• Title/Summary/Keyword: daily labor

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A study on the detailed treatment techniques of seoktap(stone stupa) in Jeollado province -in the groove for dropping water and the hole for wing bell of the okgaeseok(roof stone)- (전라도 석탑의 세부 기법 고찰 - 옥개석 물끊기홈과 충탁공을 중심으로 -)

  • Cho, Eun-kyung;Han, Joo-sung;Nam, Chang-keun
    • Korean Journal of Heritage: History & Science
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    • v.40
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    • pp.271-306
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    • 2007
  • One of the distinguishing features of late Jeosun's Hanshi (poem in Chinese) is the numerous creation of Yeonjachyung Keesokshi (serial poem on folklore) which describes the folk manner and folk way of life in detail. Keesokshi's subject matter is the folklike in general including local features, geography, climate, local production, humanity, social conducts, and daily labor for living as well. By its material characteristics, Keesokshi reflects detailed life conditions of the society members in each levels, and represents the local customs as well as the folk emotions. Among the several kinds of Keesokshis, a Sesi Keesokshi focuses only in reciting the folk customs on each seasonal festival days, and the great numbers of such serial poems appear during the latter part of the Jeosun Dynasty. Its overall background is the transition of artistic trend which came after many social changes such as expansion of realism, uprising national consciousness, shaken status system, and the rising of 'Jeosunsi' motives in the Hansi history. Moreover, each writer's various experiences and their interests in the reality and critical minds of common people contributed a crucial roll in creation of Sesi Keesokshi. 178 of the 584 remaining serial Sesi Keesokshi are written particularly about the folk customs in The Grand Full Moon Festival (the first full moon of a year by the lunar calendar). These Hanshis widely reflect the common ways of living by directly accepting the seasonal folk customs as the subject matters. Especially, close to the reality, these poems positively express the people's simple vigorous lives and create unrestrained lively image by describing the joys and sorrows of the folk existence along with their craving. Also, it is notable to have customs such as 'Shil-Ssa-Um' and 'No-gu-ban-kong-yang' as subjects for its rarity in other literatures.

Industrial Policy as a Development Strategy: Cuba' s Experience and Policy Implications (개발전략으로서 산업정책: 쿠바의 경험과 정책적 시사점)

  • Cin, Beom Cheol
    • International Area Studies Review
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    • v.22 no.3
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    • pp.3-27
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    • 2018
  • This paper analyzes Cuba's market-oriented reforms to alleviate essential problems with socialist countries such as soft budget constraints and incentive problems. It also discuss about effectiveness of industrial policy as a development strategy. The soft budget constraints and incentive problems resulted in the collapse of Soviet bloc and COMECON in early 1990s. After the collapse, Cuban economy suffered a steep dive, and national income tumbling down rapidly. Cuban faced serious shortages of food, gasoline, and other basic necessities of life. To halt and partially reverse economic downturn and dire austerity in the 1990's, the Cuban government made some partial reforms to the inherited Soviet system of cental planningand faced severe shortage in food, energy, and daily necessities. In response to the economic crisis. Cuba introduced economic reforms and implemented industrial policy as a development strategy as long as Cuba maintained a strong socialist country. Cuban government established the economic free zone law and attempted to induce foreign direct investment by implementing export-led industrial policy. Fiedel Castro approved the Law No. 165 "Free Zones and Industrial Parks", in 1996. However, Cuba's ESZ strategy seems to have failed because of the U.S. sanctions, but also because of Cuba's own policies, which do not allow foreign investors to hire workers directly and impose a high implicit tax on wages. By limiting advanced techniques of personnel and organization management, indirect employment can result in lowering work efforts and productivity of workers, and aggravating production efficiency in the ESZs. Another reason to fail comes from the double wage structure due to the double monetary-exchange rate system. Most of the high non-wage costs result from the double exchange rate system. Due to Cuba's imbalanced industry and production structures, concentrated labor force, and urbanization and centralization of agriculture production, the industrial transformation development model suggested by Lewis has not been successful unlike other Asian agriculture-led development model. Cuba has to overcome many difficulties in implementing industrial policy as a development strategy.

Herbicidal Phytotoxicity under Adverse Environments and Countermeasures (불량환경하(不良環境下)에서의 제초제(除草劑) 약해(藥害)와 경감기술(輕減技術))

  • Kwon, Y.W.;Hwang, H.S.;Kang, B.H.
    • Korean Journal of Weed Science
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    • v.13 no.4
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    • pp.210-233
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    • 1993
  • The herbicide has become indispensable as much as nitrogen fertilizer in Korean agriculture from 1970 onwards. It is estimated that in 1991 more than 40 herbicides were registered for rice crop and treated to an area 1.41 times the rice acreage ; more than 30 herbicides were registered for field crops and treated to 89% of the crop area ; the treatment acreage of 3 non-selective foliar-applied herbicides reached 2,555 thousand hectares. During the last 25 years herbicides have benefited the Korean farmers substantially in labor, cost and time of farming. Any herbicide which causes crop injury in ordinary uses is not allowed to register in most country. Herbicides, however, can cause crop injury more or less when they are misused, abused or used under adverse environments. The herbicide use more than 100% of crop acreage means an increased probability of which herbicides are used wrong or under adverse situation. This is true as evidenced by that about 25% of farmers have experienced the herbicide caused crop injury more than once during last 10 years on authors' nationwide surveys in 1992 and 1993 ; one-half of the injury incidences were with crop yield loss greater than 10%. Crop injury caused by herbicide had not occurred to a serious extent in the 1960s when the herbicides fewer than 5 were used by farmers to the field less than 12% of total acreage. Farmers ascribed about 53% of the herbicidal injury incidences at their fields to their misuses such as overdose, careless or improper application, off-time application or wrong choice of the herbicide, etc. While 47% of the incidences were mainly due to adverse natural conditions. Such misuses can be reduced to a minimum through enhanced education/extension services for right uses and, although undesirable, increased farmers' experiences of phytotoxicity. The most difficult primary problem arises from lack of countermeasures for farmers to cope with various adverse environmental conditions. At present almost all the herbicides have"Do not use!" instructions on label to avoid crop injury under adverse environments. These "Do not use!" situations Include sandy, highly percolating, or infertile soils, cool water gushing paddy, poorly draining paddy, terraced paddy, too wet or dry soils, days of abnormally cool or high air temperature, etc. Meanwhile, the cultivated lands are under poor conditions : the average organic matter content ranges 2.5 to 2.8% in paddy soil and 2.0 to 2.6% in upland soil ; the canon exchange capacity ranges 8 to 12 m.e. ; approximately 43% of paddy and 56% of upland are of sandy to sandy gravel soil ; only 42% of paddy and 16% of upland fields are on flat land. The present situation would mean that about 40 to 50% of soil applied herbicides are used on the field where the label instructs "Do not use!". Yet no positive effort has been made for 25 years long by government or companies to develop countermeasures. It is a really sophisticated social problem. In the 1960s and 1970s a subside program to incoporate hillside red clayish soil into sandy paddy as well as campaign for increased application of compost to the field had been operating. Yet majority of the sandy soils remains sandy and the program and campaign had been stopped. With regard to this sandy soil problem the authors have developed a method of "split application of a herbicide onto sandy soil field". A model case study has been carried out with success and is introduced with key procedure in this paper. Climate is variable in its nature. Among the climatic components sudden fall or rise in temperature is hardly avoidable for a crop plant. Our spring air temperature fluctuates so much ; for example, the daily mean air temperature of Inchon city varied from 6.31 to $16.81^{\circ}C$ on April 20, early seeding time of crops, within${\times}$2Sd range of 30 year records. Seeding early in season means an increased liability to phytotoxicity, and this will be more evident in direct water-seeding of rice. About 20% of farmers depend on the cold underground-water pumped for rice irrigation. If the well is deep over 70m, the fresh water may be about $10^{\circ}C$ cold. The water should be warmed to about $20^{\circ}C$ before irrigation. This is not so practiced well by farmers. In addition to the forementioned adverse conditions there exist many other aspects to be amended. Among them the worst for liquid spray type herbicides is almost total lacking in proper knowledge of nozzle types and concern with even spray by the administrative, rural extension officers, company and farmers. Even not available in the market are the nozzles and sprayers appropriate for herbicides spray. Most people perceive all the pesticide sprayers same and concern much with the speed and easiness of spray, not with correct spray. There exist many points to be improved to minimize herbicidal phytotoxicity in Korea and many ways to achieve the goal. First of all it is suggested that 1) the present evaluation of a new herbicide at standard and double doses in registration trials is to be an evaluation for standard, double and triple doses to exploit the response slope in making decision for approval and recommendation of different dose for different situation on label, 2) the government is to recognize the facts and nature of the present problem to correct the present misperceptions and to develop an appropriate national program for improvement of soil conditions, spray equipment, extention manpower and services, 3) the researchers are to enhance researches on the countermeasures and 4) the herbicide makers/dealers are to correct their misperceptions and policy for sales, to develop database on the detailed use conditions of consumer one by one and to serve the consumers with direct counsel based on the database.

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A Study on Commodity Asset Investment Model Based on Machine Learning Technique (기계학습을 활용한 상품자산 투자모델에 관한 연구)

  • Song, Jin Ho;Choi, Heung Sik;Kim, Sun Woong
    • Journal of Intelligence and Information Systems
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    • v.23 no.4
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    • pp.127-146
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    • 2017
  • Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

A Study on the Impact of Artificial Intelligence on Decision Making : Focusing on Human-AI Collaboration and Decision-Maker's Personality Trait (인공지능이 의사결정에 미치는 영향에 관한 연구 : 인간과 인공지능의 협업 및 의사결정자의 성격 특성을 중심으로)

  • Lee, JeongSeon;Suh, Bomil;Kwon, YoungOk
    • Journal of Intelligence and Information Systems
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    • v.27 no.3
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    • pp.231-252
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    • 2021
  • Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.