• Journal of the Korean Orthopaedic Association
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• v.52 no.1
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• pp.33-39
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• 2017

Purpose: Surgical risks associated with the resection of osteochondroma around the proximal tibia and fibula, as well as the proximal humerus have been well established; however, the clinical presentation and optimal surgical approach for osteochondroma around the lesser trochanter have not been fully addressed. Materials and Methods: Thirteen patients with osteochondroma around the lesser trochanter underwent resection. We described the chief complaint, duration of symptom, location of the tumor, mass protrusion pattern on axial computed tomography image, tumor volume, surgical approach, iliopsoas tendon integrity after resection, and complication according to the each surgical approach. Results: Pain on walking or exercise was the chief complaint in 7 patients, and numbness and radiating pain in 6 patients. The average duration of symptom was 19 months (2-72 months). The surgical approach for 5 tumors that protruded postero-laterally was postero-lateral (n=3), anterior (n=1), and medial (n=1). All 4 patients with antero-medially protruding tumor underwent the anterior approach. Two patients with both antero-medially and postero-laterally protruding tumor received the medial and anterior approach, respectively. Two patients who underwent medial approach for postero-laterally protruded tumor showed extensive cortical defect after resection. One patient who received the anterior approach to resect a large postero-laterally protruded tumor developed complete sciatic nerve palsy, which was recovered 6 months after re-exploration. Conclusion: For large osteochondromas with posterior protrusion, we should not underestimate the probability of sciatic nerve compression. When regarding the optimal surgical approach, the medial one is best suitable for small tumors, while the anterior approach is good for antero-medial or femur neck tumor. For postero-laterally protruded large tumors, posterior approach may minimize the risk of sciatic nerve palsy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.21-35
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• 2023

Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.