• 셀메드
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• 제6권1호
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• pp.4.1-4.7
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• 2016

Dysmenorrhoea is the most important under diagnosed and undertreated gynaecologic disorder of all menstrual complaints. It affects 50% women of childbearing age and has a major impact on health and societal costs worldwideespecially in developing countries. Therefore, a literary exploration of traditional sources for aetiopathogenesis and clinical features of usr-i-tamth (dysmenorrhoea) were reviewed to correlate with contemporary knowledge.The traditional Unani sources viz., Al Hawi fi'l Tibb (Continens Liber),Tarjuma Kamil al-Sana'a al-Tibbiyya, Al-Qanun fi'l Tibb (Canon of Medicine), Dhakhira Khawarizam Shahi, Tibb-i-Akbar, Iksir-i-A'zam, Kitab al-Kulliyyat, and Kulliyyat-i-Qanun were reviewed. Further, recent studies in the contemporary era were also browsed on the website. The causes of usre-i-tamth as per classical sources are distemperament, uterine diseases (atresia, inflammation, amenorrhoea, cancer, prolapse, ulcer, tenuous morbid matter, and cervical obstruction), psychological disturbances, environmental factors, menstrual irregularities, obesity and young age. Recent studies also prove that obesity, psychological disturbance, menstrual irregularities, environmental factors, uterine diseases and young age lead to dysmenorrhea.Unani classical sources are very much enriched with the informative knowledge related to menstruation and uterine pain/dysmenorrhoea and recent studies in contemporary proves the same. Hence, implementation of the traditional system of medicines in present-day era may play a vital role to restore health in a holistic way.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• 한국공간정보시스템학회 논문지
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• 제11권2호
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• pp.45-53
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• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• 한국측량학회지
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• 제36권5호
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• pp.371-379
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• 2018

Unlike general VHR (Very-High-Resolution) satellite sensors that are mainly for panchromatic and MS (Multispectral) imaging, Worldview-3 sensor additionally provides eight SWIR (Short Wavelength Infrared) bands in wavelength range from 1198 nm to 2365 nm. This study investigates the effect of informative Worldview-3 SWIR bands for wetland classification performance. Worldview-3 imagery acquired over Sunchon Bay, which is a coastal wetland located in South Korea, is used to implement the classification. Land-cover classes for the scene are determined by referring to national land-cover maps, which are provided by the Ministry of Environment, overlapped with the scene. After that, training data for each determined class are collected. In order to analyze the effect of SWIR bands, classifications with and without SWIR bands are carried out and the results are then compared. In this regard, a SVM (Support Vector Machine) is utilized as their classifier. As a result of the accuracy assessments performed by test data that are independently extracted from training data, it was confirmed that classification performance was improved when the SWIR bands are included as input features for SVM-based classification.

• 한국콘텐츠학회논문지
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• 제1권1호
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• pp.59-67
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• 2001

컴퓨터를 비롯한 통신의 영역과 가전제품의 영역이 교차되면서 새로운 차원의 정보가전제품들이 등장하고 있으며 이들 제품들에게 있어 사용자 인터페이스는 매우 중요한 요소라 할 수 있다. 특히 영상기기류에 장착되는 OSD와 리모컨은 사용자 인터페이스의 핵심적인 요소로서 본체의 매력적인 스타일링 못지않게 심도깊은 연구가 필요한 부분이다. 그럼에도 불구하고 OSD 디자인에 대한 담당자나 영역이 불명확하여 회로기술자들이 단순기능의 이전모델부터 해온 경험과 단순한 직관을 바탕으로 사용자의 시각이 아닌 엔지니어의 시각에서 설계하여 왔다. 이에 본 연구에서는 기업에서의 개발사례를 바탕으로 인터페이스 디자이너에 의한 사용자 중심의 OSD 개발 프로세스를 규명하고 OSD의 특수성 즉 OSD가 제한된 용량의 마이컴과 메모리에 저장되어 제품에 내장되고 디스플레이되는 매체도 해상도에 제약이 있는 TV화면으로 하드웨어적인 사양에 많은 영향을 받으며, 입력장치가 리모컨으로 제한된 수의 입력버튼을 가지고 모든 조작이 가능해야 한다는 점 등 을 고려한 실행단계별 가이드라인을 제시한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.49-53
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• 1994

Advanced Real-Time Satellite Simulator(ARTSS) has been developed to support the telemetry, tracking and command operations of the ETRI satellite control system and to provide satellite engineers a more powerful and informative satellite simulations tool on the desktop. To provide extensive simulation functions for a communication satellite system in the pre-operational and operational missions, ARTSS uses a geosynchronous orbit(GEO) satellite model consisting of the attitude and orbit control subsystem, the power subsystem, the thermal subsystem, the telemetry, command and ranging subsystem, and the communications payload subsystem. In this paper, the system features and functions are presented and the satellite subsystem models are explained in detail.

• 전자공학회논문지
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• 제50권12호
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• pp.224-231
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• 2013

이 논문에서는 비정형 혼합 오디오 신호에서 청취자에게 전달 되도록 의도된 주된 신호의 종류를 검출해 낼 수 있는 방법을 제안한다. 주된 신호의 종류는 음성, 음악, 음향효과로 정하였으며, 인텐서티 기반의 발생/소멸 패턴에서 추출할 수 있는 특징을 사용하여 그들을 구별할 수 있는 방법을 소개한다. 청취자가 주어진 오디오 신호에서 주된 신호를 받아들이는 주관적인 평가를 반영하기 위해서, 웹기반의 평가시스템을 도입하여 18시간의 다양한 종류의 장르 비디오의 오디오를 평가하였다. 실험을 통하여 비디오의 장르별로 각기 다른 성능을 보이지만 가능성 있는 (음성위주의 토크쇼의 경우 86.7%, 액션 영화 49.3%)정확도를 보였다.

• 한국실내디자인학회논문집
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• 제20권4호
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• pp.11-20
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• 2011

Jeju Special Self-Governing Province are trying every effort to be presented as an International Free City with unique combination of history, culture and landscape, This research focuses on the analysis of characteristics we can find in buildings in Jeju province. The main purpose is to provide basic and informative materials for the landscape formation of Jeju by investigating current status of buildings in Jeju province. This research divides Jeju province into 34 areas and categorizes buildings by use. 2,973 cases in total are collected and analyzed their architectural features. A basic analysis of the collected data is conducted in the first and the second stages. And In the third stage, 505 cases whose addresses can be identified are selected for the in-depth analysis of the registered building data on architecture year, building area, and total area. These data are analyzed by the categories of region, year, and size for the study of general characteristics of buildings in Jeju. The results show that territoriality is weak because of the simplicity of building layout on the streets. Exterior form of buildings, streetscape image, and overall city image are tedious and boring because of the lack of the variety of facade and exterior finishing materials.

• Annals of Clinical Neurophysiology
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• 제4권1호
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• pp.21-27
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• 2002

Background : Spatial analysis of EEG is a phenomenal assessment and not so informative for phase space and dynamic aspect of EEG data. In contrast, nonlinear EEG analysis attempts to characterize the dynamics of neural networks in the brain. We have analyzed the features of EEG nonlinearly in subjects with white matter change on brain MRI and compared the results with cognitive function in each. Methods : Digital EEG data were taken for 30 seconds in 9 subjects with white matter degeneration and in 5 healthy normal controls without white matter change on MRI. Then we analyzed them nonlinearly to calculate the correlation dimension(D2) using the MATLAB software. The cognitive function was assessed by 3MS(modified mini-mental state examination). The severity of white matter change was assessed by Scheltens scale. Results : The mean D2 value of normal control was greater than that of white matter degeneration group. The D2s of some channels were correlative with 3MS and degree of white matter degeneration significantly. Conclusions : nonlinear analysis of EEG can be used as one of adjuvant functional studies for prediction of cognitive impairment in subjects with white matter degeneration and subcortical white matter change can be influential on cognitive function and correlation dimension of EEG.

• Archives of Plastic Surgery
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• 제46권2호
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• pp.102-107
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• 2019

Mobile computing devices (MCDs), such as smartphones and tablets, are revolutionizing medical practice. These devices are almost universally available and offer a multitude of capabilities, including online features, streaming capabilities, high-quality cameras, and numerous applications. Within the surgical field, MCDs are increasingly being used for simulations. Microsurgery is an expanding field of surgery that presents unique challenges to both trainees and trainers. Simulation-based training and assessment in microsurgery currently play an integral role in the preparation of trainee surgeons in a safe and informative environment. MCDs address these challenges in a novel way by providing valuable adjuncts to microsurgical training, assessment, and clinical practice through low-cost, effective, and widely accessible solutions. Herein, we present a review of the capabilities, accessibility, and relevance of MCDs for technical skills acquisition, training, and clinical microsurgery practice, and consider the possibility of their wider use in the future of microsurgical training and education.