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Background Myringotomy with tympanostomy tube insertion (MTI) is a superficial surgical procedure used to prevent hearing loss in children with serous otitis media. Intravenous anesthesia, often ketamine, is preferred for this procedure because of its ability to induce sedation without compromising airway reflexes. However, ketamine alone may be insufficient and potentially lead to spontaneous movement during surgery. This study evaluated the effectiveness of midazolam and fentanyl as adjuvants to ketamine in reducing spontaneous movement during MTI and enhancing the quality of recovery. Methods This study involved two groups of 30 patients each: one group received intravenous ketamine (1.5 mg/kg) with an equal volume of normal saline (K group), while the other received a combination of midazolam, fentanyl, and ketamine (0.05 mg/kg, 1 μg/kg, and 1.5 mg/kg, respectively; MFK group). We assessed side effects, intraoperative patient movement, surgeon satisfaction, and emergence agitation scores. Results The MFK group exhibited significantly lower scores for patient movement (p

OBJECTIVES In the modern era, there is heightened interest in understanding energy expenditure during exercise. Consequently, wearable devices such as the Galaxy Watch and Apple Watch have emerged as pivotal tools for daily health monitoring, given their convenience and increasing popularity. This study aimed to compare the calculated energy expenditure derived from the graded exercise test with readings from Galaxy and Apple Watches during a 30-min exercise session among Korean university students. Through this, we anticipate offering both motivation and clear insights into energy expenditure, thereby potentially aiding in weight management strategies for contemporary individuals. METHODS This study involved 27 college students from Korea National University of Transportation in Chungcheongbuk-do, Korea. We utilized COSMED's exercise load respiratory gas analysis system (Quark-CPET, COSMED, Rome, Italy), along with the Galaxy Watch (Galaxy Watch 5, Samsung, Seoul, Korea) and the Apple Watch (Apple watch series 5, Apple, Cupertino, USA) for measurements. Energy expenditure was monitored in real-time every 5 min throughout the 30-min exercise session. For statistical evaluations, we employed a one-way analysis of variance. Subsequent post-tests utilized the Tukey post-hoc test and Pearson correlation, with a significance level set at p0.05). Conversely, a notable difference was observed when comparing energy expenditure data from the graded exercise test to that of the Apple Watch for time intervals of 10, 15, 20, 25, and 30 min (p>0.05), although the 5-min interval did not exhibit a significant difference (p>0.05). Furthermore, a robust positive correlation was evident between the energy expenditure values derived from the graded exercise test and those from both the Galaxy Watch (r=0.952, p

IEC 61131-3 is an international standard for developing standardized software for automation and control systems. Machine vision systems are a prominent technology in the field of computer vision and are widely used in various industries, such as manufacturing, robotics, healthcare, and automotive, and are often combined with AI technologies. In industrial automation systems, software developed for defect detection or product classification typically involves separate systems for automation and machine vision programs, leading to increased system complexity and unnecessary resource wastage. To address these limitations, this study proposes an IEC 61131-3-based integrated development environment for programmable machine vision. We selected 11 APIs commonly used in machine vision systems, evaluated their functions in an IEC 61131-3 compliant development environment, and measured the performance of representative machine vision applications. This approach demonstrates the feasibility of developing PLC and machine vision programs within a single-controller system. We investigated the impact of controller performance on function execution.