This research alms at quantifying economic impacts of free trading policy on environment-friendly fuel industry applying a static general equilibrium (CGE) model for Korea. Theoretically, 'polluters haven' hypothesis had been debated as major issue on the environmental effects of trade liberalization during 1970s and 1980s but recent literature emphasizes that production, scale, structural, and regulatory effects may derive rapid diffusion of environment friendly technologies. In this study, trade liberalization policy affects output of agricultural sectors negatively while that of biodiesel as environment-friendly technology positively. The rise m the output of biodiesel is derived from the reduction in import prices of agricultural products due to the abolishment of tariff. The policy implication from the analysis is that feedstock for producing biodiesel should be exploited in the foreign countries where productivity of agriculture is quite predominant compared to Korean agriculture.
Proceedings of the Korean Institute of Intelligent Systems Conference
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1998.03a
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pp.123-126
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1998
The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the Meaning of these foundational concepts, simple genetic algorithm(SGA) allocate more trials to the schemata whose average fitness remains above average. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve in contrast with traditional single population evolutionary algorithms. In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. So we propose a co-evolutionary method finding optimal fuzzy rules. Our algorithm is that after constructing two population groups m de up of rule vase and its schema, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the proposed method to a path planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.
Purpose: Generally, patients with stroke present with decreased balance and increased spasticity following weakness of the paralyzed muscles. Muscle weakness caused by stroke has two causes. This is caused by a decrease in motor output and an adaptive muscle change, resulting in muscle weakness and muscle paralysis. The purpose of this study was to investigate the effect of strengthening exercise on balance and spasticity in chronic stroke patients and to suggest the basis of clinical treatment. Methods: Twenty subjects were divided into two groups: a lower-extremity strengthening group (experimental group) and a general physical therapy group (control group). The sliding stander equipment was used for the experimental group and a regimen of warm-up exercise, the main exercise routine, and cool-down exercise were used for the muscle strengthening exercise program. Balance and spasticity were measured before and after the training period. Balance ability was measured by the Berg balance scale, the Timed up and Go test and the weight distribution of the paralyzed muscles by the Spacebalance 3D. Spasticity was measured by the Biodex system. Results: After the training periods, the experimental group showed a significant improvement in BBS, weight distribution of the paralyzed muscles, and decreased spasticity when compared to the control group (p<0.05). Conclusion: This study supported the hypothesis that lower-extremity strengthening exercise improves the balance and decreases the spasticity of stroke patients. If it is combined with conventional neurologic physiotherapy, it would be effective rehabilitation for stroke patients.
This paper analyzes the effects of nuclear power generation on industrial growth in using the data of 22 manufacturing sectors in 14 nuclear power countries. The hypothesis that the change in the proportion of nuclear power generation in total electricity generation affects industrial value-added and industrial output through industrial electricity price reduction was tested using the dynamic panel data model. First, it was estimated that the increase in nuclear power generation by a 1% leads to a 0.8% reduction in electricity price. The results indicate that when nuclear power generation increased by a 1% point, industrial value-added and output increased by 0.16% and 0.23%,respectively, in the short-run and by 0.51% and 0.85%, respectively, in the long-run. It was also inferred that the effect of nuclear generation on industrial competitiveness working through electricity price reduction rely on institutional settings in the electricity markets. That is, the competitive effect is greater in the countries such as U.K and Japan where electricity price is high and price volatility is large. Meanwhile, in Germany which has pursued phasing out nuclear power, industrial competitiveness is promoted through stable electricity supply.
Cancer causes many crises to cancer patients imcluding physical dysfunction and emotional changes such as anxiety, depression as well as a threat of life, fear of death. As it develops, cancer makes people feel powerlessness due to the losses of their own positions, roles and independence. Although occupying a little proportion among all types of cancer, head and neck cancer may cause a wide range of physical transformation by surgical operation, damage to active functions such as eating and speaking, provoke anxiety and depression after its operation, influencing the quality life of head and neck cancer patients. Thus nursing intervention should be developed to provide supportive nursing for head and neck cancer patients and play roles as competent supporters. This study is a nonequivalent, control group, pretest-posttest, non-synchronized quasi-experimental research design to determine, how nursing intervention has effects on anxiety, depressing of head and neck cancer and operated. They were divided into experimental and comparison groups, each consisting of 20 members. The data were collected during the period from December 1, 1999 to April 11, 2000. Tools of the study included the protocol of supportive nursing intervention which was developed by researcher with reference to a literal review and esperts' advice. The measurement tool of anxiety was consisting of totaled 20 question items which was prepared by Spielberger and translated by Kim et al., the device of depression measurement consisting of total 20 question items which was the output of Song's translation the device of depression self-evaluation from Zung. Data were analyzed using the SPSS/PC 9.0 program. The homogeneity of the subjects were tested using x2-test and t-test. 5 hypoteses were tested using t-test. The results of the study can be summarized as follows. 1.The first hypothesis that the experimental group receiving supportive nursing intervention shows a little anxiety than the control group not receiving supportive nursing intervention was supported(t=3.817, P=.000). 2.The second hypothesis that the experimental group receiving supportive nursing intervention shows a little depression than the control group not receiving supportive nursing intervention was supported(t=8.089, P=.000). Consequently, supportive nursing intervention was found an effective nursing intervention strategy to reduce anxiety and depression of head and neck cancer patients. Providing supportive nursing intervention in nursing practice can enhance the quality of life of those cancer patients.
Output prices tend to respond faster to input price increases than to decreases. The 'rockets and feathers' hypothesis of asymmetric price behavior in petroleum market is tested by a full adjustment error correction model. Using monthly data for the period January 1977 to June 2006, evidence is found that there is a significant degree of asymmetry in the adjustment of wholesale prices to increases and to decreases in crude oil price. A similar hypothesis in regard to the exchange rate is also rejected by the data. Using weekly data over the period examined, evidence of asymmetry for gasoline, diesel and heating oil is also found in the transmission of price changes from wholesale to retail: retail prices increase more quickly in response to the wholesale price increases than to wholesale price decreases.
The hypothesis tested is that shifts in pH, induced when a cardioplegic solution is oxygenated, can be detrimental. The object of this study is to evaluate the effect of the pH of the oxygenating cardioplegic solution on postischemic recovery in the isolated rat heart. Either 100% oxygen or 95% oxygen: 5% carbon dioxide was added to the cardioplegic solution[St. Thomas` Hospital No. 2] and determined postischemic recovery of isolated rat hearts after 2 hours and 3 hours of 20oC cardioplegic protected ischemia. Heart were arrested and reinfused every 30 minutes throughout the ischemic period with cardioplegic solution. When 100% oxygen was added, the pH of the cardioplegic solution increased from 7.8[no oxygen] to 8.5[100% oxygen] without any change in postischemic functional recovery. But when 95% oxygen ; 5% carbon dioxide was added, the pH of the cardioplegic solution reversely decreased to 6.84 in the 2-hour ischemic group and 6.73 in the 3-hour ischemic group, associated with improved postischemic functional recovery. After 2-hour ischemia, systolic pressure improved from 88.2$\pm$3.7%[no oxygen] and 88.7$\pm$3.8%[100% oxygen] to 96.6$\pm$1.8%[95% oxygen : 5% carbon dioxide], p<0.05, aortic flow from 43.3$\pm$3.1% and 38.4$\pm$10.6% to 74.5$\pm$5.0%, p<0.001, cardiac output from 55.5$\pm$4.6% and 47.4%$\pm$10.6% to 73.1$\pm$4.6%, p<0.05, stroke volume from 62.7$\pm$4.6% and 52.0$\pm$10.1% to 77.2$\pm$4.6%, p<0.05, and dP/dT from 59.3$\pm$7.2% and 56.7$\pm$7.6% to 78.9$\pm$4.6%, p<0.05. The infused amount of the cardioplegic solution during 2-hour ischemic period was similar in three groups. After 3-hour ischemia, cardiac output improved from 17.0$\pm$3.8%[no oxygen] to 45.9$\pm$7.5%[95% oxygen: 5% carbon dioxide], p<0.05, and stroke volume from 21.0$\pm$3.9%[no oxygen] to 50.1$\pm$6.6%[95% oxygen: 5% carbon dioxide], p<0.01. In conclusion, the St. Thomas` Hospital No. 2 cardioplegic solution should be oxygenated but with 95% oxygen: 5% carbon dioxide and not 100% oxygen because of the additive effect of a relatively "Acidotic" pH.t; pH.
Nawaz, Javeria;Arshad, Muhammad Zeeshan;Park, Jin-Su;Shin, Sung-Won;Hong, Sang-Jeen
Proceedings of the Korean Vacuum Society Conference
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2012.02a
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pp.239-240
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2012
With advancements in semiconductor device technologies, manufacturing processes are getting more complex and it became more difficult to maintain tighter process control. As the number of processing step increased for fabricating complex chip structure, potential fault inducing factors are prevail and their allowable margins are continuously reduced. Therefore, one of the key to success in semiconductor manufacturing is highly accurate and fast fault detection and classification at each stage to reduce any undesired variation and identify the cause of the fault. Sensors in the equipment are used to monitor the state of the process. The idea is that whenever there is a fault in the process, it appears as some variation in the output from any of the sensors monitoring the process. These sensors may refer to information about pressure, RF power or gas flow and etc. in the equipment. By relating the data from these sensors to the process condition, any abnormality in the process can be identified, but it still holds some degree of certainty. Our hypothesis in this research is to capture the features of equipment condition data from healthy process library. We can use the health data as a reference for upcoming processes and this is made possible by mathematically modeling of the acquired data. In this work we demonstrate the use of recurrent neural network (RNN) has been used. RNN is a dynamic neural network that makes the output as a function of previous inputs. In our case we have etch equipment tool set data, consisting of 22 parameters and 9 runs. This data was first synchronized using the Dynamic Time Warping (DTW) algorithm. The synchronized data from the sensors in the form of time series is then provided to RNN which trains and restructures itself according to the input and then predicts a value, one step ahead in time, which depends on the past values of data. Eight runs of process data were used to train the network, while in order to check the performance of the network, one run was used as a test input. Next, a mean squared error based probability generating function was used to assign probability of fault in each parameter by comparing the predicted and actual values of the data. In the future we will make use of the Bayesian Networks to classify the detected faults. Bayesian Networks use directed acyclic graphs that relate different parameters through their conditional dependencies in order to find inference among them. The relationships between parameters from the data will be used to generate the structure of Bayesian Network and then posterior probability of different faults will be calculated using inference algorithms.
The purpose of this paper is to estimate the impact of foreign direct investment on environmental performance for 27 OECD countries using endogenous environmental policy model. The empirical test shows that with 1% increase in the ratio of inflow stock of foreign direct investment over domestic capital stock, emission on NOx and $CO_2$ will increase by 0.0071%(NOx) and 0.0165%($CO_2$) and 1% increase in the ratio of foreign capital stock induces 0.044%(fixed effect) and 0.047%(random effect) of economic growth. 1% increase of per labor total output increases 2.038%(fixed effect) or 1.890%(random effect) in reinforcement of environmental regulation. However, we could not confirm the Porter's hypothesis that the more strong environmental regulation leads technical innovation. The scale effects (0.0119, 0.0172) are estimated higher than the technical effects (-0.0048, -0.0007) in two pollutants (NOx, $CO_2$). It implies that each country needs to increase pollution abatement and control expenditure more aggressively to protect environment.
It was assumed that the maternal identity in primi-gravida is one of the most attribute of the motherhood, that is not biological but cognitive phenomena, appears active process as intelligent human being. The purposes of this study were that the identification the cognitive structure and the influencing factors of the maternal identity in primi-gravida. Theoretical framework in this study, maternal identity in primi-gravida was constructed as a cognitive output, has the cognitive structure of cognitive-perceptual factor, cognitive-behavioral factor, and cognitive-emotional factor. Influencing factors of maternal identity was constructed as a cognitive input, which were pregnancy related perceptions (pregnancy intention, minor discomfort, value of motherhood), interpersonal relationship(relationship with mother, relationship with husband, relationship with social network), preparation to motherhood(maternal knowledge, antenatal self care), and biological factor (gestation period). This study was the descriptive correlational research design, was done from the 3rd January to the 15th March 1996, and the research subjects were selected conviniently 226 the primi-gravida during the gestation period, data collection method was self reported questionnaire cross-sectionally. Descriptive data analysis was done by SAS PC$^{+}$, testing the hypothetical model was done by covariance structural analysis using LISREL 8.03 program. The result of the hypothesis testing, the value of motherhood(y=.650, T=4.26) the maternal knowledge (y=.137, T=2.030), the gestation period( y=.113, T=2.621), showed significant causal effect on the maternal identity in primi-gravida. In conclusion, the maternal identity in primi-gravida had interrelated cognitive structure consist of perceptual, behavioral, and emotional factors. Significant causal factors influencing the maternal identity were value identified. It seems to contribute toward the understanding the characteristics of the maternal identity as a cognitive domains that has been regarded highly abstract concept, so has not been validated empirically.y.
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