• 한국균학회소식:학술대회논문집
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• 2016.05a
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• pp.19-20
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• 2016

Sesquiterpenoids are defined as $C_{15}$ compounds derived from farnesyl pyrophosphate (FPP), and their complex structures are found in the tissue of many diverse plants (Degenhardt et al. 2009). FPP's long chain length and additional double bond enables its conversion to a huge range of mono-, di-, and tri-cyclic structures. A number of cyclic sesquiterpenes with alcohol, aldehyde, and ketone derivatives have key biological and medicinal properties (Fraga 1999). Fungi, such as the wood-rotting Polyporus brumalis, are excellent sources of pharmaceutically interesting natural products such as sesquiterpenoids. In this study, we investigated the biosynthesis of P. brumalis sesquiterpenoids on modified medium. Fungal suspensions of 11 white rot species were inoculated in modified medium containing $C_6H_{12}O_6$, $C_4H_{12}N_2O_6$, $KH_2PO_4$, $MgSO_4$, and $CaCl_2$ for 20 days. Cultivation was stopped by solvent extraction via separation of the mycelium. The metabolites were identified as follows: propionic acid (1), mevalonic acid lactone (2), ${\beta}$-eudesmane (3), and ${\beta}$-eudesmol (4), respectively (Figure 1). The main peaks of ${\beta}$-eudesmane and ${\beta}$-eudesmol, which were indicative of sesquiterpene structures, were consistently detected for 5, 7, 12, and 15 days These results demonstrated the existence of terpene metabolism in the mycelium of P. brumalis. Polyporus spp. are known to generate flavor components such as methyl 2,4-dihydroxy-3,6-dimethyl benzoate; 2-hydroxy-4-methoxy-6-methyl benzoic acid; 3-hydroxy-5-methyl phenol; and 3-methoxy-2,5-dimethyl phenol in submerged cultures (Hoffmann and Esser 1978). Drimanes of sesquiterpenes were reported as metabolites from P. arcularius and shown to exhibit antimicrobial activity against Gram-positive bacteria such as Staphylococcus aureus (Fleck et al. 1996). The main metabolites of P. brumalis, ${\beta}$-Eudesmol and ${\beta}$-eudesmane, were categorized as eudesmane-type sesquiterpene structures. The eudesmane skeleton could be biosynthesized from FPP-derived IPP, and approximately 1,000 structures have been identified in plants as essential oils. The biosynthesis of eudesmol from P. brumalis may thus be an important tool for the production of useful natural compounds as presumed from its identified potent bioactivity in plants. Essential oils comprising eudesmane-type sesquiterpenoids have been previously and extensively researched (Wu et al. 2006). ${\beta}$-Eudesmol is a well-known and important eudesmane alcohol with an anticholinergic effect in the vascular endothelium (Tsuneki et al. 2005). Additionally, recent studies demonstrated that ${\beta}$-eudesmol acts as a channel blocker for nicotinic acetylcholine receptors at the neuromuscular junction, and it can inhibit angiogenesis in vitro and in vivo by blocking the mitogen-activated protein kinase (MAPK) signaling pathway (Seo et al. 2011). Variation of nutrients was conducted to determine an optimum condition for the biosynthesis of sesquiterpenes by P. brumalis. Genes encoding terpene synthases, which are crucial to the terpene synthesis pathway, generally respond to environmental factors such as pH, temperature, and available nutrients (Hoffmeister and Keller 2007, Yu and Keller 2005). Calvo et al. described the effect of major nutrients, carbon and nitrogen, on the synthesis of secondary metabolites (Calvo et al. 2002). P. brumalis did not prefer to synthesize sesquiterpenes under all growth conditions. Results of differences in metabolites observed in P. brumalis grown in PDB and modified medium highlighted the potential effect inorganic sources such as $C_4H_{12}N_2O_6$, $KH_2PO_4$, $MgSO_4$, and $CaCl_2$ on sesquiterpene synthesis. ${\beta}$-eudesmol was apparent during cultivation except for when P. brumalis was grown on $MgSO_4$-free medium. These results demonstrated that $MgSO_4$ can specifically control the biosynthesis of ${\beta}$-eudesmol. Magnesium has been reported as a cofactor that binds to sesquiterpene synthase (Agger et al. 2008). Specifically, the $Mg^{2+}$ ions bind to two conserved metal-binding motifs. These metal ions complex to the substrate pyrophosphate, thereby promoting the ionization of the leaving groups of FPP and resulting in the generation of a highly reactive allylic cation. Effect of magnesium source on the sesquiterpene biosynthesis was also identified via analysis of the concentration of total carbohydrates. Our current study offered further insight that fungal sesquiterpene biosynthesis can be controlled by nutrients. To profile the metabolites of P. brumalis, the cultures were extracted based on the growth curve. Despite metabolites produced during mycelia growth, there was difficulty in detecting significant changes in metabolite production, especially those at low concentrations. These compounds may be of interest in understanding their synthetic mechanisms in P. brumalis. The synthesis of terpene compounds began during the growth phase at day 9. Sesquiterpene synthesis occurred after growth was complete. At day 9, drimenol, farnesol, and mevalonic lactone (or mevalonic acid lactone) were identified. Mevalonic acid lactone is the precursor of the mevalonic pathway, and particularly, it is a precursor for a number of biologically important lipids, including cholesterol hormones (Buckley et al. 2002). Farnesol is the precursor of sesquiterpenoids. Drimenol compounds, bi-cyclic-sesquiterpene alcohols, can be synthesized from trans-trans farnesol via cyclization and rearrangement (Polovinka et al. 1994). They have also been identified in the basidiomycota Lentinus lepideus as secondary metabolites. After 12 days in the growth phase, ${\beta}$-elemene caryophyllene, ${\delta}$-cadiene, and eudesmane were detected with ${\beta}$-eudesmol. The data showed the synthesis of sesquiterpene hydrocarbons with bi-cyclic structures. These compounds can be synthesized from FPP by cyclization. Cyclic terpenoids are synthesized through the formation of a carbon skeleton from linear precursors by terpene cyclase, which is followed by chemical modification by oxidation, reduction, methylation, etc. Sesquiterpene cyclase is a key branch-point enzyme that catalyzes the complex intermolecular cyclization of the linear prenyl diphosphate into cyclic hydrocarbons (Toyomasu et al. 2007). After 20 days in stationary phase, the oxygenated structures eudesmol, elemol, and caryophyllene oxide were detected. Thus, after growth, sesquiterpenes were identified. Per these results, we showed that terpene metabolism in wood-rotting fungi occurs in the stationary phase. We also showed that such metabolism can be controlled by magnesium supplementation in the growth medium. In conclusion, we identified P. brumalis as a wood-rotting fungus that can produce sesquiterpenes. To mechanistically understand eudesmane-type sesquiterpene biosynthesis in P. brumalis, further research into the genes regulating the dynamics of such biosynthesis is warranted.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.1
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• pp.67-95
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• 2014

Some Contracting States of the Chicago Convention issue FAOC(Foreign Air Operator Certificate) and conduct various safety assessments for the safety of the foreign operators which operate to their state. These FAOC and safety audits on the foreign operators are being expanded to other parts of the world. While this trend is the strengthening measure of aviation safety resulting in the reduction of aircraft accident. FAOC also burdens the other contracting States to the Chicago Convention due to additional requirements and late permission. EASA(European Aviation Safety Agency) is a body governed by European Basic Regulation. EASA was set up in 2003 and conduct specific regulatory and executive tasks in the field of civil aviation safety and environmental protection. EASA's mission is to promote the highest common standards of safety and environmental protection in civil aviation. The task of the EASA has been expanded from airworthiness to air operations and currently includes the rulemaking and standardization of airworthiness, air crew, air operations, TCO, ATM/ANS safety oversight, aerodromes, etc. According to Implementing Rule, Commission Regulation(EU) No 452/2014, EASA has the mandate to issue safety authorizations to commercial air carriers from outside the EU as from 26 May 2014. Third country operators (TCO) flying to any of the 28 EU Member States and/or to 4 EFTA States (Iceland, Norway, Liechtenstein, Switzerland) must apply to EASA for a so called TCO authorization. EASA will only take over the safety-related part of foreign operator assessment. Operating permits will continue to be issued by the national authorities. A 30-month transition period ensures smooth implementation without interrupting international air operations of foreign air carriers to the EU/EASA. Operators who are currently flying to Europe can continue to do so, but must submit an application for a TCO authorization before 26 November 2014. After the transition period, which lasts until 26 November 2016, a valid TCO authorization will be a mandatory prerequisite, in the absence of which an operating permit cannot be issued by a Member State. The European TCO authorization regime does not differentiate between scheduled and non-scheduled commercial air transport operations in principle. All TCO with commercial air transport need to apply for a TCO authorization. Operators with a potential need of operating to the EU at some time in the near future are advised to apply for a TCO authorization in due course, even when the date of operations is unknown. For all the issue mentioned above, I have studied the function of EASA and EU Regulation including TCO Implementing Rule newly introduced, and suggested some proposals. I hope that this paper is 1) to help preparation of TCO authorization, 2) to help understanding about the international issue, 3) to help the improvement of korean aviation regulations and government organizations, 4) to help compliance with international standards and to contribute to the promotion of aviation safety, in addition.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.163-176
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• 2014

Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Preventive Medicine and Public Health
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• v.30 no.3 s.58
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• pp.630-642
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• 1997

The purpose of this study was to examine the mortality risk associated with cognitive impairment among the rural elderly. The subjective of study was 558 of 'A Study on the Depression and Cognitive Impairment in the Rural Elderly' of Jung Ae Rhee and Hyang Gyun Jung's study(1993). Cognitive impairment and other social and health factors were assessed in 558 elderly rural community residents. For this study, a Korean version of the Mini-Mental State Examination(MMSEK) was used as a global indicator of cognitive functioning. And mortality risk factors for each cognitive impairment subgroup were identified by univariate and multivariate Cox regression analysis. At baseline 22.6% of the sample were mildly impaired and 14.2% were severely impaired. As the age increased, the cognitive function was more impaired. Sexual difference was existed in the cognitive function level. Also the variables such as smoking habits, physical disorders had the significant relationship with cognitive function impairment. Across a 3-year observation period the mortality rate was 8.5% for the cognitively unimpaired, 11.1% for the mildly impaired, and 16.5% for the severly impaired respendents. And the survival probability was .92 for the cognitively unimpaired, .90 for the mildly impaired, and .86 for the severly impaired respondents. Compared to survival curve for the cognitively unimpaired group, each survival curve for the mildly and the severely impaired group was not significantly different. When adjustments models were not made for the effects of other health and social covariates, each hazard ratio of death of mildly and severely impaired persons was not significantly different as compared with the cognitively unimpaired. But, as MMSEK score increased, significantly hazard ratio of death decreased. Employing Cox univariate proportional hazards model, statistically other significant variables were age, monthly income, smoking habits, physical disorders. Also when adjustments were made for the effects of other health and social covariates, there was no difference in hazard ratio of death between those with severe or mild impairment and unimpaired persons. And as MMSEK score increased, significantly hazard ratio of death did not decrease. Employing Cox multivariate proportional hazards model, statistically other significant variables were age, monthly income, physical disorders. Employing Cox multivariate proportional hazards model by sex, at men and women statistically significant variable was only age. For both men and women, also cognitive impairment was not a significant risk factor. Other investigators have found that cognitive impairment is a significant predictor of mortality. But we didn't find that it is a significant predictor of mortality. Even though the conclusions of our study were not related to cognitive impairment and mortality, early detection of impaired cognition and attention to associated health problems could improve the quality of life of these older adults and perhaps extend their survival.

• The Korean Journal of Nuclear Medicine
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• v.36 no.4
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• pp.244-254
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• 2002

Purpose: This study investigated the differences between technetium-99m ethyl cysteinate dimer (Tc-99m ECD) and technetium-99m hexamethylpropylene amine oxime (Tc-99m HMPAO) uptake in the normal brain by means of statistical parametric mapping (SPM) analysis. Materials and Methods: We retrospectively analyzed age and sex matched 53 cases of normal brain SPECT. Thirty-two cases were obtained with Tc-99m ECD and 21 cases with Tc-99m HMPAO. There were no abnormal findings on brain MRIs. All of the SPECT images were spatially transformed to standard space, smoothed and globally normalized. The differences between the Tc-99m ECD and Tc-99m HMPAO SPECT images were statistically analyzed using statistical parametric mapping (SPM'99) software. The differences bgetween the two groups were considered significant ant a threshold of corrected P values less than 0.05. Results: SPM analysis revealed significantly different uptakes of Tc-99m ECD and Tc-99m HMPAO in the normal brains. On the Tc-99m ECD SPECT images, relatively higher uptake was observed in the frontal, parietal and occipital lobes, in the basal ganglia and thalamus, and in the superior region of the cerebellum. On the Tc-99m HMPAO SPECT images, relatively higher uptakes was observed in subcortical areas of the frontal region, temporal lobe, and posterior portion of inferior cerebellum. Conclusion: Uptake of Tc-99m ECD and Tc-99m HMPO in the normallooking brain was significantly different on SPM analysis. The selective use of Tc-99m ECD of Tc-99m HMPAO in brain SPECT imaging appears especially valuable for the interpretation of cerebral perfusion. Further investigation is necessary to determine which tracer is more accurate for diagnosing different clinical conditions.

• The Korean Nurse
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• v.20 no.4 s.112
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• pp.50-59
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• 1981

간호학생들이 당연하고 있는 문제점 미래의 간호학생들이 교육문제를 논하기 위하여는 간호학생들이 가지고 있는 문제점을 파악하고 또 이해하는 것이 우선순위가 될 것이다. 간호학생들이 문제점에 대한 연구는 한국에서 뿐아니라 미국에서도 꽤 많이 시행되어져 왔으며 특히 간호학과정에서 중간 탈락되는 중퇴자들에 대한 연구들 중에 이러한 문제점에 대해서 언급한 것이 많다. 고등학교를 졸업하고 곧 대학과정에 진학한 학생들을 대상으로 조사 보고될 Munro의 자료에 의하면 전문대학과정에서 27$\%$, 대학과정에서는 41$\%$의 간호학생들이 간호학과정에서 중간 탈락하고 있음이 보고되고 있다. 이들이 중간탈락하는 데에는 여러 가지 이유가 있으나 그 중 ''간호학에 흥미를 잃어서''가 가장 큰 이유로 보고되고 있다. 이곳 한국사회에서도 역시 비슷한 현상을 보이고 있다. 그러나 대학입시경쟁과 대학내에서의 전과가 거의 허용되지 않는 특수여건이기 때문에 학교를 중간 탈락하는 율은 미국이 보고만큼 높지는 않으나 역시 ''간호학에 흥미를 잃는다''는 것이 간호학생들의 가장 큰 문제점으로 대두되고 있다. 최근 한국에서 시행된 간호학생들에 관한 연구(표 1 참조)에 의하면 간호학생들의 학문에 대한 만족도는 조사자의 35$\~$50$\%$정도에 불과하였고 더우기 이 비율은 고학년에 올라갈수록 더욱 감소되고 있는 경향을 보이고 있다. 한국에서 시행된 어느 연구보고에 의하면 간호학에 실망했다고 생각하는 학생이 전체의 67$\%$였으며, 다른 학교로 전과를 희망한 경험이 있다는 학생이 71$\%$나 되는 것으로 보고되고 있다. 그러나 왜 흥미를 잃게 되는지 그 이유에 대하여 설명해 주는 연구는 많지 않았다. 미국의 한 저자는 간호학생들이 간호학에 흥미를 잃게 되는 원인을 간호원의 역할에 대한 이해가 정확하지 못한 것과 졸업 후 진로기회에 대한 인식부족 때문이라고 추측하고 있다. 간호학에 흥미를 잃게 되는 이유는 크게 다음의 세 가지로 분류 요약될 수 있다. 첫째, 간호학을 전공으로 택한 동기이다. 간호학의 특수성으로 인하여 학생들이 간호학을 전공으로 택한 동기도 다른 전공분야보다는 훨씬 다른 여러 종류를 보이고 있다. 즉, 종교적 이유, 다른 사람들에게 봉사할 수 있는 직업이기 때문에, 쉽게 취업을 할 수 있어서, 결혼 후에도 직업을 가질 수 있기 때문에, 외국으로 쉽게 취업할 수 있어서 등이 간호학을 선택한 이유로 보고되고 있다. 흥미나 적성에 맞다고 생각하기 때문에 간호학을 택한 학생의 수는 다른 과에 비하여 훨씬 적다. 이러한 흥미나 적성 때문이 아닌 여러 가지 다른 이유들로 인하여 간호학을 택한 경우에 특히 간호학에 쉽게 흥미를 잃어버리는 것을 볼 수 있다. 간호학에 현실적인 개념을 가지고 있는 학생들일수록 추상적이고 현실적인 개념을 가지고 있는 학생들보다 더 간호학에 지속적인 흥미를 가지며 중간에 탈락하는 율이 훨씬 적다는 것이 많은 연구에서 보고되었다. 또한 흥미나 적성 때문에 간호학을 택하였다는 학생들이 다른 과로 전과를 희망하는 율이 낮다는 것도 보고되었다. 둘째, 교과내용자체나 실습에 대한 불만족이다. 간호학에 대한 체계적인 교과내용의 결여, 과중한 과제물, 임상실습에서의 욕구불만, 실습으로 인한 부담, 지식과 실습의 차이점에 대한 갈등 등이 주요 이유로 보고되고 있다. 대부분의 연구들이 이 교과목이나 실습에 대한 불만족, 특히 실습경험에서의 갈등을 학생들이 흥미를 잃는 가장 중요한 요인이 되는 것으로 보고하고 있다. 어느 한 연구에서는 응답자의 90$\%$가 임상실습에 만족하지 못한다고 응답하였으며 그들 중의 88$\%$가 실습감독에 문제가 있다고 생각한다고 보고하였다. 셋째, 교수들에 대한 불만족이다. 대부분의 연구들이 학년이 올라가면 갈수록 교수에 대한 신뢰도가 낮아지며 또한 그에 비례하여 간호학에 대한 만족도가 낮아진다고 보고하고 있다. 교육내용에 대한 전문지식의 결여, 학생들과의 인간적인 관계의 결여, 교수법에 대한 불만족 등이 교수에 대한 불만의 주요내용으로 보고되었다. 미래의 간호에 부응할 학생교육 계속적인 사회적 변동과 더불어 급격하게 변화하고 있는 일반인들의 건강에 대한 요구도와 앞에서 기술한 문제점 등을 감안할 때 학생들에게 동기를 부여하고 간호학에 확신감을 가질 수 있도록 준비시키므로써 간호환경에서 실망하기보다는 오히려 그것을 받아들여 변화하는 사회요구에 책임감을 느낄 수 있도록 교육시키는 것이 미래의 간호학생을 준비시키는데 가장 중요한 요인이라고 할 수 있겠다. 이러한 교육을 위하여 다음의 두가지 안을 제시한다. 1. 교수와 학생간의 관계-서로의 좋은 동반자 : 교수들이 학생에게 미치는 영향, 특히 학생들의 성취도에 대한 영향에 대하여는 이미 많은 연구가 시행되었다. Tetreault(1976)가 간호학생들의 전문의식에 영향을 미치는 요인에 대하여 연구한 바에 의하면 다른 어느 것보다도 교수의 전문의식여부가 학생들의 전문의식 조성에 가장 큰 영향을 미친다고 하였다. 또한 학생들이 교수에게 신뢰감을 가지고 있을때, 교수들이 전문가로서의 행동을 하는 것을 보았을때 비로서 배움이 증가된다고 하였다. Banduras는 엄격하고 무서운 교수보다는 따뜻하고 인간적인 교수에게 학생들이 더 Role Model로서 모방하려는 경향을 나타낸다고 보고 하였다. 그러면 어떻게 학생에게 신뢰받는 교수가 될 수 있겠는가? apos;학생들의 요구에 부응할 때apos;라고 한마디로 표현할 수 있을 것이다. Lussier(1972)가 언급한 것처럼 학생들의 요구에 부응하지 못하는 교육은 Piaget이 언급한 교육의 기본 목표, 즉 개인에게 선배들이 한 것을 그대로 반복하여 시행하도록 하는 것이 아니라 새로운 것을 시도할 수 있는 능력을 가지게 하는 목표에는 도달할 수 없으며 이러한 목표는 간호학에도 가장 기본이 되어야 할 기본목표이기 때문이다. 학생들이 현재 어떤 요구를 가지고 있으며 또 어떤 생각을 하고 있는지 계속 파악하고 있는 것이 학생요구에 부응하는 교육을 할 수 있는 기본조건이 될 것이다. 의외로 많은 교수들이 학생들을 이해하고 있다고 생각하고 있으나 잘못 이해하고 있는 경우가 많다. 표 2는 현 간호학생들이 생각하고 있는 가치관과 문제점을 파악하고 또 교수가 그 가치관과 문제점을 어느 정도 파악하고 있는지 알아보기 위하여 일개 4년제 대학 200여명의 학생과 그 대학에 근무하는 18명의 교수진을 대상으로 질문한 결과를 간략하게 보고한 것이다. 또한 여기에서 학생이 보고하는 가치관, 문제점, 교수에게 바라는 점이 교수가 이해하고 있는 것과 차이가 있다는 것도 보여주고 있다. 우리가 학생들의 요구를 파악할 수 있도록 귀를 기울이고 이해하며, 그 요구에 부응하려고 노력할때 진정한 교수와 학생간의 관계가 이루어질 수 있을 것이며 이때 비로서 우리는 apos;partnershipapos;을 이룰 수 있을 것이다. 이때 간호학에 대한 실망은 줄어들 수 있을 것이며 우리도 학생들에게 전문가적인 태도를 함양시켜줄 수 있는 기회를 부여할 수 있을 것이다. 이렇게 될때 앞으로 기다리고 있는 미지의 의무에 효과적으로 또 적극적으로 대처할 수 있는 자질을 형성한 학생들을 준비해 낼 수 있을 것이다. 2. 간호모델에 의한 교과과정의 확립과 임상실습에의 적용 : 교과과정이 학생들의 모양을 만들어주는 하나의 기본틀이라고 말할 수 있다면 미래의 요구에 부응하는 학생들을 준비시키기 위하여 지금까지와는 다른 새로운 방향의 교과과정이 필요하다는 것은 재론할 필요가 없을 것이다. 이미 진취적인 간호대학에서는 guided design systems approach 또는 integrated curriculum 등의 새로운 교과과정을 시도하고 있음은 알려진 사실이다. 물론 간호모델에 준한 교과과정을 발전시키는데 대한 장점과 이에 수반되는 여러가지 새로운 문제점에 대하여 많은 논란이 있으나 모든 교과과정이 처음 시도될 때부터 완전한 것이 있을 수 없으며 시간이 지남에 따라 성숙되는 것임을 감안해 볼 때 이러한 새로운 교과과정에의 시도는 미래의 새로운 간호방향에 필수적인 사업이라고 하겠다. 이러한 교과과정을 개발하는데 몇가지 게안점을 첨부하려 한다. (1) 새로운 교과과정의 개발은 처음부터 끝까지 모든 교수진의 협력과 참여로 이루어져야 한다. (2) 비록 처음에는 어렵고 혼란이 있더라도 교과과정은 의학모델이 아닌 간호모델을 중심으로 이루어져야 한다. (3) 간호모델에서 다루어지는 개념들은 모두 직접 간호업무에 적용될 수 있는 것으로 선택되어야 한다. (4) 교과과정의 결과로 배출되는 학생들의 준비정도는 그 지역사회에 적합하여야 한다. (5) 그 지역사회의 고유한 문화적 요소가 포함되어야 한다. 아직 우리는 간호분야 내부의 갈등을 해결하지 못하고 있는 시기에 있다. 우리 내부의 문제점을 잘 해결할 수 있을때 외부와의 갈등에 잘 대처할 수 있을 것이다. 내부의 갈등을 잘 해결하기 위한 힘을 모으기 위하여는 동반자, 즉 교수와 학생, 간호교육자와 임상간호원 등이 서로 진정한 의미의 동반자 될때 가장 중요한 해결의 실마리가 될 것이다.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.