• Title/Summary/Keyword: convergence technology

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The Analysis of Investment Determinants in Angel Investors: Focus on the Financial Characteristics (엔젤투자자의 투자의사 결정요인 분석: 재무적 특성을 중심으로)

  • Sang Chang Lee;Byungkwon Lim;Chun-Kyu Kim
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.6
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    • pp.147-157
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    • 2023
  • This paper investigates the financial factors affecting angel investors' investment decisions for 818 firms from 2009 to 2018 in the Korean venture investment market. We construct a quasi-experimental design using propensity scoring matching and compare the investment determinants between investment firms and matching firms. The main empirical findings are as follows. First, we find that angel investors are more likely to choose firms based on a firm's growth such as profit and assets rather than profitability or financial stability. In addition, we identify that they prefer the firm not only higher intangible assets but also higher R&D expenditures. Second, we find that angel investors consider both growth and activity ratios in the firms for over three years and have entered the mid-stage of startups. Overall, we confirm that the investment decision of angel investors mainly focuses on the venture startups' growth trend or future growth potential rather than the realized profitability or financial stability. We also infer that the possibility of performance creation is an important investment factor along with growth for the mid-stage startup.

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An Analysis of the Support Policy for Small Businesses in the Post-Covid-19 Era Using the LDA Topic Model (LDA 토픽 모델을 활용한 포스트 Covid-19 시대의 소상공인 지원정책 분석)

  • Kyung-Do Suh;Jung-il Choi;Pan-Am Choi;Jaerim Jung
    • Journal of Industrial Convergence
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    • v.22 no.6
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    • pp.51-59
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    • 2024
  • The purpose of the paper is to suggest government policies that are practically helpful to small business owners in pandemic situations such as COVID-19. To this end, keyword frequency analysis and word cloud analysis of text mining analysis were performed by crawling news articles centered on the keywords "COVID-19 Support for Small Businesses", "The Impact of Small Businesses by Response System to COVID-19 Infectious Diseases", and "COVID-19 Small Business Economic Policy", and major issues were identified through LDA topic modeling analysis. As a result of conducting LDA topic modeling, the support policy for small business owners formed a topic label with government cash and financial support, and the impact of small business owners according to the COVID-19 infectious disease response system formed a topic label with a government-led quarantine system and an individual-led quarantine system, and the COVID-19 economic policy formed a topic label with a policy for small business owners to acquire economic crisis and self-sustainability. Focusing on the organized topic label, it was intended to provide basic data for small business owners to understand the damage reduction policy for small business owners and the policy for enhancing market competitiveness in the future pandemic situation.

The Impact of Nomad Physical Activity Through Online Videos of Active Seniors on Physical Self-Perception and Successful Aging (엑티브시니어의 온라인 동영상을 통한 노마드 체육활동이 신체적자기지각과 성공적 노화에 미치는 영향)

  • Hye-young Hwang;Soo-Jin Seo;Hyun-Kyoung Kim;Hey-Jin Kim;Heung-Tae Kim
    • Journal of Industrial Convergence
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    • v.22 no.6
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    • pp.81-88
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    • 2024
  • The purpose of this study is to provide academic basic data by identifying the effects of active seniors' online video physical activity on physical self-perception and successful aging. In order to achieve the purpose of this study, 10 active seniors in D city were selected, and after receiving consent to participate in online video physical activity, it was divided into pre and post, and from March 14 to April 22, 2022, Kakao Talk group chat was opened to watch online physical activity videos during the 12th session, download 2 videos a week, and exercise from Monday to Friday. To solve the research problem, frequency analysis and paired t-test were conducted using the SPSS Ver20.0 statistical program. As a result, first, as a result of analyzing the pre- and post-tests of physical self-perception through physical activity of active seniors, all of face satisfaction, body satisfaction, change in physical strength, and change in disease increased on average. Second, as a result of pre- and post-analysis of active seniors' successful aging through physical activity, acceptance of others, orientation toward self-fulfillment, self-acceptance, and satisfaction with children increased, but autonomous life and active participation in life decreased. Through these results, in the COVID-19 period, when activities were restricted due to social distancing, active seniors' online video physical activity has a positive effect on physical self-perception and successful aging, and various programs that can be active on their own should be developed in the future.

Analysis and Study for Appropriate Deep Neural Network Structures and Self-Supervised Learning-based Brain Signal Data Representation Methods (딥 뉴럴 네트워크의 적절한 구조 및 자가-지도 학습 방법에 따른 뇌신호 데이터 표현 기술 분석 및 고찰)

  • Won-Jun Ko
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.137-142
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    • 2024
  • Recently, deep learning technology has become those methods as de facto standards in the area of medical data representation. But, deep learning inherently requires a large amount of training data, which poses a challenge for its direct application in the medical field where acquiring large-scale data is not straightforward. Additionally, brain signal modalities also suffer from these problems owing to the high variability. Research has focused on designing deep neural network structures capable of effectively extracting spectro-spatio-temporal characteristics of brain signals, or employing self-supervised learning methods to pre-learn the neurophysiological features of brain signals. This paper analyzes methodologies used to handle small-scale data in emerging fields such as brain-computer interfaces and brain signal-based state prediction, presenting future directions for these technologies. At first, this paper examines deep neural network structures for representing brain signals, then analyzes self-supervised learning methodologies aimed at efficiently learning the characteristics of brain signals. Finally, the paper discusses key insights and future directions for deep learning-based brain signal analysis.

Process Optimization for the Industrialization of Transparent Conducting Film (투명 전도막의 산업화를 위한 공정 최적화)

  • Nam, Hyeon-bin;Choi, Yo-seok;Kim, In-su;Kim, Gyung-jun;Park, Seong-su;Lee, Ja Hyun
    • Industry Promotion Research
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    • v.9 no.1
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    • pp.21-29
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    • 2024
  • In the rapidly advancing information society, electronic devices, including smartphones and tablets, are increasingly digitized and equipped with high-performance features such as flexible displays. This study focused on optimizing the manufacturing process for Transparent Conductive Films (TCF) by using the cost-effective conductive polymer PEDOT and transparent substrate PET as alternatives to expensive materials in flexible display technology. The variables considered are production speed (m/min), coating maximum temperature (℃), and PEDOT supply speed (rpm), with surface resistivity (Ω/□) as the response parameter, using Response Surface Methodology (RSM). Optimization results indicate the ideal conditions for production: a speed of 22.16 m/min, coating temperature of 125.28℃, and PEDOT supply at 522.79 rpm. Statistical analysis validates the reliability of the results (F value: 18.37, P-value: < 0.0001, R2: 0.9430). Under optimal conditions, the predicted surface resistivity is 145.75 Ω/□, closely aligned with the experimental value of 142.97 Ω/□. Applying these findings to mass production processes is expected to enhance production yields and decrease defect rates compared to current practices. This research provides valuable insights for the advancement of flexible display manufacturing.

Imaging Findings of Peripheral Arterial Disease on Lower-Extremity CT Angiography Using a Virtual Monoenergetic Imaging Algorithm (가상의 단일 에너지 영상 재구성 기법을 이용한 하지 단층촬영 혈관조영술에서 말초 동맥 질환 영상 소견)

  • Jun Seong Kim;So Hyun Park;Suyoung Park;Jung Han Hwang;Jeong Ho Kim;Seong Yong Pak;Kihyun Lee;Bernhard Schmidt
    • Journal of the Korean Society of Radiology
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    • v.83 no.5
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    • pp.1032-1045
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    • 2022
  • Peripheral arterial disease (PAD) is common in elderly patients. Lower-extremity CT angiography (LE-CTA) can be useful for detecting PAD and planning its treatment. PAD can also be accurately evaluated on reconstructed monoenergetic images (MEIs) from low kiloelectron volt (keV) to high keV images using dual-energy CT. Low keV images generally provide higher contrast than high keV images but also feature more severe image noise. The noise-reduced virtual MEI reconstruction algorithm, called the Mono+ technique, was recently introduced to overcome such image noise. Therefore, this pictorial review aimed to present the imaging findings of PAD on LE-CTA and compare low and high keV images with those subjected to the Mono+ technique. We found that, in many cases, the overall and segmental image qualities were better and metal artifacts and venous contamination were decreased in the high keV images.

Radiology Residents' Independent Diagnosis of Appendicitis Using 2-mSv Computed Tomography: A Secondary Analysis of a Large Pragmatic Randomized Trial

  • Jungheum Cho;Hae Young Kim;Seungjae Lee;Ji Hoon Park;Kyoung Ho Lee
    • Korean Journal of Radiology
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    • v.24 no.6
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    • pp.529-540
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    • 2023
  • Objective: To compare the diagnostic performance and clinical outcomes of 2-mSv computed tomography (CT) and conventional-dose CT (CDCT), following radiology residents' interpretation of CT examinations for suspected appendicitis. Materials and Methods: Altogether, 3074 patients with suspected appendicitis aged 15-44 years (28 ± 9 years, 1672 females) from 20 hospitals were randomly assigned to the 2-mSv CT (n = 1535) or CDCT (n = 1539) groups in a pragmatic trial from December 2013 and August 2016. Overall, 107 radiology residents participated in the trial as readers in the form of daily practice after online training for 2-mSv CT. They made preliminary CT reports, which were later finalized by attending radiologists via addendum reports, for 640 and 657 patients in the 2-mSv CT and CDCT groups, respectively. We compared the diagnostic performance of the residents, discrepancies between preliminary and addendum reports, and clinical outcomes between the two groups. Results: Patient characteristics were similar between the 640 and 657 patients. Residents' diagnostic performance was not significantly different between the 2-mSv CT and CDCT groups, with a sensitivity of 96.0% and 97.1%, respectively (difference [95% confidence interval {CI}], -1.1% [-4.9%, 2.6%]; P = 0.69) and specificity of 93.2% and 93.1%, respectively (0.1% [-3.6%, 3.7%]; P > 0.99). The 2-mSv CT and CDCT groups did not significantly differ in discrepancies between the preliminary and addendum reports regarding the presence of appendicitis (3.3% vs. 5.2%; -1.9% [-4.2%, 0.4%]; P = 0.12) and alternative diagnosis (5.5% vs. 6.4%; -0.9% [-3.6%, 1.8%]; P = 0.56). The rates of perforated appendicitis (12.0% vs. 12.6%; -0.6% [-4.3%, 3.1%]; P = 0.81) and negative appendectomies (1.9% vs. 1.1%; 0.8% [-0.7%, 2.3%]; P = 0.33) were not significantly different between the two groups. Conclusion: Diagnostic performance and clinical outcomes were not significantly different between the 2-mSv CT and CDCT groups following radiology residents' CT readings for suspected appendicitis.

Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels

  • Pyeong Hwa Kim;Hee Mang Yoon;Jeong Rye Kim;Jae-Yeon Hwang;Jin-Ho Choi;Jisun Hwang;Jaewon Lee;Jinkyeong Sung;Kyu-Hwan Jung;Byeonguk Bae;Ah Young Jung;Young Ah Cho;Woo Hyun Shim;Boram Bak;Jin Seong Lee
    • Korean Journal of Radiology
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    • v.24 no.11
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    • pp.1151-1163
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    • 2023
  • Objective: To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model. Materials and Methods: A convolutional neural network was trained to predict age according to the bone development shown on a hand radiograph (bone age) using 21036 hand radiographs of Korean children and adolescents without known bone development-affecting diseases/conditions obtained between 1998 and 2019 (median age [interquartile range {IQR}], 9 [7-12] years; male:female, 11794:9242) and their chronological ages as labels (Korean model). We constructed 2 separate external datasets consisting of Korean children and adolescents with healthy bone development (Institution 1: n = 343; median age [IQR], 10 [4-15] years; male: female, 183:160; Institution 2: n = 321; median age [IQR], 9 [5-14] years; male: female, 164:157) to test the model performance. The mean absolute error (MAE), root mean square error (RMSE), and proportions of bone age predictions within 6, 12, 18, and 24 months of the reference age (chronological age) were compared between the Korean model and a commercial model (VUNO Med-BoneAge version 1.1; VUNO) trained with Greulich-Pyle-based age as the label (GP-based model). Results: Compared with the GP-based model, the Korean model showed a lower RMSE (11.2 vs. 13.8 months; P = 0.004) and MAE (8.2 vs. 10.5 months; P = 0.002), a higher proportion of bone age predictions within 18 months of chronological age (88.3% vs. 82.2%; P = 0.031) for Institution 1, and a lower MAE (9.5 vs. 11.0 months; P = 0.022) and higher proportion of bone age predictions within 6 months (44.5% vs. 36.4%; P = 0.044) for Institution 2. Conclusion: The Korean model trained using the chronological ages of Korean children and adolescents without known bone development-affecting diseases/conditions as labels performed better in bone age assessment than the GP-based model in the Korean pediatric population. Further validation is required to confirm its accuracy.

Appendiceal Visualization on 2-mSv CT vs. Conventional-Dose CT in Adolescents and Young Adults with Suspected Appendicitis: An Analysis of Large Pragmatic Randomized Trial Data

  • Jungheum Cho;Youngjune Kim;Seungjae Lee;Hooney Daniel Min;Yousun Ko;Choong Guen Chee;Hae Young Kim;Ji Hoon Park;Kyoung Ho Lee;LOCAT Group
    • Korean Journal of Radiology
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    • v.23 no.4
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    • pp.413-425
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    • 2022
  • Objective: We compared appendiceal visualization on 2-mSv CT vs. conventional-dose CT (median 7 mSv) in adolescents and young adults and analyzed the undesirable clinical and diagnostic outcomes that followed appendiceal nonvisualization. Materials and Methods: A total of 3074 patients aged 15-44 years (mean ± standard deviation, 28 ± 9 years; 1672 female) from 20 hospitals were randomized to the 2-mSv CT or conventional-dose CT group (1535 vs. 1539) from December 2013 through August 2016. A total of 161 radiologists from 20 institutions prospectively rated appendiceal visualization (grade 0, not identified; grade 1, unsure or partly visualized; and grade 2, clearly and entirely visualized) and the presence of appendicitis in these patients. The final diagnosis was based on CT imaging and surgical, pathologic, and clinical findings. We analyzed undesirable clinical or diagnostic outcomes, such as negative appendectomy, perforated appendicitis, more extensive than simple appendectomy, delay in patient management, or incorrect CT diagnosis, which followed appendiceal nonvisualization (defined as grade 0 or 1) and compared the outcomes between the two groups. Results: In the 2-mSv CT and conventional-dose CT groups, appendiceal visualization was rated as grade 0 in 41 (2.7%) and 18 (1.2%) patients, respectively; grade 1 in 181 (11.8%) and 81 (5.3%) patients, respectively; and grade 2 in 1304 (85.0%) and 1421 (92.3%) patients, respectively (p < 0.001). Overall, undesirable outcomes were rare in both groups. Compared to the conventional-dose CT group, the 2-mSv CT group had slightly higher rates of perforated appendicitis (1.1% [17] vs. 0.5% [7], p = 0.06) and false-negative diagnoses (0.4% [6] vs. 0.0% [0], p = 0.01) following appendiceal nonvisualization. Otherwise, these two groups were comparable. Conclusion: The use of 2-mSv CT instead of conventional-dose CT impairs appendiceal visualization in more patients. However, appendiceal nonvisualization on 2-mSv CT rarely leads to undesirable clinical or diagnostic outcomes.

Diagnostic Accuracy of CT for Evaluating Circumferential Resection Margin Status in Resectable or Borderline Resectable Pancreatic Head Cancer: A Prospective Study Using Axially Sliced Surgical Pathologic Correlation

  • Ji Hoon Park;Yoo-Seok Yoon;Seungjae Lee;Hae Young Kim;Ho-Seong Han;Jun Suh Lee;Won Chang;Haeryoung Kim;Hee Young Na;Seungyeob Han;Kyoung Ho Lee
    • Korean Journal of Radiology
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    • v.23 no.3
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    • pp.322-332
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    • 2022
  • Objective: CT plays a central role in determining the resectability of pancreatic cancer, which directs the use of neoadjuvant therapy. This study aimed to assess the diagnostic accuracy of CT in predicting circumferential resection margin (CRM) involvement in patients with resectable or borderline resectable pancreatic head cancer. Materials and Methods: Seventy-seven patients who were scheduled for upfront surgery for resectable or borderline resectable pancreatic head cancer were prospectively enrolled, and 75 patients (38 male and 37 female; mean age ± standard deviation, 68 ± 11 years) were finally analyzed. The CRM status was evaluated separately for the superior mesenteric artery (SMA) and posterior and superior mesenteric vein/portal vein (SMV/PV) margins. Three independent radiologists reviewed the preoperative CT images and evaluated the resection margin status. The reference standard for CRM status was pathologic examination of pancreaticoduodenectomy specimens in an axial plane perpendicular to the axis of the second portion of the duodenum. The diagnostic accuracy of CT was assessed for overall CRM involvement, defined as involvement of the SMA or posterior margins (per-patient analysis), and involvement of each of the three resection margins (per-margin analysis). The data were pooled using a crossed random effects model. Results: Forty patients had pathologically confirmed overall CRM involvement in pancreatic cancer, while CRM involvement was not seen in 35 patients. For overall CRM involvement, the pooled sensitivity and specificity were 15% (95% confidence interval: 7%-49%) and 99% (96%-100%), respectively. For each of the resection margins, the pooled sensitivity and specificity were 14% (9%-54%) and 99% (38%-100%) for the SMA margin, 12% (8%-46%) and 99% (97%-100%) for the posterior margin; and 37% (29%-53%) and 96% (31%-100%) for the SMV/PV margin, respectively. Conclusion: CT showed very high specificity but low sensitivity in predicting pathological CRM involvement in pancreatic cancer.