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A comparative study of the use of executive information systems between Korea and the United States
Since their conception, EIS have been developed and adopted in many firms. The importance of EIS is now increasing with the need of accessing data from many sources under the high-velocity environment. Although many of the Korean firms are now in the process of introducing EIS with the faster growing economy, most research has been conducted on the use of EIS in Western firms. This study aims to explore the current state of EIS usage in Korean firms and make a comparison with that of the United States. Based upon Watson et al. (1992), a questionnaire instrument was constructed. The questionnaires were distributed to 136 Korean companies that were reported to use EIS and 50 of the questionnaires returned. We found that there were many differences in the use of EIS between Korea and the United States. This was mainly due to the fact that the use of EIS in Korea was at a very early stage and executives in Korea did not realize and/or understand the benefits from the use of EIS yet
Metal-Insulator Phase Transition in Quasi-One-Dimensional VO<sub>2</sub>Structures
The metal-insulator transition (MIT) in strongly correlated oxides has attracted considerable attention from both theoretical and experimental researchers. Among the strongly correlated oxides, vanadium dioxide (VO2) has been extensively studied in the last decade because of a sharp, reversible change in its optical, electrical, and magnetic properties at approximately 341 K, which would be possible and promising to develop functional devices with advanced technology by utilizing MITs. However, taking the step towards successful commercialization requires the comprehensive understanding of MIT mechanisms, enabling us to manipulate the nature of transitions. In this regard, recently, quasi-one-dimensional (quasi-1D) VO2structures have been intensively investigated due to their attractive geometry and unique physical properties to observe new aspects of transitions compared with their bulk counterparts. Thus, in this review, we will address recent research progress in the development of various approaches for the modification of MITs in quasi-1D VO2structures. Furthermore, we will review recent studies on realizing novel functional devices based on quasi-1D VO2structures for a wide range of applications, such as a gas sensor, a flexible strain sensor, an electrical switch, a thermal memory, and a nonvolatile electrical memory with multiple resistance.</jats:p
Examining the Validity of Fitbit Charge HR \u3csup\u3eTM\u3c/sup\u3e for Measuring Heart Rate in Free-Living Conditions
Optical blood flow sensors (i.e. photoplethysmographic techniques) have recently been utilized in wearable activity trackers. The Fitbit Charge HRTM (FBHR) is one of the widely recognized wearable activity trackers that utilizes Fitbit’s proprietary PurePulse optical heart rate (HR) technology to automatically measure wrist-based HR. Despite its increasing popularity, however, no study to date has addressed the validity of FBHR for measuring HR in free-living conditions. PURPOSE: The purpose of this study was to examine the validity of FBHR for measuring HR using a chest strap Polar HR monitor (PHR) as a reference measure in free-living conditions. METHODS: Ten healthy college students (8 males; mean age = 26.5 ±5.4 years; mean body mass index (BMI) = 24.5 ±3.23 kg·m2) participated in the study. The participants were asked to perform normal daily activities for 8 hours in a day while wearing the PHR (model RS400) on their chest and two FBHRs on their dominant and non-dominant wrists, respectively. HR was recorded every minute and the minute-by-minute HR data from each monitor were synchronized by time of day. Pearson correlation was used to examine the linearity of average beats-per-minute (bpm) estimated from FBHRs with respect to the PHR. Mean differences in average bpm between the monitors were examined by a general linear model for repeated measures. Lastly, mean absolute percentage error (MAPE) of minute-by-minute bpm estimated from the FBHRs were calculated against the PHR. RESULTS: Average HRs (mean ±SD) for PHR, FBHR non-dominant, and FBHR dominant were 75.6 ±18.5 bpm, 72.8 ±16.7 bpm, and 73.9 ±17.06 bpm, respectively. Pearson correlation coefficients (r) between the PHR and FBHR non-dominant and dominant were r=.805 and r=.793, respectively. MAPE were 9.17 ±10.9% for FBHR non-dominant and 9.71 ± 12.4% for FBHR HR dominant. ANOVA and post-hoc analyses with Bonferroni revealed significant differences in estimating HR from FBHR non-dominant wrist (p=.001) and FBHR dominant wrist (p=.001) compared to PHR monitor. CONCLUSION: The results indicated that the wrist-oriented Fitbit Charge HRTM device does not provide an accurate measurement of HR during free-living condition in this study. However, further research is needed to validate these monitors with a larger sample with different population groups.
Optical blood flow sensors (i.e. photoplethysmographic techniques) have recently been utilized in wearable activitytrackers. The Fitbit Charge HRTM (FBHR) is one of the widely recognized wearable activity trackers that utilizesFitbit’sproprietary PurePulse optical heart rate (HR) technology to automatically measure wrist-based HR. Despiteits increasing popularity, however, no study to date has addressed the validity of FBHR for measuring HR in free-living conditions. PURPOSE: The purpose of this study was to examine the validity of FBHR for measuring HRusing a chest strap Polar HR monitor (PHR) as a reference measure in free-living conditions. METHODS: Tenhealthy college students (8 males; mean age = 26.5 ±5.4 years; mean body mass index (BMI) = 24.5 ±3.23kg·m2) participated in the study. The participants were asked to perform normal daily activities for 8 hours in a daywhile wearing the PHR (model RS400) on their chest and two FBHRs on their dominant and non-dominant wrists,respectively. HR was recorded every minute and the minute-by-minute HR data from each monitor weresynchronized by time of day. Pearson correlation was used to examine the linearity of average beats-per-minute(bpm) estimated from FBHRs with respect to the PHR. Mean differences in average bpm between the monitorswere examined by a general linear model for repeated measures. Lastly, mean absolute percentage error (MAPE)of minute-by-minute bpm estimated from the FBHRs were calculated against the PHR. RESULTS: Average HRs(mean ±SD) for PHR, FBHR non-dominant, and FBHR dominant were 75.6 ±18.5 bpm, 72.8 ±16.7 bpm, and73.9 ±17.06 bpm, respectively. Pearson correlation coefficients (r) between the PHR and FBHR non-dominantand dominant were r=.805 and r=.793, respectively. MAPE were 9.17 ±10.9% for FBHR non-dominant and 9.71 ±12.4% for FBHR HR dominant. ANOVA and post-hoc analyses with Bonferroni revealed significant differences inestimating HR from FBHR non-dominant wrist (p=.001) and FBHR dominant wrist (p=.001) compared to PHRmonitor. CONCLUSION: The results indicated that the wrist-oriented Fitbit Charge HRTM device does not providean accurate measurement of HR during free-living condition in this study. However, further research is needed tovalidate these monitors with a larger sample with different population groups
Readmissions following elective radical total gastrectomy for early gastric cancer: A case-controlled study
AbstractBackgroundReadmission after gastrectomy is one of the factors that reflect quality of life. Therefore, we analyzed the several factors related to readmissions after total gastrectomy for early gastric cancer.MethodsFrom January 2002 through December 2009, 102 consecutive patients who underwent radical total gastrectomy for early gastric cancer were enrolled in this study. We evaluated the incidence, cause, time point, and type of treatment for readmission after discharge; we compared the readmission and non-readmission groups in regard to clinicopathologic features and postoperative outcomes.ResultsThe readmission rate during the five years after total gastrectomy was 22 of 102 (21.6%). The most common cause for readmission was esophagojejunostomy stricture (5 cases). The treatment given for 31 readmissions included 23 conservative therapies, 3 radiologic or endoscopic interventions, and 5 re-operations. No significant differences were detected in the clinicopathologic feature, postoperative outcomes, or 5-year survival rates between the readmission and non-readmission group. No specific risk factor was found to be associated with readmission.ConclusionAlthough we could not determine a specific risk factor associated with readmission after radical total gastrectomy, prevention of readmission by evaluating the causes and treatments after radical total gastrectomy can improve the patient's quality of life
Reliability of DEXA on Body Composition in Korean Athletes
PURPOSE: The purpose of this study was to assess the reliability of DEXA for measuring body composition in Korean Athletes.
METHODS: Twenty-nine athletes (n=29) registered for the college athlete program voluntarily participated in the study. Participants’ height and weight were measured, and BMI (Body Mass Index) was calculated before the participants’ body composition was measured. Muscle mass (kg), lean mass (kg), bone mineral density (BMC) (g·cm-2), and total fat mass (kg) of each participant was assessed by DEXA lunar DPX-L (GE Lunar, Madison, USA) for four times within a day to examine the difference by time frames. Four trials consist of ‘early in the morning × 2 with fasting’ with 30min break between two trials, ‘after lunch × 2’ with 30 min break between the two trials. Intra-class correlation (ICC) was conducted for overall reliability (p\u3c0.05) and a repeated measure ANOVA was performed to compare the difference of each trial (p\u3c0.05).
RESULTS: The mean ± SD of muscle mass, lean mass, BMC, and fat mass was 56.4 ± 4.6kg, 59.4 ± 5.0kg, 2.3 ± 0.4g·cm-2, and 9.3 ± 4.8kg respectively. Each trail (mean ± SD) of muscle mass were 56.4 ± 4.7kg, 56.1 ± 4.8kg, 56.5 ± 4.6kg, and 56.4 ± 4.7kg, respectively, lean mass were 59.4 ± 5.1kg, 59.2 ± 5.1kg, 59.5 ± 5.0kg, and 59.4 ± 5.0kg, respectively, BMC were 3.0 ± 0.4g·cm-2, 3.0 ± 0.4g·cm-2, 3.0 ± 0.4g·cm- 2, and 3.0 ± 0.4g·cm-2, respectively, and fat mass were 9.3 ± 4.9kg, 9.2 ± 4.8kg, 9.3 ± 4.9kg, and 9.3 ± 4.9kg, respectively. Reliability of the ICC test showed strong agreement on muscle mass (r=0. 994 and p\u3c0.0001), lean mass (r=0. 995 and p\u3c0.0001), BMC (r=0. 995 and p\u3c0.0001), and fat mass (r=0. 998 and p\u3c0.0001). Cronbach’s alpha were 0.99 (muscle mass), 0.99 (Lean Mass), 0.99 (BMC), and 1.00 (Fat mass). No significant difference between each trial was observed in fat mass (p\u3e0.36). However, there was a significant difference in muscle mass (p\u3c0.001), lean mass (p\u3c0.001), and BMC (p\u3c0.04).
CONCLUSION: Although all of the variables showed strong agreement on overall reliability from the ICC test, the reliability for the muscle mass, lean mass, and BMC showed significant differences in different time frame
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