• Journal of English Language & Literature
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• v.58 no.6
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• pp.1143-1165
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• 2012

Tinted with ontological concern, Ted Hughes passes through an existential climate, eventually confirms death( or nothingness) as the new foundation of his poetry, and explores the various paradoxical effects of nothingness. Nihilism, fraught with rather negative and traumatic themes such as death, melancholy, and despair can, however, generate being (even in multiple modes), animalistic vitality, and insubstantial specters. Among these new functions of nothingness animality and spectrality are the most notable in Hughes's poetry. A considerable number of animals and bioorganisms that Hughes introduces exhibit the enormous energy derived from the dignity of death, from subversive challenges against the established hierarchy, and from new and dynamic multifaceted sources of nothingness. In other words, Hughes's animals, yield surplus power beyond themselves, as if they are demi-gods; in short, they feature the sublime as unidentified terrifying effects of nothingness. In a sense, animality means allowing some level of violence without legal sanction. Hughes inaugurates this kind of all bigotry-eradicating violence and attempts to subvert higher beings such as humans and gods, and existing doctrines: thrushes rise up against the animal and human worlds; a rush of ghostly crabs at night press through the human world. Hughes also resists the highest being, God, employing the technique of rewriting God's theology. Dirty, anomalous crows attack, subvert, and dismember the delicate, indurate, and thorough system of logos. Hughes, of course, does not place the animals merely in lofty regard, aware of the ulterior deprivation of the sublime animality, the trace of existential negativity. Thus, a seemingly omnipotent crow can become a mere beggar guzzling ice cream from the garbage bin on the beach. In addition, the violent and dignified aspects of nothingness can be transformed to reveal the thin and trivial traits as unreliable specters. Dark, heavy, and terrible nullity lessens its own volume and mass, and exposes the airy waves of shadows or specters. However, owing to nullity's untraceable track, the scarcity and unfamiliarity of the phantoms inversely display their foreign gigantic effects such as fantasy and violence.

• Earthquakes and Structures
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• v.26 no.4
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• pp.311-326
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• 2024

Transmission tower structures are particularly susceptible to damage and even collapse under strong seismic ground motions. Conventional seismic analyses of transmission towers are usually performed by considering only ground motion uncertainty while ignoring structural uncertainty; consequently, the performance evaluation and failure prediction may be inaccurate. In this context, the present study numerically investigates the seismic responses and failure mechanism of transmission towers by considering multiple sources of uncertainty. To this end, an existing transmission tower is chosen, and the corresponding three-dimensional finite element model is created in ABAQUS software. Sensitivity analysis is carried out to identify the relative importance of the uncertain parameters in the seismic responses of transmission towers. The numerical results indicate that the impacts of the structural damping ratio, elastic modulus and yield strength on the seismic responses of the transmission tower are relatively large. Subsequently, a set of 20 uncertainty models are established based on random samples of various parameter combinations generated by the Latin hypercube sampling (LHS) method. An uncertainty analysis is performed for these uncertainty models to clarify the impacts of uncertain structural factors on the seismic responses and failure mechanism (ultimate bearing capacity and failure path). The numerical results show that structural uncertainty has a significant influence on the seismic responses and failure mechanism of transmission towers; different possible failure paths exist for the uncertainty models, whereas only one exists for the deterministic model, and the ultimate bearing capacity of transmission towers is more sensitive to the variation in material parameters than that in geometrical parameters. This research is expected to provide an in-depth understanding of the influence of structural uncertainty on the seismic demand assessment of transmission towers.

• Journal of Environmental Impact Assessment
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• v.28 no.6
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• pp.556-567
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• 2019

As the number of skyscrapers in micro water grid units such as green building and smart building is increasing in the world, the green building certification system is being implemented to solve problems such as increased demand for water resources and energy. However, researches on the use of sustainable water resources like water reuse and water conservation through linkage and continuous use of water resources, while the power and energy sectors are actively conducting R&D projects in the green building certification system on the micro water grid level. Therefore, this paper analyzes the characteristics and limitations of the water resources sector for the continuous utilization of multiple water sources in the green building certification system, due to the inadequate consideration of sustainability. Then investigates whether various water resources such as constants, nature, and alternative water resources are continuously used in and out of the green building or smart building and complex in the micro water grid unit to suggest evaluation methods and performance evaluation standards.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.19-26
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• 2023

Humans have adapted and evolved to natural light. However, as humans stay in indoor longer in modern times, the problem of biorhythm disturbance has been induced. To solve this problem, research is being conducted on lighting that reproduces the correlated color temperature(CCT) of natural light that varies from sunrise to sunset. In order to reproduce the CCT of natural light, multiple LED light sources with different CCTs are used to produce lighting, and then a control index DB is constructed by measuring and collecting the light characteristics of the combination of input currents for each light source in hundreds to thousands of steps, and then using it to control the lighting through the light characteristic matching method. The problem with this control method is that the more detailed the steps of the combination of input currents, the more time and economic costs are incurred. In this paper, an LED lighting control method that applies interpolation and combination calculation based on the minimum spectral power distribution information for each light source is proposed to reproduce the CCT of natural light. First, five minimum SPD information for each channel was measured and collected for the LED lighting, which consisted of light source channels with different CCTs and implemented input current control function of a 256-steps for each channel. Interpolation calculation was performed to generate SPD of 256 steps for each channel for the minimum SPD information, and SPD for all control combinations of LED lighting was generated through combination calculation of SPD for each channel. Illuminance and CCT were calculated through the generated SPD, a control index DB was constructed, and the CCT of natural light was reproduced through a matching technique. In the performance evaluation, the CCT for natural light was provided within the range of an average error rate of 0.18% while meeting the recommended indoor illumination standard.

• Ocean and Polar Research
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• v.42 no.3
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• pp.195-210
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• 2020

The observed time series from the Korea Ocean Research Stations (KORS) in the Yellow and East China Seas (YECS) have various sources of noise, including bio-fouling on the underwater sensors, intermittent depletion of power, cable leakage, and interference between the sensors' signals. Besides these technical issues, intricate waves associated with background tidal currents tend to result in substantial oscillations in oceanic time series. Such technical and environmental issues require a regionally optimized automatic quality control (QC) procedure. Before the achievement of this ultimate goal, we examined the approach of the Ocean Observatories Initiative (OOI)'s standard QC to investigate whether this procedure is pertinent to the KORS. The OOI QC consists of three categorized tests of global/local range of data, temporal variation including spike and gradient, and sensor-related issues associated with its stuck and drift. These OOI QC algorithms have been applied to the water temperature time series from the Ieodo station, one of the KORS. Obvious outliers are flagged successfully by the global/local range checks and the spike check. Both stuck and drift checks barely detected sensor-related errors, owing to frequent sensor cleaning and maintenance. The gradient check, however, fails to flag the remained outliers that tend to stick together closely, as well as often tend to mark probably good data as wrong data, especially data characterized by considerable fluctuations near the thermocline. These results suggest that the gradient check might not be relevant to observations involving considerable natural fluctuations as well as technical issues. Our study highlights the necessity of a new algorithm such as a standard deviation-based outlier check using multiple moving windows to replace the gradient check and an additional algorithm of an inter-consistency check with a related variable to build a standard QC procedure for the KORS.

• Korean Journal of Community Nutrition
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• v.21 no.3
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• pp.284-292
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• 2016

Objectives: This study compared the differences of postmenopausal women's bone mineral density in relation to the degree of obesity, metabolism index and dietary factors that affect bone mineral density. Methods: The subjects included in the study are 39 postmenopausal women of normal weight with body mass index less than $25kg/m^2$ and 32 postmenopausal who are obese. Anthropometry and biochemical analysis were performed and nutrient intakes and DQI-I were assessed. Results: Normal weight women were $56.03{\pm}3.76years$ old and obese women were $58.09{\pm}5.13years$ old and there was no significant difference in age between the two groups. The T-score of bone mineral density was $0.03{\pm}1.06$ in normal weight women and $-0.60{\pm}1.47$ in obese women and this was significantly different between the two groups (p<0.05). Blood Leptin concentration was significantly lower in normal weight women ($6.09{\pm}3.37ng/mL$) compared to obese women in ($9.01{\pm}4.99ng/mL$) (p<0.05). The total score of diet quality index-international was $70.41{\pm}9.34$ in normal weight women and $64.93{\pm}7.82$ in obese women (p<0.05). T-score of bone mineral density showed negative correlations with percentage of body fat (r = -0.233, p=0.05), BMI (r = -0.197, p=0.017), triglyceride (r = -0.281, p=0.020) and leptin (r = -0.308, p=0.011). The results of multiple regression analysis performed as the method of entry showed that with 22.0% of explanation power, percentage of body fat (${\beta}=-0.048$, p<0.05), triglyceride (${\beta}=-0.005$, p<0.05) and HDL-cholesterol (${\beta}=0.034$, p<0.01), moderation of DQI-I (${\beta}=-0.231$, p<0.05) affected T-score significantly. Conclusions: The results of the study showed that obese women have less bone density than those with normal weight women. In addition, the factor analysis result that affect bone mineral density showed that intake of fat is a very important factor. Therefore, postmenopausal women need to maintain normal weight and manage blood lipid levels within normal range. They also need to take various sources of protein and reduce consumption of empty calorie foods that have high calories, fat, cholesterol and sodium.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.298-298
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• 2013

Finding renewable and clean energy resources is essential research to solve global warming and depletion of fossil fuels in modern society. Recently, complex harvesting of energy from multiple sources is available in our living environments using a single device has become highly desirable, representing a new trend in energy technologies. We report that when simultaneously driving the fusion and composite cells of two or more types, it is possible to make an affect the other cells to obtain a greater synergistic effect. To understand the coupling effect of photovoltaic and piezoelectric device, we fabricate the serially integrated hybrid cell (s-HC) based on organic solar cell (OSC) and piezoelectric nanogenerator (PNG). The size of increased voltage peaks when OSC and PNG are working on is larger than the case when only PNG is working. This voltage difference is the Voc change of OSC, not the voltage change of PNG and current density difference between these two cases is manifested more clearly. When the OSC and PNG are working in s-HC at the same time, piezoelectric potential (VPNG) is generated in ZnO and theoretical total voltage is sum of voltage of an OSC (VOSC) and VPNG. However, electrons from OSC are influenced by piezoelectric potential in ZnO and current loss of OSC in whole circuit decreases. As a result, VOSC increases temporarily. Current shows the similar behavior. PNG acts a resistance in the whole circuit and current loss occurs when the electrons from OSC pass through the PNG. But piezoelectric potential recover current loss and decrease the resistance of PNG. Our PNG can maintain piezoelectric potential when the strain is held owing to the LDH layer while general PNG cannot maintain piezoelectric potential. During the section that strain is held, voltage enhancement effect is maintained and same effect appeared even turn off the light. Actually at this time, electrons in ZnO nanosheets move to LDH and trapped by the positive charges in this layer. After this strain is held, piezoelectric potential of ZnO nanosheets is disappeared but potential difference which is developed by negative charge dominant LDH layer is remained. This potential acts similar role like piezoelectric potential in ZnO. Electrons from the OSC also are influenced by this potential and the more current flows.

• Analyses & Alternatives
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• v.7 no.2
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• pp.35-77
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• 2023

This study aims to solve the entangled loop between demographic transition (DT) and economic growth by analyzing cross-country data. We undertake a national-level group analysis to verify the compressed transition of demographic variables over time. Assuming that the LA (latecomer advantage) on DT over time exists, we verify that the DT of the latecomer is compressed by providing a formal proof of LA on DT over income. As a DT has the double-kinked functions of income, we check them in multiple aspects: early maturation, leftward threshold, and steeper descent under a contour map and econometric methods. We find that the developing countries (the latecomer) have speedy DT (CDT, compressed DT) as well as speedy income such that DT of the latecomers starts at lower levels of income, lasts for a shorter period, and finishes at the earlier stage of economic development compared to that of developed countries (the early mover). To check the balance of DT, we classify countries into four groups of DT---balanced, slow, unilateral, and rapid transition countries. We identify that the main causes of rapid transition are due to the strong family planning programs of the government. Finally, we check the effect of latecomer's CDT on economic growth inversely: we undertake the simulation of the CDT effect on economic growth and the aging process for the latecomer. A worrying result is that the CDT of the latecomer shows a sharp upturn of the working-age population, followed by a sharp downturn in a short period. Compared to early-mover countries, the latecomer countries cannot buy more time to accommodate the workable population for the period of demographic bonus and prepare their aging societies for demographic onus. Thus, we conclude that CDT is not necessarily advantageous to developing countries. These outcomes of the latecomer's CDT can be re-interpreted as follows. Developing countries need power sources to pump up economic development, such as the following production factors: labor, physical and financial capital, and economic systems. As for labor, the properties of early maturation and leftward thresholds on DTs of the latecomer mean that demographic movement occurs at an unusually early stage of economic development; this is similar to a plane that leaks fuel before or just before take-off, with the result that it no longer flies higher or farther. What is worse, the property of steeper descent represents the falling speed of a plane so that it cannot be sustained at higher levels, and then plummets to all-time lows.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.