The brightness temperature from NOAA AVHRR CH 4 images was examined for the metropolitan Seoul area, the capital city of Korea, to detect the characteristics of the urban heat island for this study. Surface data from 21 meteorological stations were compared with the brightness temperatures Through computer enhancement techniques, more than 20 heat islands could be recognized in South Korea, with 1 km spatii resolution at a scale of 1: 200, 00O(Fig. 3, 4 and 6). The result of the analysis of AVHRR CH 4 images over the metropolitan Seoul area can be summerized as follows (1) The pattern of brightness temperature distribution in the metropolitan Seoul area shows a relatively strong temperature contrast between urban and rural areas. There is some indication of the warm brightness temperature zone characterrizing built-up area including CBD, densely populated residential district and industrial zone. The cool brightness temperature is asociaed with the major hills such as Bukhan-san, Nam-san and Kwanak-san or with the major water bodies such as Han-gang, and reservoirs. Although the influence of the river and reservoirs is obvious in the brightness temperauture, that of small-scaled land use features such as parks in the cities is not features such as parks in the cities is not apperent. (2) One can find a linerar relationshop between the brightenss temperature and air temperature for 10 major cities, where the difference between two variables is larger in big cities. Though the coefficient value is 0.82, one can estimate that factors of the heat islands can not be explained only by the size of the cities. The magnitude of the horizontal brightness temperature differences between urban and rural area is found to be greater than that of horizontal air temperature difference in Korea. (3) Also one can find the high heat island intensity in some smaller cities such as Changwon(won(Tu-r=9.0$^{\circ}$C) and Po-hang(Tu-r==7.1$^{\circ}$~)T. he industrial location quotient of Chang-won is the second in the country and Po-hang the third. (4) A comparision of the enhanced thermal infrared imageries in 1986 and 1989, with the map at a scale of 1:200, 000 for the meotropolitan Seoul area showes the extent of possible urbanization changes. In the last three years, the heat islands have been extended in area. zone characterrizing built-up area including (5) Although the overall data base is small, the data in Fig. 3 suggest that brightness tempeautre could ge utilized for the study on the heat island characteristics. Satellite observations are required to study and monitor the impact of urban heat island on the climate and environment on global scale. This type of remote sensing provides a meams of monitoring the growth of urban and suburban aeas and its impact on the environment.
Purpose: The purpose of this study was to analyze the influence of palatal height on Korean vowels and speech intelligibility in Korean adults and to produce baseline data for future prosthodontic treatment. Material and methods: Forty one healthy Korean men and women who had no problem in pronunciation, hearing, and communication and had no history of airway disease participated in this study. Subjects were classified into H, M, and L groups after clinical determination of palatal height with study casts. Seven Korean vowels were used as sample vowels and subjects'clear speech sounds were recorded using Multispeech software program on computer. The F1 and the F2 of 3 groups were produced and they were compared. In addition, the vowel working spaces of 3 groups by /a/, /i/, and /u/ corner vowels were obtained and their areas were compared. Kruskal-Wallis test and Mann-Whiteny U test were used as statistical methods and P < .05 was considered statistically significant. Results: There were no significant differences in formant frequencies among 3 groups except for the F2 formant frequency between H and L group (P = .003). In the analysis of vowel working space areas of 3 groups, the vowel working spaces of 3 groups were similar in shape and no significant differences of their areas were found. Conclusion: The palatal height did not affect vowel frequencies in most of the vowels and speech intelligibility. The dynamics of tongue activity seems to compensate the morphological difference.
This study was expected to yield the meaningful conclusions from the experimental group who took lessons based on inductive activities using GeoGebra at the beginning of proof learning and the comparison one who took traditional expository lessons based on deductive activities. The purpose of this study is to give some helpful suggestions for teaching proof to mathematically gifted elementary students. To attain the purpose, two research questions are established as follows. 1. Is there a significant difference in proof abilities between the experimental group who took inductive lessons using GeoGebra and comparison one who took traditional expository lessons? 2. Is there a significant difference in proof attitudes between the experimental group who took inductive lessons using GeoGebra and comparison one who took traditional expository lessons? To solve the above two research questions, they were divided into two groups, an experimental group of 10 students and a comparison group of 10 students, considering the results of gift and aptitude test, and the computer literacy among 20 elementary students that took lessons at some education institute for the gifted students located in K province after being selected in the mathematics. Special lesson based on the researcher's own lesson plan was treated to the experimental group while explanation-centered class based on the usual 8th grader's textbook was put into the comparison one. Four kinds of tests were used such as previous proof ability test, previous proof attitude test, subsequent proof ability test, and subsequent proof attitude test. One questionnaire survey was used only for experimental group. In the case of attitude toward proof test, the score of questions was calculated by 5-point Likert scale, and in the case of proof ability test was calculated by proper rating standard. The analysis of materials were performed with t-test using the SPSS V.18 statistical program. The following results have been drawn. First, experimental group who took proof lessons of inductive activities using GeoGebra as precedent activity before proving had better achievement in proof ability than the comparison group who took traditional proof lessons. Second, experimental group who took proof lessons of inductive activities using GeoGebra as precedent activity before proving had better achievement in the belief and attitude toward proof than the comparison group who took traditional proof lessons. Third, the survey about 'the effect of inductive activities using GeoGebra on the proof' shows that 100% of the students said that the activities were helpful for proof learning and that 60% of the reasons were 'because GeoGebra can help verify processes visually'. That means it gives positive effects on proof learning that students research constant character and make proposition by themselves justifying assumption and conclusion by changing figures through the function of estimation and drag in investigative software GeoGebra. In conclusion, this study may provide helpful suggestions in improving geometry education, through leading students to learn positive and active proof, connecting the learning processes such as induction based on activity using GeoGebra, simple deduction from induction(i.e. creating a proposition to distinguish between assumptions and conclusions), and formal deduction(i.e. proving).
Virtual reality that we have seen from the movies in 80's and 90's is hawing near based on the rapid progress of science together with a computer technology. Various virtual reality system developments (such as VRML, HMD FishTank, Wall Type, CAVE Type, and so on) and the advancement of those systems make for the embodiment of virtual reality that gives more sense of the real. Virtual reality is so immersive that makes people feel like they are in that environment and enable them to manipulate without experiencing the environment at first hand that is hard to experience in reality. Virtual reality can be applied to the spheres, such as education, high-level programming, remote control, surface exploration of the remote satellite, analysis of exploration data, scientific visualization, and so on. For some connote examples, there are training of a tank and an aeroplane operation, fumiture layout design, surgical operation practice, game, and so on. In these virtual reality systems, the actual operation of the human participant and virtual workspace are connected each other to the hardware that stimulates the five senses adequately to lend the sense of the immersion. There are still long way to go, however, before long it will be possible to have the same feeling in the virtual reality as human being can have by further study and effort. In this thesis, the basic definition, the general idea, and the kind of virtual reality were discussed. Especially, CAVE typed in reality that is highly immersive was analyzed in definition, and then the method of VR programming and modeling in the virtual reality system were suggested by showing the restoration process of Kyongbok Palace (as the content of the original form of the culture) that was made by KISTI(Korea Institute of Science and Technology Information) in 2003 through design process in virtual reality system. Through these processes, utilization of the immersive virtual reality system was discussed and how to take advantage of this CAVE typed virtual reality system at the moment was studied. In closing the problems that had been exposed in the process of the restoration of the cultural property were described and the utilization plan of the virtual reality system was suggested.
Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.
With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.
Kim, Bo-Hye;Choi, Kyoung-Kyu;Park, Sang-Hyuk;Choi, Gi-Woon
Restorative Dentistry and Endodontics
/
v.35
no.2
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pp.88-95
/
2010
The purpose of this study was to compare the root canal shaping ability of 4 rotary NiTi instruments in simulated root canals. For the preparation of thirty two curved root canals, Mtwo instruments using "single length"technique, and Profile, ProTaper Universal, and K3 using crown-down technique (N = 8) were used. All canal samples were prepared by reaching an apical canal size of #30. Pre- and post-instrumentation digital images were recorded and an assessment of canal shape was determined using a computer image analysis program SigmaScan Pro (Systat Software Inc., San Jose, CA, USA). The changes of the dimension of inner walls of canals, (2) the changes of the dimension of outer walls of canals, and (3) the centering ratio were measured at 7 measuring points, and then data were statistically analyzed using one-way ANOVA and Duncan's test. The results were as below; 1. The root canal shaping ability of Profile was significantly faster than that of other rotary NiTi instruments (p < 0.05). 2. The deformation and fracture of all instruments used for this study were not experienced. 3. In the degree of changes of the dimension of inner walls of canals, Profile demonstrated the lowest changes of the dimension of inner walls of canals except at the measuring points of the 1 and 2 mm (p < 0.05). However, the ProTaper Universal showed the highest changes of the dimension of inner walls of canals at all measuring points (p < 0.05). 4. In the degree of changes of the dimension of outer walls of canals, Mtwo demonstrated the lowest changse of the dimension of outer walls of canals except at the measuring point of the 1 mm (p < 0.05). However, Profile exhibited the highest changes of the dimension of outer walls of canals at the measuring points of 3 and 4 mm and ProTaper Universal and K3 showed the largest changes of the dimension of outer walls of canals at the measuring points of 1, 2, 6, and 7 mm (p < 0.05). 5. In degree of centering ratio, Profile demonstrated the least centering ratio comparing with the centering ratio shown by other NiTi instruments at the measuring points of 1, 4, 5, and 6 mm. Results suggest that in the coronal part of canal preparation, active cutting files such as ProTaper Universal may efficiently flare the canal orifice and form a better taper, and in the apical part of the canal, files which have a better centering ability such as Profile may maintain the original canal curvature and reduce the shaping time.
Kim, Tae Sun;Kim, Min Ji;Kang, Yu Mi;Oh, Geune;Choi, Su Yeon;Oh, Mu Sul;Yang, Yong Shik;Seo, Jung-Mi;Ryu, Mi-Geum;Kim, Eun-Sun;Ha, Dong-Ryong;Cho, Bae Sik
Korean Journal of Food Science and Technology
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v.46
no.3
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pp.334-340
/
2014
Toxin-producing Bacillus cereus is the causative agent of two different types of food poisoning: the emetic and the diarrheal types. This study was conducted to investigate the presence of enterotoxin and emetic toxin genes in 263 B. cereus isolated from 619 different ready-to-eat food items. Hemolytic enterotoxins hblA, hblC, and hblD were detected in 85.6, 41.1, and 76.8%, respectively, of the B. cereus isolates. About 67.0% (175/263) of the isolates presented all of three genes. Non-hemolytic enterotoxins nheA, nheB, and nheC were detected in 100, 97.0, and 68.4% of the isolates, respectively. Approximately 90.0% (236/263) of the isolates presented all of these three non-hemolytic enterotoxin genes. Emetic toxin gene, CER, was detected in 132 of 263 (50.2%) isolates. Computer-assisted cluster analysis of Rep-PCR profiles showed a high genetic diversity among the isolates. All B. cereus isolates from food samples tested in this study carried at least 6 of 10 toxin genes.
The purpose of this study is to present an alternative improving the efficient and reasonable of the physical distribution system management is influenced by many factors. Therefore, the study depends on the documentary method and survey method to achieve the purpose of this study. The major components of a physical distribution system are refers to as elements, include warehouse·storage system, transportation system, inventory system, physical distribution information system. The factors used in this study are ① factor of product(quality·A/S·added value of product·adaption of product·technical competitive power to other enterprises), ② factor of market(market channel·kinds of customer·physical distribution share), ③ factor of warehouse·storage(warehouse design·size·direction·storage ability·warehouse quality), ④ factor of transportation(promptness·reliability·responsibility·kinds of transportation·cooperation united transportation system·national transportation network), ⑤ factor of packaging (packaging design·material·educating program·pollution degree measure program), ⑥ factor of inventory(ordinary inventory criterion·consistence for inventories record), ⑦ factor of unloaded(unloaded machine·having machine ratio), ⑧ factor of information system (physical distribution quantity analysis·usable computer part), ⑨ factor of physical distribution cost(sales ratio to product) ⑩ factor of physical distribution system(physical distribution center etc). The implication of this study can be summarized as follows: ① In firms that have not adopted a systems integrative approach, physical distribution is a fragmented and often uncoordinated set of activities spread throughout various functions with function having its own set of priorities and measurements. ② The physical distribution is recognized as more an important strategic factor than a simple cost reduction factor, ③ It can be used a strategic competition tool to enterprise.
Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.
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