• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.21-28
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• 2006

Structural health monitoring (SHM) is a new technology that will be increasingly applied at the industrial field as a potential approach to improve cost and convenience of structural inspection. Recently, the development of smart sensor is very active for real application. This study has focused on preparation and application study of SAL sensor. In order to detect elastic wave, smart piezoelectric sensor, SAL, is fabricated by using a piezoelectric element, shielding layer and protection layer. This protection layer plays an important role in a patched network of distributed piezoelectric sensor and shielding treatment. Four types of SAL sensor are designed/prepared/tested, and these details will be discussed in the paper. In this study, SAL sensor can be feasibly applied to perform structural health monitoring and to detect damage sources which result in elastic waves.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.21-30
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• 2021

With the rapid development of artificial intelligence and big data, a lot of medical data is effectively used, and the diagnosis and analysis of diseases has entered the era of intelligence. With the increasing public health awareness, ordinary citizens have also put forward new demands for panic disorder health services. Specifically, people hope to predict the risk of panic disorder as soon as possible and grasp their own condition without leaving home. Against this backdrop, the smart health industry comes into being. In the Internet age, a lot of panic disorder health data has been accumulated, such as diagnostic records, medical record information and electronic files. At the same time, various health monitoring devices emerge one after another, enabling the collection and storage of personal daily health information at any time. How to use the above data to provide people with convenient panic disorder self-assessment services and reduce the incidence of panic disorder in China has become an urgent problem to be solved. In order to solve this problem, this research applies the context awareness to the automatic diagnosis of human diseases. While helping patients find diseases early and get treatment timely, it can effectively assist doctors in making correct diagnosis of diseases and reduce the probability of misdiagnosis and missed diagnosis.

• Health Policy and Management
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• v.30 no.4
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• pp.433-437
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• 2020

Cancer is a disease which has the huge burden in worldwide, and cancer is the number one cause of death in Korea. At this point, the new framework for cancer monitoring index is required for regional cancer monitoring. Especially, cancer survivors are the important target which is rapidly increasing recently, also cancer survivor's quality of care should be considered in the cancer monitoring index framework. To develop the Multidimensional Cancer Monitoring Index considering cancer survivor's quality of care, we took into account cancer continuum which including prevention, detection, diagnosis, treatment, survivorship, assessment of quality of care and monitoring cancer patient, and end-of life care for stage. For target, components of health care delivery system such as patient, family, provider, payer, and policy maker are included. Also, Donabedian model which is a framework for examining health services and evaluating quality of health care such as structure, process, and outcome is applied to contents. This new cancer monitoring framework which includes multidimensional components could help to develop regional cancer monitoring index, and to make national cancer management and prevention policy in the future.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.233-244
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• 2021

Recently, several ICT-based cat studies have produced some successful results, according to academic and industry sources. However, research on the level of simply identifying the cat's condition, such as the behavior and sound classification of cats based on images and sound signals, has yet to be found. In this paper, based on the veterinary scientific knowledge of cats, a practical and academic cat monitoring and disease diagnosis system is proposed to monitor the health status of the cat 24 hours a day by automatically categorizing and analyzing the behavior of the cat with location information using LSTM with a beacon sensor and a raspberry pie that can be built at low cost. Validity of the proposed system is verified through experimentation with cats in actual custody (the accuracy of the cat behavior classification and location identification was 96.3% and 92.7% on average, respectively). Furthermore, a rule-based disease analysis system based on the veterinary knowledge was designed and implemented so that owners can check whether or not the cats have diseases at home (or can be used as an auxiliary tool for diagnosis by a pet veterinarian).

• Structural Engineering and Mechanics
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• v.41 no.4
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• pp.539-558
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• 2012

The diagnosis of bridge serviceability is carried out by a combination of in-situ visual inspection, static and dynamic loading tests and analyses. Structural health monitoring (SHM) using information technology and sensors is increasingly being used for providing a better estimate of structural performance characteristics rather than above traditional methods. Because the mechanical behavior of bridges with various kinds of damage can not be made clear, it is very difficult to estimate both the damage mode and degree of damage of existing bridges. In this paper, the sensitivity of both static and dynamic behaviors of bridges are studied as a measure of damage assessment through experiments on model bridges induced with some specified artificial damages. And, a method of damage assessment of bridges based on those behaviors is discussed in detail. Finally, based on the results, a possible application for structural health monitoring systems for existing bridges is also discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1219-1223
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• 2006

Tongue is one of the most important parts in patient diagnosis in traditional Korean(Chinese) medicine. This paper presents health monitoring method using tongue images of a person. The method uses not absolute tongue features but relative ones which are differences from reference health condition(RHC), diagnosed in hospital, for a person. A user can give tongue images to a health monitoring system everyday, which extracts regions of interest (ROI's) of the tongue, and compares their features with reference health condition. In the experiments, tongue image analysis for a person by our computerized method encouraged us that the method using tongue images can be contributed for health monitoring.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5613-5618
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• 2015

Clinicians should looking for techniques that helps to early diagnosis of cancer, because early cancer detection is critical to increase survival and cost effectiveness of treatment, and as a result decrease mortality rate. Medical images are the most important tools to provide assistance. However, medical images have some limitations for optimal detection of some neoplasias, originating either from the imaging techniques themselves, or from human visual or intellectual capacity. Image processing techniques are allowing earlier detection of abnormalities and treatment monitoring. Because the time is a very important factor in cancer treatment, especially in cancers such as the lung and breast, imaging techniques are used to accelerate diagnosis more than with other cancers. In this paper, we outline experience in use of image processing techniques for lung and breast cancer diagnosis. Looking at the experience gained will help specialists to choose the appropriate technique for optimization of diagnosis through medical imaging.

• Parasites, Hosts and Diseases
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• v.59 no.3
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• pp.281-289
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• 2021

This study aimed to characterize the seasonal abundance of hard ticks that transmit severe fever with thrombocytopenia syndrome virus from April to November 2019 and 2020 on Ganghwa-do, Incheon Metropolitan City, Korea. The ticks were collected at grassland, grave site, copse and mountain road using a collection trap method. The ixodid hard ticks comprising three species (Haemaphysalis longicornis, H. flava, and Ixodes nipponensis) collected were 6,622 in 2019 and 3,811 in 2020. H. longicornis was the most frequent (97.9% in 2019 and 96.0% in 2020), followed by H. flava (2.0% and 3.0% in 2019 and 2020, respectively) and I. nipponensis (less than 0.1%). Our study demonstrated that seasonal patterns of the tick populations examined for two years were totally unsimilar. The hard ticks tested using RT-qPCR were all negative for severe fever with thrombocytopenia syndrome virus.

• Clinical and Experimental Pediatrics
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• v.52 no.9
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• pp.964-970
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• 2009

Neonatal seizures are generally not only brief and subtle but also not easily recognized and are usually untreated. In sick neonates, seizures are frequently not manifested clinically but are detected only by electroencephalography (subclinical EEG seizures). This phenomenon of electroclinical dissociation is fairly common in neonates. On the other hand, neonates frequently show clinical behaviors such as stiffening, apnea, or autonomic manifestations that mimic seizures, which is usually associated with underlying encephalopathy and non-epileptic seizures. Therefore, it might be difficult to confirm the diagnosis of neonatal seizures. Early recognition of neonatal seizures is important to minimize poor neurodevelopmental outcomes, including cognitive, behavioral, and learning disabilities, as well as the development of postnatal epilepsy. EEG is a reliable tool in the determination of neonatal seizures. Continuous EEG monitoring is essential for the identification of seizures, evaluation of treatment efficacy, and prediction of the neurodevelopmental outcome. However, there is not yet a wide consensus on the optimal "standard" lead montage for the continuous EEG monitoring.

• Smart Structures and Systems
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• v.13 no.5
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• pp.775-796
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• 2014

This study presents a vibration-based health monitoring strategy for short span bridges utilizing an inspection vehicle. How to screen the health condition of short span bridges in terms of a drive-by bridge inspection is described. Feasibility of the drive-by bridge inspection is investigated through a scaled laboratory moving vehicle experiment. The feasibility of using an instrumented vehicle to detect the natural frequency and changes in structural damping of a model bridge was observed. Observations also demonstrated the possibility of diagnosis of bridges by comparing patterns of identified bridge dynamic parameters through periodical monitoring. It was confirmed that the moving vehicle method identifies the damage location and severity well.