• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.284-290
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• 2024

Speech emotion recognition (SER) is a technique that is used to analyze the speaker's voice patterns, including vibration, intensity, and tone, to determine their emotional state. There has been an increase in interest in artificial intelligence (AI) techniques, which are now widely used in medicine, education, industry, and the military. Nevertheless, existing researchers have attained impressive results by utilizing acted-out speech from skilled actors in a controlled environment for various scenarios. In particular, there is a mismatch between acted and spontaneous speech since acted speech includes more explicit emotional expressions than spontaneous speech. For this reason, spontaneous speech-emotion recognition remains a challenging task. This paper aims to conduct emotion recognition and improve performance using spontaneous speech data. To this end, we implement deep learning-based speech emotion recognition using the VGG (Visual Geometry Group) after converting 1-dimensional audio signals into a 2-dimensional spectrogram image. The experimental evaluations are performed on the Korean spontaneous emotional speech database from AI-Hub, consisting of 7 emotions, i.e., joy, love, anger, fear, sadness, surprise, and neutral. As a result, we achieved an average accuracy of 83.5% and 73.0% for adults and young people using a time-frequency 2-dimension spectrogram, respectively. In conclusion, our findings demonstrated that the suggested framework outperformed current state-of-the-art techniques for spontaneous speech and showed a promising performance despite the difficulty in quantifying spontaneous speech emotional expression.

• Journal of Acupuncture Research
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• v.22 no.3
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• pp.123-135
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• 2005

Objective : The aim of this study was to rivew systemically literature and clinical trials in the treatment of urinary incontinence or lower urinary tract syndrome(LUTS). Methods : Computerized literature searches were carried out on two electronic database, and computerized searching on some korea oriental medicine journals in library of Kyung-Hee Medical center. Results : 1. Three reports of review study, six reports of experimental study and fourteen reports of clinical trials were collected and reviewed. Three reports of review study were all printed in the korea oriental medicine journal. From 2000, researches and studies have been increased in quantity and improved in quality. 2. Urinary disturbance include variable symptoms of lower urinary tract symptoms, urinary incontinence, in theaspect of Oriental medicine these symptoms are anurin, dysuria, urinary incontinence, nochumal enuresis, uracratia and so on. 3. Roughly physiological procedure of Acupuncture in Treatment of Urianry Disturbance may be that effect of acupuncture stimulation for parasympathetic nerve, sleep-arousal system in cerebrum, pontine/spinal urination center and pudendal/pelvic nerve affect bladder in expansion of bladder capacity, inhibition of urinary contraction and affection in periurethral muscle by continuous excitement of spinal annular circuit and synapse of neuron. 4. Clinical result for acupuncture treatment in urinary disturbance is summarized that acupuncture treatment in urianation disturbance of Neurogenic Bladder, Incontinence, Cycitis, Nocturnal Enuresis, Prostatitis/Pelvic Pain Syndrom and so on is significant clinical trials and technique. Conclusion : Hereafter, in the old age society these variable urinary disturbance patients are increased and desire of treatment may be also increased. So study of various and formal treatment and tecnnique is needed.

• Economic and Environmental Geology
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• v.56 no.3
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• pp.311-330
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• 2023

Development of Carbon Capture and Storage (CCS) technique is becoming increasingly important as a method to mitigate the strengthening effects of global warming, generated from the unprecedented increase in released anthropogenic CO₂. In the recent years, the characteristics of basaltic rocks (i.e., large volume, high reactivity and surplus of cation components) have been recognized to be potentially favorable in facilitation of CCS; based on this, research on utilization of basaltic formations for underground CO₂ storage is currently ongoing in various fields. This study investigated the feasibility of underground storage of CO₂ in basalt, based on the examination of the CO₂ storage mechanisms in subsurface, assessment of basalt characteristics, and review of the global research on basaltic CO₂ storage. The global research examined were classified into experimental/modeling/field demonstration, based on the methods utilized. Experimental conditions used in research demonstrated temperatures ranging from 20 to 250 ℃, pressure ranging from 0.1 to 30 MPa, and the rock-fluid reaction time ranging from several hours to four years. Modeling research on basalt involved construction of models similar to the potential storage sites, with examination of changes in fluid dynamics and geochemical factors before and after CO₂-fluid injection. The investigation demonstrated that basalt has large potential for CO₂ storage, along with capacity for rapid mineralization reactions; these factors lessens the environmental constraints (i.e., temperature, pressure, and geological structures) generally required for CO₂ storage. The success of major field demonstration projects, the CarbFix project and the Wallula project, indicate that basalt is promising geological formation to facilitate CCS. However, usage of basalt as storage formation requires additional conditions which must be carefully considered - mineralization mechanism can vary significantly depending on factors such as the basalt composition and injection zone properties: for instance, precipitation of carbonate and silicate minerals can reduce the injectivity into the formation. In addition, there is a risk of polluting the subsurface environment due to the combination of pressure increase and induced rock-CO₂-fluid reactions upon injection. As dissolution of CO₂ into fluids is required prior to injection, monitoring techniques different from conventional methods are needed. Hence, in order to facilitate efficient and stable underground storage of CO₂ in basalt, it is necessary to select a suitable storage formation, accumulate various database of the field, and conduct systematic research utilizing experiments/modeling/field studies to develop comprehensive understanding of the potential storage site.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.1-8
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• 2013

Data mining techniques are used to find important and meaningful information from huge databases, and pattern mining is one of the significant data mining techniques. Pattern mining is a method of discovering useful patterns from the huge databases. Frequent pattern mining which is one of the pattern mining extracts patterns having higher frequencies than a minimum support threshold from databases, and the patterns are called frequent patterns. Traditional frequent pattern mining is based on a single minimum support threshold for the whole database to perform mining frequent patterns. This single support model implicitly supposes that all of the items in the database have the same nature. In real world applications, however, each item in databases can have relative characteristics, and thus an appropriate pattern mining technique which reflects the characteristics is required. In the framework of frequent pattern mining, where the natures of items are not considered, it needs to set the single minimum support threshold to a too low value for mining patterns containing rare items. It leads to too many patterns including meaningless items though. In contrast, we cannot mine any pattern if a too high threshold is used. This dilemma is called the rare item problem. To solve this problem, the initial researches proposed approximate approaches which split data into several groups according to item frequencies or group related rare items. However, these methods cannot find all of the frequent patterns including rare frequent patterns due to being based on approximate techniques. Hence, pattern mining model with multiple minimum supports is proposed in order to solve the rare item problem. In the model, each item has a corresponding minimum support threshold, called MIS (Minimum Item Support), and it is calculated based on item frequencies in databases. The multiple minimum supports model finds all of the rare frequent patterns without generating meaningless patterns and losing significant patterns by applying the MIS. Meanwhile, candidate patterns are extracted during a process of mining frequent patterns, and the only single minimum support is compared with frequencies of the candidate patterns in the single minimum support model. Therefore, the characteristics of items consist of the candidate patterns are not reflected. In addition, the rare item problem occurs in the model. In order to address this issue in the multiple minimum supports model, the minimum MIS value among all of the values of items in a candidate pattern is used as a minimum support threshold with respect to the candidate pattern for considering its characteristics. For efficiently mining frequent patterns including rare frequent patterns by adopting the above concept, tree based algorithms of the multiple minimum supports model sort items in a tree according to MIS descending order in contrast to those of the single minimum support model, where the items are ordered in frequency descending order. In this paper, we study the characteristics of the frequent pattern mining based on multiple minimum supports and conduct performance evaluation with a general frequent pattern mining algorithm in terms of runtime, memory usage, and scalability. Experimental results show that the multiple minimum supports based algorithm outperforms the single minimum support based one and demands more memory usage for MIS information. Moreover, the compared algorithms have a good scalability in the results.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.45-58
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• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.468-478
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• 2004

It is essential in various application areas of data mining and bioinformatics to effectively retrieve the occurrences of interesting patterns from sequence databases. For example, let's consider a network event management system that records the types and timestamp values of events occurred in a specific network component(ex. router). The typical query to find out the temporal casual relationships among the network events is as fellows: 'Find all occurrences of CiscoDCDLinkUp that are fellowed by MLMStatusUP that are subsequently followed by TCPConnectionClose, under the constraint that the interval between the first two events is not larger than 20 seconds, and the interval between the first and third events is not larger than 40 secondsTCPConnectionClose. This paper proposes an indexing method that enables to efficiently answer such a query. Unlike the previous methods that rely on inefficient sequential scan methods or data structures not easily supported by DBMSs, the proposed method uses a multi-dimensional spatial index, which is proven to be efficient both in storage and search, to find the answers quickly without false dismissals. Given a sliding window W, the input to a multi-dimensional spatial index is a n-dimensional vector whose i-th element is the interval between the first event of W and the first occurrence of the event type Ei in W. Here, n is the number of event types that can be occurred in the system of interest. The problem of‘dimensionality curse’may happen when n is large. Therefore, we use the dimension selection or event type grouping to avoid this problem. The experimental results reveal that our proposed technique can be a few orders of magnitude faster than the sequential scan and ISO-Depth index methods.hods.

• Clinical and Experimental Pediatrics
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• v.49 no.6
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• pp.610-616
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• 2006

Purpose : The purpose of this study was to evaluate the timing of sexual maturation and secular trends of menarchial age in Korean adolescents. Methods : Nine hundred eighty two school students and 119 university female students were included. Tanner's pubertal assessment method was applied using a self-assessment sheet with pictures for their developmental stages. A medical checkup database from 1,156,022 women was also used to analyze the age of menarche from the year 1900 to 1980. Results : Onset of puberty was at $11.3{\pm}1.3$ years(y) in girls and $12.1{\pm}1.5$ y in boys and total pubertal duration was 3.6 y in girls and 3.3 y in boys. Height at the onset of puberty was $146.1{\pm}7.9cm$ in girls and $152.7{\pm}9.8cm$ in boys. Weight at the onset of puberty was $39.3{\pm}6.9kg$ in girls and $47.7{\pm}14.4kg$ in boys. The mean age of menarche was $12.0{\pm}1.0y$ and mean age at nocturnal emission was $12.3{\pm}1.8y$. By age ten, 3.0 percent of girls experienced menarche, which increased to 41.1 percent by age 12, and 98.0 percent by age over 15. By SMR 2 breast stage, 18.2 percent of girls experienced menarche, which increased to 66.1 percent and 91.7 percent by SMR stages 3 and 4, respectively. By SMR 2 pubic hair stage, 52.0 percent and by SMR 3, 93.8 percent of girls experienced menarche. While the menarchial age of women born around 1980 was $12.4{\pm}1.1y$, the menarchial age of women born around 1990 was $12.0{\pm}1.1y$. Age at menarche has been advanced approximately by 2 years between 1900 and 1980 birth cohorts. Conclusion : There was a downward secular trend in pubertal timing. Age at menarche has been advanced by 2 years during the last 80 years. Further large scale, prospective studies, including inspection by specialists, are needed to provide reference data for pubertal timing in Korean adolescents.

• Clinical and Experimental Pediatrics
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• v.49 no.10
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• pp.1073-1078
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• 2006

Purpose : This study was performed to assess how a fetal diagnosis of congenital heart disease affects parents, as regards pregnancy management and care of infants after birth. Methods : Database search to find out abnormal fetal echocardiography performed at Seoul National University Children's Hospital from July 1988 to June 2003 revealed 370 examinations. After excluding both arrhythmias without structural cardiac disease and multiple pregnancies, 299 pregnancies remained and this data formed the basis of this analysis. We retrospectively reviewed the medical records with special attention to pregnancy outcomes and also tried to find out factors influencing parental decisions on whether to continue or terminate pregnancy. Results : In this study, the mean gestation age at diagnosis was $28{\pm}6.0weeks$. The mean age of mothers was $30{\pm}3.9$ years old. Younger gestational ages at diagnosis(P=0.000), more severe grades of fetal heart disease(P=0.002) and younger mothers(P=0.014) correlated with terminations of pregnanies. But the grades of fetal status, the grades of associated anomaly, whether in-vitro-fertilization was carried out or not and numbers of previous children were not significant. Conclusion : This study found that the earlier gestational ages at diagnosis, younger maternal age and higher grades of fetal heart disease tended to lead parent to select abortions. Fetal echocardiographies were performed too late. Moreover Koreans have a biased view that malformation is a something incurable and a tragedy not only to oneself, but also to a family. So parents select terminations of pregnancy, even in curable cases. This is very unethical.

• Clinical and Experimental Pediatrics
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• v.49 no.7
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• pp.757-762
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• 2006

Purpose : Pneumonia is one of the most common infections in children who visit emergency departments(ED), but standard clinical guidelines for children with pneumonia in Korea have not been studied. This study was performed to collect and evaluate a data-base of children with pneumonia for establishing clinical guidelines in ED. Methods : This study reviewed 304 children who were diagnosed and treated for pneumonia in the ED at one tertiary hospital between January 2003 and December 2003 retrospectively by reviewing the charts and analyzing the clinical characteristics, laboratory findings, and radiologic findings between an admission group and a discharge group. Results : The 2 year-5 year age group was the top of age distribution and the peak incidence of monthly distribution was December. Two hundred forty seven(81.3 percent) children were hospitalized(admission group), and the mean length of hospitalization was $7.24{\pm}3.24$ days. The most common indications of admission were fever, tachypnea and an age of less than three months. There was statistical differences in the outpatient department follow-up between the two groups(85.8 percent in admission group vs 35.1 percent in discharge group). Conclusion : More prospective studies are needed to establish clinical standard guidelines for children with pneumonia. This will be helpful in ED management and will aid the prevention of pneumonia.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.