• Journal of Yeungnam Medical Science
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• v.24 no.2
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• pp.148-153
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• 2007

Background : Computer- and web-based simulation methods help students develop problem solving and decision making skills. In addition, they provide reality based learning to the student clinical experience with immediate medical feedback as well as repetitive training, on-site reviews and case closure. Materials and Methods : Seventy-five third-year medical students participated in a two-week simulation program. The students selected four modules from eight modules as follows: airway and breathing 1, cardiac arrest 1, cardiac arrhythmia 1, and chest pain 1, and then selected the first case within each of the modules. After 2 weeks, a pass score was obtained and the data analyzed. The average pass score of over 70% was considered a passing grade for each module. If the student did not pass each module, there was no score (i.e., pass score was zero). In addition, when at least one of the four modules was zero, the student was not included in this study. Results : Seventy-five students participated in the simulation program. Nineteen students were excluded based on their performance. The final number of students studied was 56 students (74.7%). The average scores for each module 1 to 4 were 86.7%, 85.3%, 84.0%, and 84.0%, and the average obtained pass score was 88.6 for the four modules in all 56 students. Conclusion : Medical simulation enabled students to experience realistic patient situations as part of medical learning. However, it has not been incorporated into traditional educational methodology. Here we describe the introduction and the development of various simulation modules and technologies for medical education.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.103-118
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• 1999

This paper analyzes the performance of symbol timing recovery and equalizer in 8VSB digital terrestrial TV receiver under various multipath signals and proposes equalization techniques which improve indoor reception performance. Data segment sync is used for symbol timing recovery and timing offset is measured for echoes of various delays and amplitudes by using symbol timing detection filter whose pattern is +1. +1. -1. and -1. Measured timing offsets were below 10% for long echoes with more than 5 symbol delay and above 30% for short echoes with around 1 symbol delay. Indoor reception is always more challenging than outdoor reception due to lower signal strength. large and short multipaths. and moving interfering objects. So it is considered to use FSE (Fractionally Spaced Equalizer) which is very robust to timing offset and blind equalizer which can update equalizer tap coefficients even by information data. We compare the performance of conventional DFE (Decision Feedback Equalizer) and FSE-DFE using LMS algorithm and Stop and Go algorithm for the indoor reception. Experiments reveals FSE has excellent performance for large timing offset and Stop and Go algorithm shows good performance for Doppler shift. so we propose to use FSE-DFE structure with Stop and Go algorithm for the reliable indoor reception.

• Journal of KSNVE
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• v.10 no.6
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• pp.1059-1066
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• 2000

In this paper. a new indirect feedback active noise control (ANC) scheme barred on the fundamental frequency estimation is proposed for systems with a harmonic noise. When reference signals necessary for feedforward ANC configuration are difficult to obtain, the conventional ANC algorithms for multi-tonal noise do not measure the reference signals but generate them with the estimated frequencies.$^{(4)}$ However, the beating phenomena, in which certain frequency components of the noise vanish intermittently, may make the adaptive frequency estimation difficult. The confusion in the estimated frequencies due to the beating phenomena makes the generated reference signals worthless. The proposed algorithm consists of two parts. The first part is a reference generator using the fundamental frequency estimation and the second one is the conventional feedforward control. We propose the fundamental frequency estimation algorithm using decision rules. which is insensitive to the beating phenomena. In addition, the proposed fundamental frequency estimation algorithm has good tracking capability and lower variance of frequency estimation error than that of the conventional cascade ANF method.$^{(4)}$ We are also able to control all interested modes of the noise, even which cannot be estimated by the conventional frequency estimation method because of the poor S/N ratio. We verify the performance of the proposed ANC method through simulations for the measured cabin noise of a passenger ship and the measured time-varying engine booming noise of a passenger vehicle.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.353-367
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• 2015

The goal of this study is to analyze the feedback structure of habitat changes of the Whooper Swan in Eulsukdo using system thinking to suggest a management plan for ecosystem health. Using the causal loop diagrams of population changes between Whooper Swan and other bird species in Eulsukdo, we found that the environmental changes in the roosting and foraging area affect the Whooper Swan's population. The causal loop diagrams of the Whooper Swan's roosting area indicated that the environmental changes (e.g., water level, noise, bird watching, and other experience activities) may influence their population density variation. In addition, the casual loop diagrams of the Whooper Swan's foraging area showed that the Whooper Swan's population was affected by various variables that included area factors such as surface area of freshwater, frozen water, salinity, and density of Scirpus planiculmis. Furthermore, through the integrated causal loop diagram, cumulative discharge of Nakdong estuary weir and building activities were identified as the variables that affect the population of the Whooper Swan. Thus, we selected this area as the strategic point to establish a management plan for the Whooper Swan's habitat. The results of this study will help in decision making of a long-term management plan for sustaining the environmental health of the ecosystem in Eulsukdo.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.125-137
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• 2011

Product reviews in online shopping sites can serve as a useful guideline to buying decisions of customers. However, due to the massive amount of such reviews, it is almost impossible for users to read all the product reviews. For this reason, e-commerce sites provide users with useful reviews or statistics of ratings on products that are manually chosen or calculated. Opinion mining or sentiment analysis is a study on automating above process that involves firstly analyzing users' reviews on a product to tell if a review contains positive or negative feedback, and secondly, providing a summarized report of users' opinions. Previous researches focus on either providing polarity of a user's opinion or summarizing user's opinion on a feature of a product that result in relatively low usage of information that a user review contains. Actual user reviews contains not only mere assessment of a product, but also dissatisfaction and flaws of a product that a user experiences. There are increasing needs for effective analysis on such criteria to help users on their decision-making process. This paper proposes a model that stores various types of user reviews in a data warehouse, and analyzes integrated reviews dynamically. Also, we analyze reviews of an online application shopping site with the proposed model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.1
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• pp.57-72
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• 2008

Serve and do so that graft together specialists' view application field of computer and developmental disability diagnosis estimation data to construct developmental disability diagnosis estimation system in this Paper and constructed developmental disability diagnosis estimation system. Developmental disability diagnosis estimation must supply information of specification area that specialists are having continuously. Developmental disability diagnosis estimation specialist system need multimedia data processing that is specialized little more for developmental disability classification diagnosis and decision-making and is atomized for this. Characteristic of developmental disability diagnosis estimation system that study in this paper can supply quick feedback about result, and can reduce mistake on recording and calculation as well as can shorten examination's enforcement time, and background of training is efficient system fairly in terms of nonprofessional who is not many can use easily. But, as well as when multimedia information that is essential data of system construction for developmental disability diagnosis estimation is having various kinds attribute and a person must achieve description about all developmental disability diagnosis estimation informations, great amount of work done is accompanied, technology about equal data can become different according to management. Because of these problems, applied search technology of contents base (Content-based) that search connection information by contents of edit target data for developmental disability diagnosis estimation data processing multimedia data processing technical development. In the meantime, typical access way for conversation style data processing to support fast image search, after draw special quality of data by N-dimension vector, store to database regarding this as value of N dimension and used data structure of Tree techniques to use index structure that search relevant data based on this costs. But, these are not coincided correctly in purpose of developmental disability diagnosis estimation because is developed focusing in application field that use data of low dimension such as original space DataBase or geography information system. Therefore, studied save structure and index mechanism of new way that support fast search to search bulky good physician data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.739-752
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• 2002

Recently, to utilize the limited bandwidth effectively, the concept of partial response (PR) signaling has widely been adopted in both the high-speed data transmission and high-density digital recording/playback systems such as digital microwave, digital subscriber loops, hard disk drives, digital VCR's and digital versatile recordable disks and so on. This paper is concerned with adaptive equalization of partial response channels particularly for the magnetic recording channels. Specifically we study how the PR channel equalizers work for different choices of desired or reference signals used for adjusting the equalizer weights. In doing so, we consider three different configurations that are actually implemented in the commercial products mentioned above. First of all, we show how to compute the theoretical values of the optimum Wiener solutions derived by minimizing the mean-squared error (MSE) at the equalizer output. Noting that this equalizer MSE measure cannot be used to fairly compare the three configurations, we propose to use the data MSE that is computer just before the final detector for the underlying PR system. We also express the data MSE in terms of the channel impulse response values, source data power and additive noise power, thereby making it possible to compare the performance of the configurations under study. The results of extensive computer simulation indicate that our theoretical derivation is correct with high precision. Comparing the three configurations, it also turns out that one of the three configurations needs to be further improved in performance although it has an apparent advantage over the others in terms of memory size when implemented using RAM's for the decision feedback part.

• Phonetics and Speech Sciences
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• v.13 no.1
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• pp.1-15
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• 2021

The present study investigated the mental representation and processing of an ambiguous word in the bimodal processing system by manipulating the lexical ambiguity of a visually or auditorily presented word. Homonyms (e.g., '물었다') with more than two meanings and control words (e.g., '고통을') with a single meaning were used in the experiments. The lemma frequency of words was manipulated while the relative frequency of multiple meanings of each homonym was balanced. In both experiments using the lexical decision task, a robust frequency effect and a critical interaction of word type by frequency were found. In Experiment 1, spoken homonyms yielded faster latencies relative to control words (i.e., ambiguity advantage) in the low frequency condition, while ambiguity disadvantage was found in the high frequency condition. A similar interactive pattern was found in visually presented homonyms in the subsequent Experiment 2. Taken together, the first key finding is that interdependent lexico-semantic processing can be found both in the visual and auditory processing system, which in turn suggests that semantic processing is not modality dependent, but rather takes place on the basis of general lexical knowledge. The second is that multiple semantic candidates provide facilitative feedback only when the lemma frequency of the word is relatively low.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.2
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• pp.73-78
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• 2022

Since Traditional Korean medicine (TKM) doctors use various knowledge systems during treatment, diagnosis results may differ for each TKM doctor. However, it is difficult to explain all the reasons for the diagnosis because TKM doctors use both explicit and implicit knowledge. In this study, an upgraded random forest (RF)-based evaluation tool was proposed to extract clinical knowledge of TKM doctors. Also, it was confirmed to what extent the professor's clinical knowledge was delivered to the trainees by using the evaluation tool. The data used to construct the evaluation tool were targeted at 106 people who visited the Sasang Constitutional Department at Kyung Hee University Korean Medicine Hospital at Gangdong. For explicit knowledge extraction, four TKM doctors were asked to express the importance of symptoms as scores. In addition, for implicit knowledge extraction, importance score was confirmed in the RF model that learned the patient's symptoms and the TKM doctor's constitutional determination results. In order to confirm the delivery of clinical knowledge, the similarity of symptoms that professors and trainees consider important when discriminating constitution was calculated using the Jaccard coefficient. As a result of the study, our proposed tool was able to successfully evaluate the clinical knowledge of TKM doctors. Also, it was confirmed that the professor's clinical knowledge was delivered to the trainee. Our tool can be used in various fields such as providing feedback on treatment, education of training TKM doctors, and development of AI in TKM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.