• Journal of Digital Convergence
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• v.17 no.7
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• pp.285-292
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• 2019

With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.

• International Area Studies Review
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• v.16 no.3
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• pp.239-266
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• 2012

The purpose of this paper is to suggest desirable improvement for KRX derivatives market plagued with many problems in spite of its world level of quantitative growth. In order to try to find desirable improvement for KRX derivatives market which has many problems like that, I suggest various ways of improvement for regulatory system in the future in terms of behavioral regulation for investor protection. First of all, in order to relieve speculative tendency of trading, KOSPI200 option market with ATM-oriented option trading needs to be induced from the market in which OTM-oriented option is now trading. So discount or exemption of brokerage fee for ATM trading and the introduction of market-maker for ATM type can be considered. For the protection of individual investors, we suggest feasible plans such as differential regulation between professional and individual investors, consolidation of basic deposit management, and enlargement of opportunities for risk management education & simulation trading.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.24 no.2
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• pp.135-144
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• 2021

Purpose: Although ultrasonography is the gold standard of diagnosing intussusception, plain abdomen radiograph (AXR) is often used to make differential diagnosis for pediatric patients with abdominal pain. In intussusception patients, we aimed to analyze the AXR and clinical data to determine the characteristics of early AXR findings associated with diagnosis of intussusception and recurrence after reduction. Methods: Between January 2011 and June 2018, 446 patients diagnosed with intussusception based on International Classification of Diseases-10 code of K56.1 were admitted. We retrospectively reviewed medical records of 398 patients who received air reduction; 51 of them have recurred after initial reduction. We evaluated six AXR features including absent ascending colon gas, absent transverse colon gas, target sign, meniscus sign, mass, and ileus. Clinical data and AXR features were compared between single episode and recurrence groups. Results: Two groups did not show significant differences regarding clinical data. Mean time to recurrence from air reduction was 3.4±3.2 days. Absent ascending colon gas (63.9%) was the most common feature in intussusception, followed by mass (29.1%). All of six AXR features were observed more frequently in the recurrence group. Absent transverse colon gas was the most closely associated AXR finding for recurrence (odds ratio, 2.964; 95% confidence interval, 1.327-6.618; p=0.008). Conclusion: In our study, absence of ascending colon gas was the most frequently seen AXR factor in intussusception patients. Extended and careful observation after reduction may be beneficial if such finding on AXR is found in intussusception patients.

• Journal of the Korean Society of Safety
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• v.35 no.6
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• pp.85-92
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• 2020

Wet Scrubber reacts the incoming pollutant gas with cleaning water (water + absorbent) to absorb pollutants and release the clean air to the atmosphere. Wet scrubbers and packed tower scrubbers using this principle are widely used in businesses that emit acid gases. In particular, in the etching process using hydrochloric acid (HCl), alkaline washing water (NaOH) having a pH of about 8 to 11 is used to absorb a large amount of acid gas. However, These salts are attached to the injection nozzle (nozzle), filling material (packing), and the demister (Demister), causing air pollution, human damage, and inoperability due to clogging and acid gas discharge. Therefore, In this study, an improvement plan was proposed to manage the washing water with pH 3~4 acidic washing water. The test method takes samples from the Wet Scrubber flue measurement laboratory twice a month for 1 year. Hydrogen chloride (HCl) concentration (ppm) was measured, and nozzle clogging and scale conditions were measured, compared, and analyzed through a differential pressure gauge and a pressure gauge. As a result of the check, it was visually confirmed that the scale was reduced to 50% or less in the spray nozzle, filler, and demister. In addition, the emission limit of hydrogen chloride in accordance with the Enforcement Regulation of the Air Quality Conservation Act [Annex 8] met 3 ppm or less. Therefore, even if the washing water is operated in an acidic pH range of 3 to 4, it is expected to reduce air pollution and human damage due to clogging of internal parts, and it is expected to reduce maintenance costs such as regular cleaning or replacement of parts.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.17-22
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• 2022

To reduce the bump of bridge/earthwork transition area caused by the settlement of the soft ground during public use, the road agencies have been continuously overlay or repavement at those areas. In this study, the vehicle-mounted ground penetrating radar with 1GHz air-coupled antenna was used to estimate the settlement amount of those areas for nine bridges built in the soft ground. Results shows that it is possible to effectively measure the thickness of pavement up to a depth of 1 m on an asphalt road with ground penetrating radar technology that can inspect under the road surface. Distinctively deformation of the road surface, the variation in the thickness of the pavement measured at bridge/earth transition areas is equivalent to a minimum of 50 mm and a maximum of 600 mm, and there is a risk of cavity in the ground. The difference in the increased pavement thickness is 50~250 mm for each bridge connection, which may cause the differential settlement. In this study, by using the result of the ground penetration radar, a plan for improving drivability and maintenance of the settlement is suggested and applied to the field.

• Journal of the Korean Orthopaedic Association
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• v.56 no.4
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• pp.351-356
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• 2021

A 67-year-old male patient with a history of epididymectomy and anti-tuberculosis treatment for epididymis tuberculosis was admitted for acute low back pain and radiating pain. The patient had no history of gout but showed hyperuricemia and a bone destruction lesion in the facet joint and lamina of the lumbar spine. A histology examination was performed after a computed tomography-guided needle biopsy, and the findings were compatible with gout spondyloarthropathy and tuberculous spondylitis. The acute symptoms improved after conservative treatment for gouty arthritis. When patients with hyperuricemia risk factors, such as taking anti-tuberculosis drugs, complain of acute low back pain, gout spondyloarthropathy should be considered in a differential diagnosis.

• Journal of Genetic Medicine
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• v.19 no.2
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• pp.63-75
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• 2022

Purpose: Osteoporosis is a common calcium and metabolic skeletal disease which is characterized by decreased bone mass, microarchitectural deterioration of bone tissue and impaired bone strength, thereby leading to enhanced risk of bone fragility. In this study, we aimed to identify novel genes for susceptibility to osteoporosis and/or bone density. Materials and Methods: To identify differentially expressed genes (DEGs) between control and osteoporosis-induced cells, annealing control primer-based differential display reverse-transcription polymerase chain reaction (RT-PCR) was carried out in pre-osteoblast MC3T3-E1 cells. Expression levels of the identified DEGs were evaluated by quantitative RT-PCR. Association studies for the quantitative bone density analysis and osteoporosis case-control analysis of single nucleotide polymorphism (SNPs) were performed in Korean women (3,570 subjects) from the Korean Association REsource (KARE) study cohort. Results: Comparison analysis of expression levels of the identified DEGs by quantitative RT-PCR found seven genes, Anxa6, Col5a1, Col6a2, Eno1, Myof, Nfib, and Scara5, that showed significantly different expression between the dexamethason-treated and untreated MC3T3-E1 cells and between the ovariectomized osteoporosis-induced mice and sham mice. Association studies revealed that there was a significant association between the SNPs in the five genes, ANXA6, COL5A1, ENO1, MYOF, and SCARA5, and bone density and/or osteoporosis. Conclusion: Using a whole-genome comparative expression analysis, gene expression evaluation analysis, and association analysis, we found five genes that were significantly associated with bone density and/or osteoporosis. Notably, the association P-values of the SNPs in the ANXA6 and COL5A1 genes were below the Bonferroni-corrected significance level.

• Smart Media Journal
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• v.12 no.11
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• pp.36-47
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• 2023

Industrial Control System(ICS), which controls facilities at major industrial sites, is increasingly connected to other systems through networks. With this integration and the development of intelligent attacks that can lead to a single external intrusion as a whole system paralysis, the risk and impact of security on industrial control systems are increasing. As a result, research on how to protect and detect cyber attacks is actively underway, and deep learning models in the form of unsupervised learning have achieved a lot, and many abnormal detection technologies based on deep learning are being introduced. In this study, we emphasize the application of preprocessing methodologies to enhance the anomaly detection performance of deep learning models on time series data. The results demonstrate the effectiveness of a Wavelet Transform (WT)-based noise reduction methodology as a preprocessing technique for deep learning-based anomaly detection. Particularly, by incorporating sensor characteristics through clustering, the differential application of the Dual-Tree Complex Wavelet Transform proves to be the most effective approach in improving the detection performance of cyber attacks.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.7.1-7.14
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• 2023

Background: At present, no short standard questionnaire exists for assessing and comparing major work organization hazards in the workplaces of the United States. Methods: We conducted a series of psychometric tests (content validity, factor analysis, differential-item functioning analysis, reliability, and concurrent validity) to validate and identify core items and scales for major work organization hazards using the data from the 2002-2014 General Social Surveys (GSSs), including the Quality of Worklife (QWL) questionnaire. In addition, an extensive literature review was undertaken to find other major work organization hazards which were not addressed in the GSS. Results: Although the overall validity of the GSS-QWL questionnaire was satisfactory in the psychometric tests, some GSS-QWL items of work-family conflict, psychological job demands, job insecurity, use of skills on the job, and safety climate scales appeared to be weak. In the end, 33 questions (31 GSS-QWL and 2 GSS) were chosen as the least, but best validated core questions and included in a new short standard questionnaire (called the Healthy Work Survey [HWS]). And their national norms were established for comparisons. Furthermore, based on the literature review, fifteen more questions for assessing other significant work organization hazards (e.g., lack of scheduling control, emotional demands, electronic surveillance, wage theft) were included in the new questionnaire. Thus, the HWS includes 48 questions in total for assessing traditional and emerging work organization hazards, which covers seven theoretical domains: work schedule/arrangement, control, support, reward, demands, safety, and justice. Conclusions: The HWS is a short standard questionnaire for assessing work organization hazards which can be used as a first step toward the risk management of major work organization hazards in the workplaces of the US.

• Smart Structures and Systems
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• v.33 no.2
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• pp.165-175
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• 2024

Rotating beams play a crucial role in representing complex mechanical components that are prevalent in vital sectors like energy and transportation industries. These components are susceptible to the initiation and propagation of cracks, posing a substantial risk to their structural integrity. This study presents a two-stage methodology for detecting the location and estimating the size of an open-edge transverse crack in a rotating Euler-Bernoulli beam with a uniform cross-section. Understanding the dynamic behavior of beams is vital for the effective design and evaluation of their operational performance. In this regard, modal parameters such as natural frequencies and eigenmodes are frequently employed to detect and identify damages in mechanical components. In this instance, the Frobenius method has been employed to determine the first two natural frequencies and corresponding eigenmodes associated with flapwise bending vibration. These calculations have been performed by solving the governing differential equation that describes the motion of the beam. Various parameters have been considered, such as rotational speed, beam slenderness, hub radius, and crack size and location. The effect of the crack has been replaced by a rotational spring whose stiffness represents the increase in local flexibility as a result of the damage presence. In the initial phase of the proposed methodology, a damage index utilizing the slope of the beam's eigenmode has been employed to estimate the location of the crack. After detecting the presence of damage, the size of the crack is determined using a Genetic Algorithm optimization technique. The ultimate goal of the proposed methodology is to enable the development of more suitable and reliable maintenance plans.