oscillation events occur more frequently for storms driven by CME $({\sim}62%)$ than for storms driven by CIR $({\sim}30%)$. In addition, sawtooth oscillations occurred mainly $({\sim}82%)$ in the main phase of storms for CME-driven storms while they occurred mostly $({\sim}78%)$ during the storm recovery phase for CIR-driven storms. Next we have examined the average characteristics of the Bz component of IMF, and solar wind speed, which were the main components for driving geomagnetic storm. We found that for most of the sawtooth events, the IMF Bz corresponds to -15 to 0 nT and the solar wind speed was in the range of $400{\sim}700km/s$. We found that there was a weak tendency that the number of teeth for a given sawtooth event interval was proportional to the southward IMF Bz magnitude.