• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.225-234
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• 2023

In this era of information and communication technology (ICT), tremendous improvements have been witnessed in our daily lives. The impact of these technologies is subjective and negative or positive. For instance, ICT has brought a lot of ease and versatility in our lifestyles, on the other hand, its excessive use brings around issues related to physical and mental health etc. In this study, we are bridging these both aspects by proposing the idea of AI based mental healthcare (AIMS). In this regard, we aim to provide a platform where the patient can register to the system and take consultancy by providing their assessment by means of a chatbot. The chatbot will send the gathered information to the machine learning block. The machine learning model is already trained and predicts whether the patient needs a treatment by classifying him/her based on the assessment. This information is provided to the mental health practitioner (doctor, psychologist, psychiatrist, or therapist) as clinical decision support. Eventually, the practitioner will provide his/her suggestions to the patient via the proposed system. Additionally, the proposed system prioritizes care, support, privacy, and patient autonomy, all while using a friendly chatbot interface. By using technology like natural language processing and machine learning, the system can predict a patient's condition and recommend the right professional for further help, including in-person appointments if necessary. This not only raises awareness about mental health but also makes it easier for patients to start therapy.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5637-5642
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• 2012

Objective: Gastric cancer (GC) is one of the most common malignancies and its mortality ranks third among all cancers in China. We previously noted that XRCC1 Arg194Trp was associated with GC risk in Western China in a study on XRCC1 Arg194Trp and ADPRT Val762Ala. We aimed to further explore the association of these polymorphisms with risk of the noncardia subtype. Methods: We enrolled 176 noncardia GC patients and 308 controls from four hospitals and a community between October 2010 and August 2011. Genotyping was performed in a 384-well plate format on the Sequenom MassARRAY platform. A self-designed questionnaire was utilized to collect epidemiological data from the subjects regarding demographic factors and potential risk factors. Results: Subjects were aged $56.8{\pm}11.8$ (mean ${\pm}$ standard deviation) and $57.6{\pm}11.1$ years in the case and control groups, respectively. Individuals carrying the XRCC1 Trp/Trp or Arg/Trp variant genotype were at significantly increased risk of noncardia GC (adjusted OR, 1.48; 95% CI, 1.00-2.17), after adjustment for family history of cancer, drinking, and smoking. The increased risk of XRCC1 Arg194Trp variant genotype was more pronounced among subjects below 60 years old (adjusted OR, 1.78; 95% CI, 1.07-2.96), compared to older individuals. ADPRT Val762Ala variants (Ala/Ala or Val/Ala) were not associated with noncardia GC (adjusted OR, 1.03; 95% CI, 0.69-1.54). Conclusions: Our study suggests that XRCC1 Arg194Trp is a genetic susceptibility factor for developing noncardia GC in Han Chinese in Western China. In particular, individuals with the XRCC1 Arg194Trp variant genotype are at increased risk for GC below 60 years old.

• Genomics & Informatics
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• v.9 no.4
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• pp.152-160
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• 2011

Hypertension is the major factor of most death and high blood pressure (BP) can lead to stroke, myocardial infarction and cardiac failure. Moreover, hypertension is strongly correlated with body mass index (BMI). Although the exact causes of hypertension are still unclear, some of genetic loci were discovered from genome-wide association study (GWAS). Therefore, it is essential to study genetic variation for finding more genetic factor affecting hypertension. The purpose of our study is to conduct a CNV association study for hypertension-related traits, BP and BMI, in Korean individuals. We identified 2,206 CNV regions from 3,274 community-based Korean participants using the Affymetrix Genome-Wide Human SNP Array 6.0 platform and performed a logistic regression analysis of CNVs with two hypertension-related traits, BP and BMI. Moreover, the 4,692 participants in an independent cohort were selected for respective replication analyses. GWAS of CNV identified two loci encompassing previously known hypertension-related genes: LPA (lipoprotein) on 6q26, and JAK2 (Janus kinase 2) on 9p24, with suggestive p-values (0.0334 for LPA and 0.0305 for JAK2 ). These two positive findings, however, were not evaluated in the replication stage. Our result confirmed the conclusion of CNV study from the WTCCC suggesting weak association with common diseases. This is the first study of CNV association study with BP and BMI in Korean population and it provides a state of CNV association study with common human diseases using SNP array.

• The Journal of Korean Physical Therapy
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• v.10 no.1
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• pp.149-154
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• 1998

This study was designed 1) to quantitatively observe changes in static platform and 2) to observe balance performance using vision. Seventy-five subjects participated in the study. Subjects comprised 39 males and 36 females(mean ages=23.8 years) without neurologic and orthopaedic impairments. Static balance was measured with eyes open and closed. Subjects was required to move the cneter of balance curser in a counterclockwise for 30 sec. The effect for the COBx(-) suggests that subjects tended to maintain their weight slightly In the left. The time taken and the accuracy to move the center of balance from target to target was 14 sec, $49.47\%$. The body sway upon reaching the target was 7.3 AP sway and 11.88 LR sway distance. In this study, the data developed could be appropriate to use for sine comparisons when balance training patients with neurologic or orthopaedic impairments.

• Electronics and Telecommunications Trends
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• v.33 no.3
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• pp.89-99
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• 2018

Human activity recognition (HAR) is a technology that aims to offer an automatic recognition of what a person is doing with respect to their body motion and gestures. HAR is essential in many applications such as human-computer interaction, health care, rehabilitation engineering, video surveillance, and artificial intelligence. Smartphones are becoming the most popular platform for activity recognition owing to their convenience, portability, and ease of use. The noticeable change in smartphone-based activity recognition is the adoption of a deep learning algorithm leading to successful learning outcomes. In this article, we analyze the technology trend of activity recognition using smartphone sensors, challenging issues for future development, and a strategy change in terms of the generation of a activity recognition dataset.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.3
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• pp.246-259
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• 2011

This study presents a structural health monitoring (SHM) method for bolted connections by using multi-channel wireless impedance sensor nodes and multiple PZT-interfaces. To achieve the objective, the following approaches are implemented. Firstly, a PZT-interface is designed to monitor bolt loosening in bolted connection based on variation of electro-mechanical(EM) impedance signatures. Secondly, a wireless impedance sensor node is designed for autonomous, cost-efficient and multi-channel monitoring. For the sensor platform, Imote2 is selected on the basis of its high operating speed, low power requirement and large storage memory. Finally, the performance of the wireless sensor node and the PZT-interfaces is experimentally evaluated for a bolt-connection model Damage monitoring method using root mean square deviation(RMSD) index of EM impedance signatures is utilized to estimate the strength of the bolted joint.

• Electronics and Telecommunications Trends
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• v.30 no.5
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• pp.80-88
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• 2015

최근 삼성, 애플, 구글, 마이크로소프트 등 글로벌 IT기업들이 디지털 헬스케어 시장에 뛰어들고 있다. 디지털 헬스케어는 건강상태에 대한 정보를 수집하고 이를 효율적으로 관리함으로써 개인맞춤형 건강관리 및 의료서비스 제공이 가능한 ICT융합 건강관리 서비스 및 기기로 건강관리서비스의 주도권이 의료영역에서 일반 소비영역으로 확대된 형태라고 할 수 있다. 본고에서는 디지털 헬스케어 선점을 위해 최근 경쟁이 가속화되고 있는 개인건강정보 플랫폼의 동향에 대하여 알아보았다. 삼성전자 애플, 구글, 마이크로소프트 등 국내외 글로벌 IT기업들의 개인건강정보 플랫폼과 한국전자통신연구원(ETRI)에서 미래창조과학부의 지원으로 개발 중인 개인건강정보 기반 개방형 ICT힐링 서비스 플랫폼에 대하여 살펴보았다.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.275-276
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• 2006

선박 및 해양기자재의 안전 진단을 위한 기존의 기술은 접 센서(point sensor)를 이용한 변형률 측정 기술이 대부분이라 할 수 있다. 본 논문은 기존의 기술보다 효율적으로 응용될 수 있는 광섬유 센서를 이용한 분포 개념의 온도 및 변형률 측정(DTSS: Distributed Temperature & Strain Sensing) 기술에 대해 소개하고 있다. 이 기술은 선체 응력 모니터링, 해양 구조물 안전진단, subsea flowline 모니터링, platform의 riser 안정성, umbilical 모니터링 등에 활용될 수 있다.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.89-100
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• 2014

Construction victims have increased year by year. Disaster proportion is also increasing continuously. Looking over the causes of disasters by each type of work, fall from working platform indicate the highest rate above all so that it is urgently required to set up safety measures. This study is to grasp the present status of construction accidents, to identify areal characteristics of the top 20% accidents on the basis of working platforms with the highest accident rate, to grasp the causes of accidents after their analyses, and to present methods to reduce casualties related to working platforms. As measures to reduce construction disasters, this study proposes to improve safety management and training on working platforms, to complement safety regulations, and to better performance including the development and expansion of certified products suitable for safety regulations.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.185-191
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• 2005

In this paper, we proposed a downscaled 3D object technique using medical images for telediagnostic use. The proposed system consisted of downscaling/thresholding processes for building a downscaled 3D object and a process for obtaining 2D images at specific angles for diagnosis support. We used 80 slices of Digital Imaging and Communication in Medicine(DICOM) CT images as sample images and the platform-independent Java language for the experiment. We confirmed that the total image set size and transmission time of the original DICOM image set using a down-scaled 3D object decreased approximately $99\%\;and\;98.41\%,$ respectively. With additional studies, the proposed technique obtained from these results will become useful in supporting diagnosis for home and hospital care.