• Korean Journal of Biological Psychiatry
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• v.23 no.2
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• pp.37-40
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• 2016

Treatment-resistant depression (TRD) is a major public health problem. It is estimated that about 30% of patients with major depressive disorder do not show substantial clinical improvement to somatic or psychosocial treatment. Most of studies for TRD have focused on the subjects already known as TRD. Patients with unipolar depressive episodes that do not respond satisfactorily to numerous sequential treatment regimens were included in the TRD studies. Such post hoc experimental design can be regarded only as consequences of having TRD, rather than as causal risk factors for it. Although informative, data derived from such studies often do not allow a distinction to be made between cause and effect. So, we should shift paradigm toward examining the risk for developing TRD in untreated depressed patients. To deal with this problem, untreated depressed patients should be enrolled in the study to identify biological markers for treatment resistance. The peripheral or central biological markers should be explored before starting treatment. Subsequent systematic administration of treatments with appropriate monitoring in the subjects can determine the risk for developing treatment resistance in untreated individuals. Such information could give a cue to improve the initial diagnosis and provide more effective treatment for TRD.

• Structural Engineering and Mechanics
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• v.31 no.3
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• pp.333-347
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• 2009

Due to structural complicacy, structural health monitoring for civil engineering needs more accurate and effectual methods of damage identification. This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve the validity of damage detection. Firstly, the essential theory and applied mathematic methods of MSIF are introduced. And then, the structural damage identification method based on multi-mode information fusion is put forward. Later, on the basis of a numerical simulation of a concrete continuous box beam bridge, it is obviously indicated that the improved modal strain energy method based on multi-mode information fusion has nicer sensitivity to structural initial damage and favorable robusticity to noise. Compared with the classical modal strain energy method, this damage identification method needs much less modal information to detect structural initial damage. When the noise intensity is less than or equal to 10%, this method can identify structural initial damage well and truly. In a word, this structural damage identification method based on multi-mode information fusion has better effects of structural damage identification and good practicability to actual structures.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.16 no.2
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• pp.1-11
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• 2008

Increasing demand for improved reliability and survivability of mission-critical systems is driving the development of health monitoring and Automated Contingency Management (ACM) systems. An ACM system is expected to adapt autonomously to fault conditions with the goal of still achieving mission objectives by allowing some degradation in system performance within permissible limits. ACM performance depends on supporting technologies like sensors and anomaly detection, diagnostic/prognostic and reasoning algorithms. This paper presents the development of a generic prototype test bench software framework for developing and validating ACM systems for advanced propulsion systems called the Propulsion ACM (PACM) Test Bench. The architecture has been implemented for a Monopropellant Propulsion System (MPS) to demonstrate the validity of the approach. A Simulink model of the MPS has been developed along with a fault injection module. It has been shown that the ACM system is capable of mitigating the failures by searching for an optimal strategy. Furthermore, the concepts of Validation and Verification (V&V) of such systems are introduced with relevant examples.

• Smart Structures and Systems
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• v.13 no.5
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• pp.869-890
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• 2014

In this study, a damage detection approach using train-induced vibration response of the bridge is proposed, utilizing only direct structural analysis by means of introducing soft computing methods. In this approach, the possible damage patterns of the bridge are assumed according to theoretical and empirical considerations at first. Then, the running train-induced dynamic response of the bridge under a certain damage pattern is calculated employing a developed train-bridge interaction analysis program. When the calculated result is most identical to the recorded response, this damage pattern will be the solution. However, owing to the huge number of possible damage patterns, it is extremely time-consuming to calculate the bridge responses of all the cases and thus difficult to identify the exact solution quickly. Therefore, the soft computing methods are introduced to quickly solve the problem in this approach. The basic concept and process of the proposed approach are presented in this paper, and its feasibility is numerically investigated using two different train models and a simple girder bridge model.

• Genomics & Informatics
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• v.11 no.4
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• pp.174-179
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• 2013

The large amount of data on cancer genome research has contributed to our understanding of cancer biology. Indeed, the genomics approach has a strong advantage for analyzing multi-factorial and complicated problems, such as cancer. It is time to think about the actual usage of cancer genomics in the clinical field. The clinical cancer field has lots of unmet needs in the management of cancer patients, which has been defined in the pre-genomic era. Unmet clinical needs are not well known to bioinformaticians and even non-clinician cancer scientists. A personalized approach in the clinical field will bring potential additional challenges to cancer genomics, because most data to now have been population-based rather than individualbased. We can maximize the use of cancer genomics in the clinical field if cancer scientists, bioinformaticians, and clinicians think and work together in solving unmet clinical needs. In this review, we present one imaginary case of a cancer patient, with which we can think about unmet clinical needs to solve with cancer genomics in the diagnosis, prediction of prognosis, monitoring the status of cancer, and personalized treatment decision.

• Journal of Preventive Medicine and Public Health
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• v.46 no.4
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• pp.173-182
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• 2013

Obesity during childhood is a dominant risk factor for noncommunicable diseases (NCDs), and is itself considered a disease that needs to be treated. Recently, the growth in childhood obesity in Korea has become stagnant; however, two in every ten children are still overweight. In addition, 60% or more of overweight children have at least one metabolic syndrome risk factor. Thus, childhood obesity should be controlled through lifestyle modification. This paper reviews studies of the modifiable risk factors of obesity in Korean children. According to the life-course approach, preschool-aged children (<5 years) are influenced by their parents rather than individual habits because they are under mostly parental care. Elementary school-aged children (6 to 11 years) are affected by overlapping individual and parental effects. This may mean that the establishment of individual behavior patterns begins during this period. The conditions of poor eating habits such as skipping meals, eating out, and high fat intake, along with low physical activity, facilitate increased obesity among adolescents (12 to 18 years). Notably, adolescent girls show high rates of both underweight and obesity, which may lead to the development of NCDs in their offspring. Therefore, the problem of NCDs is no longer limited to adults, but is also prevalent among children. In addition, early intervention offers cost-effective opportunities for preventing NCDs. Thus, children need primary consideration, adequate monitoring, diagnosis, and treatment to reduce the burden of NCDs later in adulthood.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1793-1798
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• 2007

Recently there are some trends to construct smart home system infrastructure depending upon the development of Information and Communication Technology. Also requirements of the Ubiquitous Healthcare Systems at home which can monitor the status of health continuously are increased rapidly comparing with hospitals. Healthcare service can be divided into two categories. The first one is Alarm Service that can be used for the emergency status and the other one is Remote Support Service which can monitor the patient including home environments and give those diagnosis information to medical office or to his family. Generally wired networks and fixed healthcare measuring system have some limits to transmit reliable realtime based information for both categories described above comparing with portable monitoring system. Getting over the inefficiency we will design and implement portable healthcare system under the wireless Zigbee network environments.

• Smart Structures and Systems
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• v.5 no.1
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• pp.95-117
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• 2009

In this paper, the time series based damage detection algorithms developed by Nair, et al. (2006) and Nair and Kiremidjian (2007) are applied to the benchmark experimental data from the National Center for Research on Earthquake Engineering (NCREE) in Taipei, Taiwan. Both acceleration and strain data are analyzed. The data are modeled as autoregressive (AR) processes, and damage sensitive features (DSF) and feature vectors are defined in terms of the first three AR coefficients. In the first algorithm developed by Nair, et al. (2006), hypothesis tests using the t-statistic are applied to evaluate the damaged state. A damage measure (DM) is defined to measure the damage extent. The results show that the DSF's from the acceleration data can detect damage while the DSF from the strain data can be used to localize the damage. The DM can be used for damage quantification. In the second algorithm developed by Nair and Kiremidjian (2007) a Gaussian Mixture Model (GMM) is used to model the feature vector, and the Mahalanobis distance is defined to measure damage extent. Additional distance measures are defined and applied in this paper to quantify damage. The results show that damage measures can be used to detect, quantify, and localize the damage for the high intensity and the bidirectional loading cases.

• Journal of IKEEE
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• v.23 no.3
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• pp.1082-1087
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• 2019

In this study, ECG signal amplifier, wireless transmitter/receiver circuit, signal processing filter circuit and A/D converter circuit design required for the development of small sized ECG module for wireless transmission/ reception were performed. In order to verify the performance of ECG sensors, the measurement was performed from 1 m to 3 m to measure the signal noise ratio according to the gateway distance. Experimental results showed that the signal noise ratio at 2 m distance was 17.18 dB on average, which fulfilled the requirements for commercialization. The experimental results obtained in this study are expected to contribute to the low cost, high efficiency mobile health field where remote monitoring diagnosis can be applied to small biometric devices for chronic disease management.

• Parasites, Hosts and Diseases
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• v.59 no.2
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• pp.153-157
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• 2021

This study reports the first two clinical cases of spirometrosis caused by Spirometra sp. in cats in Korea. In these two cases, the cats vomited, and long proglottids of tapeworm were recovered. The sick cats presented with anorexia and lethargy. However, they unexpectedly showed no diarrhea, which is the main symptom of spirometrosis. Based on a fecal floatation test as well as morphological and molecular analyses, the parasite was diagnosed as Spirometra sp. The 2 cases were treated with praziquantel. This study suggests regular monitoring of health and deworming in companion animals, even when animals are well cared for, with regular preventive medication. Additionally, spirometrosis should be considered in the differential diagnosis in cases of gastrointestinal symptoms in Spirometra endemic areas.