• Molecules and Cells
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• v.42 no.4
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• pp.301-312
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• 2019

Post-transcriptional regulation underlies the circadian control of gene expression and animal behaviors. However, the role of mRNA surveillance via the nonsense-mediated mRNA decay (NMD) pathway in circadian rhythms remains elusive. Here, we report that Drosophila NMD pathway acts in a subset of circadian pacemaker neurons to maintain robust 24 h rhythms of free-running locomotor activity. RNA interference-mediated depletion of key NMD factors in timeless-expressing clock cells decreased the amplitude of circadian locomotor behaviors. Transgenic manipulation of the NMD pathway in clock neurons expressing a neuropeptide PIGMENT-DISPERSING FACTOR (PDF) was sufficient to dampen or lengthen free-running locomotor rhythms. Confocal imaging of a transgenic NMD reporter revealed that arrhythmic Clock mutants exhibited stronger NMD activity in PDF-expressing neurons than wild-type. We further found that hypomorphic mutations in Suppressor with morphogenetic effect on genitalia 5 (Smg5) or Smg6 impaired circadian behaviors. These NMD mutants normally developed PDF-expressing clock neurons and displayed daily oscillations in the transcript levels of core clock genes. By contrast, the loss of Smg5 or Smg6 function affected the relative transcript levels of cAMP response element-binding protein B (CrebB) in an isoform-specific manner. Moreover, the overexpression of a transcriptional repressor form of CrebB rescued free-running locomotor rhythms in Smg5-depleted flies. These data demonstrate that CrebB is a rate-limiting substrate of the genetic NMD pathway important for the behavioral output of circadian clocks in Drosophila.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.711-732
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• 2019

Many unmanned aerial vehicle (UAV) applications have been employed for performing data collection in facilitating tasks such as surveillance and monitoring objectives in remote and dangerous environments. In light of the fact that most of the existing UAV relaying applications operate in conventional half-duplex (HD) mode, a full-duplex (FD) based UAV relay aided wireless network is investigated, in which the UAV relay helps forwarding information from the source (S) node to the destination (D). Since the activated UAV relays are always floating and flying in the air, its channel state information (CSI) as well as channel capacity is a time-variant parameter. Considering decode-and-forward (DF) relaying protocol in UAV relays, the cooperative relaying channel capacity is constrained by the relatively weaker one (i.e. in terms of signal-to-noise ratio (SNR) or signal-to-interference-plus-noise ratio (SINR)) between S-to-relay and relay-to-D links. The channel capacity can be optimized by adaptively optimizing the transmit power of S and/or UAV relay. Furthermore, a hybrid HD/FD mode is enabled in the proposed UAV relays for adaptively optimizing the channel utilization subject to the instantaneous CSI and/or remaining self-interference (SI) levels. Numerical results show that the channel capacity of the proposed UAV relay aided wireless networks can be maximized by adaptively responding to the influence of various real-time factors.

• Journal of Gynecologic Oncology
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• v.29 no.6
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• pp.91.1-91.12
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• 2018

Objective: To examine the association between tumor grade and survival for women with squamous cervical cancer. Methods: This retrospective observational study utilized the Surveillance, Epidemiology, and End Result program data between 1983 and 2013 to examine women with squamous cervical cancer with known tumor differentiation grade. Multivariable analyses were performed to assess independent associations between tumor differentiation grade and survival. Results: A total of 31,536 women were identified including 15,175 (48.1%) with grade 3 tumors, 14,084 (44.7%) with grade 2 neoplasms and 2,277 (7.2%) with grade 1 tumors. Higher tumor grade was significantly associated with older age, higher stage disease, larger tumor size, and lymph node metastasis (all, p<0.001). In a multivariable analysis, grade 2 tumors (adjusted-hazard ratio [HR]=1.21; p<0.001) and grade 3 tumors (adjusted-HR=1.45; p<0.001) were independently associated with decreased cause-specific survival (CSS) compared to grade 1 tumors. Among the 7,429 women with stage II-III disease who received radiotherapy without surgical treatment, grade 3 tumors were independently associated with decreased CSS compared to grade 2 tumors (adjusted-HR=1.16; p<0.001). Among 4,045 women with node-negative stage I disease and tumor size ${\leq}4cm$ who underwent surgical treatment without radiotherapy, grade 2 tumors (adjusted-HR=2.54; p=0.028) and grade 3 tumors (adjusted-HR=4.48; p<0.001) were independently associated with decreased CSS compared to grade 1 tumors. Conclusion: Our study suggests that tumor differentiation grade may be a prognostic factor in women with squamous cervical cancer, particularly in early-stage disease. Higher tumor grade was associated with poorer survival.

• The Journal of Information Systems
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• v.30 no.1
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• pp.65-84
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• 2021

Purpose Based on the development of artificial intelligence and big data technologies, the RegTech has been emerged to reduce regulatory costs and to enable efficient supervision by regulatory bodies. The word RegTech is a combination of regulation and technology, which means using the technological methods to facilitate the implementation of regulations and to make efficient surveillance and supervision of regulations. The purpose of this study is to describe the recent adoption of RegTech and to provide basic examples of applying RegTech to capital market regulations. Design/methodology/approach English-based ontology and deep learning technologies are quite developed in practice, and it will not be difficult to expand it to European or Latin American languages that are grammatically similar to English. However, it is not easy to use it in most Asian languages such as Korean, which have different grammatical rules. In addition, in the early stages of adoption, companies, financial institutions and regulators will not be familiar with this machine-based reporting system. There is a need to establish an ecosystem which facilitates the adoption of RegTech by consulting and supporting the stakeholders. In this paper, we provide a simple example that shows a procedure of applying RegTech to recognize and interpret Korean language-based capital market regulations. Specifically, we present the process of converting sentences in regulations into a meta-language through the morpheme analyses. We next conduct deep learning analyses to determine whether a regulatory sentence exists in each regulatory paragraph. Findings This study illustrates the applicability of RegTech-based ontology and deep learning technologies in Korean-based capital market regulations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.214-220
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• 2021

SUGVs (Small Unmanned Ground Vehicles) are being used to conduct dangerous missions, such as EOD (explosive ordinance disposal), counter-terrorism operations, fire extinguishing and fire-fighting reconnaissance, reconnaissance of disaster areas, and surveillance of contact areas. Technology leading countries, the United States, United Kingdom, France, Germany, and Israel, have developed and operated various SUGVs for use in the military and civilian fields. The developed system was upgraded further based on additional requirements associated with data collected during the actual operation. The development trends of technology leading countries are an important indicator for the future development of SUGVs. In this study, the development trends and missions of SUGVs operating in the technology leading countries were analyzed. Based on the development trends of SUGVs in these countries, this paper discusses the features and design characteristics needed for the development of SUGVs in future military and civilian domains.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.35-42
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• 2021

In this paper, we propose a deep learning-based person re-identification method using a three-dimensional RGB-Depth Xtion2 camera considering joint coordinates and dynamic features(velocity, acceleration). The main idea of the proposed identification methodology is to easily extract gait data such as joint coordinates, dynamic features with an RGB-D camera and automatically identify gait patterns through a self-designed one-dimensional convolutional neural network classifier(1D-ConvNet). The accuracy was measured based on the F1 Score, and the influence was measured by comparing the accuracy with the classifier model (JC) that did not consider dynamic characteristics. As a result, our proposed classifier model in the case of considering the dynamic characteristics(JCSpeed) showed about 8% higher F1-Score than JC.

• Pediatric Infection and Vaccine
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• v.27 no.3
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• pp.180-183
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• 2020

Purpose: To describe pediatric coronavirus disease 2019 (COVID-19) cases after the reopening of schools in the Republic of Korea and their transmission routes. Methods: All case report forms and epidemiologic investigation forms for children aged 3-18 years reported as COVID-19 cases to the National Notifiable Disease Surveillance System from May 1 to July 12, 2020, were reviewed. Results: After the schools were reopened in May 2020, a total of 127 pediatric COVID-19 cases were confirmed until July 12. Of these, 59 children (46%) were exposed to severe acute respiratory syndrome coronavirus 2 through family and relatives, followed by 18 children (14%) through cram schools or private lessons, 8 children (6%) through multi-use facilities, and 3 children (2%) through school. Conclusions: The present data do not suggest an increased risk of COVID-19 transmission in the context of stringent school-based infection prevention measures introduced across the country.

• Korean Journal of Clinical Laboratory Science
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• v.53 no.1
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• pp.11-18
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• 2021

Respiratory viruses (RVs) cause infections in hospital environments through direct contact with infected visitors. In infection control, it causes major problems of acquired infections in hospitals by respiratory viruses. The surveillance data derived from clinical laboratories are often used to properly allocate medical resources to hospitals and communities for treatment, consumables, and diagnostic product purchases in the institutions and public health sectors that provide health care. An early diagnosis is essential in infection with respiratory viruses, and methods that can be used in diagnostic methods using respiratory samples include virus culture, molecular diagnosis, and analysis. A microchip provides a new strategy for developing a more diverse and powerful technology called point-of-care testing. The importance of the respiratory system should be applied strictly to the infection control guidelines to ensure the occupational health and safety of health care workers. Evidence of clinical efficacy, including this study, is challenging the long-standing paradigm for infection propagation. Additional assistance will be needed for frequent tests to detect respiratory viruses in inpatients who have begun to show new respiratory symptoms indicating infections requiring efforts to control the infection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.619-627
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• 2021

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test.

• Parasites, Hosts and Diseases
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• v.60 no.5
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• pp.327-338
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• 2022

This study determined the recent status and trend of Pneumocystis jirovecii pneumonia (PcP) in the non-human immunodeficiency virus (HIV) (non-HIV-PcP) and HIV (HIV-PcP) infected populations using data from the Health Insurance Review & Assessment Service (HIRA) and the Korea Disease Control and Prevention Agency (KDCA). SaTScan and Join-point were used for statistical analyses. Non-HIV-PcP cases showed an upward trend during the study period from 2010 to 2021, with the largest number in 2021 (551 cases). The upward trend was similar until 2020 after adjusting for the population. Seoul had the highest number of cases (1,597) in the non-HIV-PcP group, which was the same after adjusting for the population (162 cases/1,000,000). It was followed by Jeju-do (89 cases/1,000,000). The most likely cluster (MLC) for the non-HIV-PCP group was Seoul (Relative Risk (RR)=4.59, Log Likelihood Ratio (LLR)=825.531), followed by Jeju-do (RR=1.59, LLR=5.431). An upward trend was observed among the non-HIV-PcP group in the Jeju-do/Jeollanam-do/Jeollabuk-do/Gyeongsangnam-do/Busan/Daejeon/Daegu/Ulsan joint cluster (29.02%, LLR=11.638, P<0.001) located in the southern part of Korea. Both women and men in the non-HIV groups showed an overall upward trend of PcP during the study period. Men in the 60-69 age group had the highest annual percentage change (APC 41.8) during 2014-2019. In contrast, the HIV groups showed a falling trend of PcP recently. Men in the 60-69 age group had the most decrease (APC -17.6) during 2018-2021. This study provides an analytic basis for health measures and a nationwide epidemiological surveillance system for the management of PcP.