Purposes: Pancreatic injury is rare in abdominal trauma patients (3%~12%). but it could result in significant morbidity and even mortality. Early and adequate decision making are very important in the management of patients with traumatic pancreatic injury. The purpose of this study was to assess the kinds of management and outcome through the review of our experience of pancreatic injury with multiple trauma. Methods: We reviewed 17 patients with traumatic pancreas injury via electronic medical records from Jan. 2002 and April. 2011. We collected demographic findings; the type, location and grade of pancreas injury, the treatment modality, and patient's outcomes, such as complications, length of hospital stay (LOS), and mortality. Results: Total 17 patients were reviewed, and man was 13 (88%). Traffic accident was the most common cause of injury. Pancreas neck was the most common injured site, and occured in 5 patients. Ductal injury was detected in 7 cases. Eleven patients were treated by surgical procedure, and in this group, 3 patients underwent the endoscopic retrograde pancreas drainage procedure coincidently. ERPD was tried in 8 patients, and failed in 2 patients. The major complications were post-traumatic fluid collection and abscess which accounted for 70 % of all patients. The hospital stay was 35.9 days, and it was longer in patient with ductal injury ($38.0{\pm}18.56$ vs. $34.5{\pm}33.68$ days). Only one patient was died due to septic shock associated with an uncontrolled retroperitoneal abscess. Conclusion: Early diagnosis is the most important factor to apply the adequate treatment option and to manage the traumatic pancreas injury. Aggressive treatment should be considered in patients with a post-operative abscess.
With the advent of light-weight daily physiological signal monitoring sensors, intelligent inference and analysis method for physiological signal monitoring application, commercialized products and services are released. However, practical constraints still remain for daily physiological signal monitoring. Most devices provide rough health check function and analyze with randomly sampled measurements. In this work, we propose the probabilistic modeling of physiological signal analysis. This model represent the relationship between previous user measurement (history), other group`s type, model and current observation. From the experiment, we found that the personalized analysis with long term regular data shows reliable result and reduces the analyzing errors. In addition, participants agree that the personalized analysis shows reliable and adaptive information than other standard analysis method.
This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.
Journal of Korean Institute of Industrial Engineers
/
v.34
no.2
/
pp.190-204
/
2008
Recently, it has been strongly required to establish a systematic and sustainable performance investigation and evaluation framework on governmental funding projects for IT small and medium-sized enterprises. In this paper, Data Envelopment Analysis (DEA) models are adopted for performance evaluation on governmental funding projects for IT small and medium-sized enterprises. A new data structure is proposed for the DEA performance evaluation. Generally, in using DEA models, DEA multipliers restriction is critical to achieve the reliability of DEA optimal solutions. Based on the outputs and inputs considered in this study, Acceptance Region (AR) constraints are generated and incorporated into the DEA models so as to improve the reliability of DEA efficiency scores. Associated with AR Type I (AR-I), AR Global Model (ARGM) constraints, DEA/ (AR-I, ARGM) models are designed and then sensitivity analysis follows investigating the robustness of DEA efficiency scores relating to AR constraints adjustment. Finally, a performance evaluation is illustrated regarding governmental direct funding projects from Ministry of Information and Communication (MIC) in Korea where each project unit (i.e. Decision Making Unit (DMU)) is determined whether it is efficient or not. By using DEA/(AR-I, ARGM) models designed in this paper, robustly efficient DMUs are gradually identified according to the successive AR constraints adjustment. Among 25 DMUs, results show that 6 DMUs such as B, E, G, Q, S, Y are determined as robustly efficient against AR constraints intermediate adjustment.
A volcano disaster damage prediction system supports decision making for counteracting volcanic disasters by simulating meteorological condition and volcanic eruptions. In this system, a program called Fall3D generates predicted results for the diffusion of ash after a volcanic eruption on the basis of meteorological information. The relevant meteorological information is generated by a weather numerical prediction model known as Weather Research & Forecasting (WRF). In order to reduce the entire processing time without modifying these two simulation programs, pipelining can be used by partly executing Fall3D whenever the hourly (partial) results of WRF are generated. To reduce the processing time, successor programs such as Fall3D require that certain features be suspended until the part of the results that is based on prior calculation is generated by a predecessor. Even though Fall3D does not have a suspend or resume feature, pipelining effect can be produced by using the program's restart feature, which resumes simulation from the previous session. In this study, we suggest a workflow that can control the execution type.
This study examines market acceptance for DMB service, one of the touted new business models in Korea's next-generation mobile communications service market, using adoption end diffusion of innovation as the theoretical framework. Market acceptance for DMB service was assessed by predicting the demand for the service using the Bass model, and the demand variability over time was then analyzed by integrating the innovation adoption model proposed by Rogers (2003). In our estimation of the Bass model, we derived the coefficient of innovation and coefficient of imitation, using actual diffusion data from the mobile telephone service market. The maximum number of subscribers was estimated based on the result of a survey on satellite DMB service. Furthermore, to test the difference in diffusion pattern between mobile phone service and satellite DMB service, we reorganized the demand data along the diffusion timeline according to Rogers' innovation adoption model, using the responses by survey subjects concerning their respective projected time of adoption. The comparison of the two demand prediction models revealed that diffusion for both took place forming a classical S-curve. Concerning variability in demand for DMB service, our findings, much in agreement with Rogers' view, indicated that demand was highly variable over time and depending on the adopter group. In distinguishing adopters into different groups by time of adoption of innovation, we found that income and lifestyle (opinion leadership, novelty seeking tendency and independent decision-making) were variables with measurable impact. Among the managerial variables, price of reception device, contents type, subscription fees were the variables resulting in statistically significant differences. This study, as an attempt to measure the market acceptance for satellite DMB service, a leading next-generation mobile communications service product, stands out from related studies in that it estimates the nature and level of acceptance for specific customer categories, using theories of innovation adoption and diffusion and based on the result of a survey conducted through one-to-one interviews. The authors of this paper believe that the theoretical framework elaborated in this study and its findings can be fruitfully reused in future attempts to predict demand for new mobile communications service products.
PURPOSES : The objective of this study was to analyze variations in the vehicle driving behavior characteristics on signalized intersections according to the use of traffic enforcement camera (red light camera). METHODS : In order to analyze the driving behavior characteristics on signalized intersections when red light camera are installed, the target sites for investigation were selected depending on whether the red light camera is installed and accident rates increased after the installation. In particular, to analyze the characteristics of dilemma zones in signalized intersections, approach speed and deceleration speed of 3 type vehicles (passing vehicles during a yellow light, stopping at a yellow light, passing vehicles during a green light) were examined. Based on these data, the starting point, ending point, and distance of the dilemma zones were calculated. Also, the locations of increased traffic accidents and decreased accidents after the installation of the equipment were distinguished when analyzing the traffic accident characteristics. RESULTS : Analysis results revealed that there was a tendency for the dilemma zone distance to decrease after the installation of equipment(red light camera) in most sites. This tendency was found to be due to the decrease in the approaching speed of vehicles at intersections after the installation of equipment, resulting in the starting and ending points of dilemma zone to become closer to the stop line. Moreover, analysis showed that the number of traffic accidents decreased for most intersections after the installation of equipment and safety of the intersections increased somewhat. CONCLUSIONS : In general, installation of equipment(red light camera) caused the intersections approaching speed and dilemma zone distance to decrease. Decision-making is difficult for drivers in the dilemma zone, so the decrease in the dilemma zone distance implies an improvement in traffic safety. Furthermore, the number of accidents within intersections significantly decreased after the equipment was installed, leading to the conclusion that installation of the equipment affected the decrease in traffic accidents.
Journal of Korean Society for Geospatial Information Science
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v.10
no.2
s.20
/
pp.19-27
/
2002
The goal of this research is to develop the method of facility management which is used to manage the facility efficiently by using existing analyses of a system and a operation, and establish the method of a facility administration by applying AHP(Analytic Hierarchy Process) model. Because the standard of a accuracy in spacial analysis and calculation is a unclear, the exact analysis of a geographic data for a decision-making needs statistical analysis and administrator-centered type of system didn't satisfy the desire of users. There must be the existing general statistics module, integrated internet GIS and the composition of interface in order to structure a spacial statistics analysis methods that satisfy the matters desired in internet GIS into the spacial analysis function. This paper presents the need of internet GIS and AHP Model in supporting and managing function of all facilities in campus and introduce the possibility of applying.
Korean Government has developed Sejong City as a new administration city. This city of future was planned and designed toward one of the most eco-friendly city on the basis of ICTs. To attain this object, a carbon emission monitoring system (CEMS) was designed and installed as a part of u-city service which provides various information anytime and anywhere to enrich the people's quality of life. In this paper, at first, the structure and functions of CEMS are introduced. This system is consist of 5 parts - data collection from user and linked public DBs, transforming data into meaningful information for the policy makers, system-user interfacing via statistical tables and graphs, and system maintenance. This system can be operated by the citizen participation through whole the process. With the help of GIS map and graphic interface, statistics of monitored data for both citizen and decision maker provided and after feed-back, they have affected on the behaviour of citizen's energy consumption and related policy as well. By the CEMS, energy consumption data of 124 agreed households were collected during 9 months in 2012. Electricity, gas and water consumption were remote-metered automatically by the system and analysed. This showed that more than 85% of CO2 emission is rely on electricity usage. Furthermore, number of family members and size of house influences on the emission of CO2 by each household together with the life-style of the occupants. Electricity and water consumption showed the seasonal factor while gas consumption represents the number of family members. Even this paper has limitations caused by 9 months of data collection, it shows the policy directions to reduce the emission of CO2 focusing on the house size and number of family members of each households. With the result of this research, life-style of the generation of dwellers should be investigated and the CO2 emission characteristics of other housing type as well for the data building for future policy making.
As Online Behavioral Advertising is dramatically growing with usefulness of information and user convenience in recent years, there are privacy issues caused by collecting user's behavioral information without their consent. To tackle the problem, the need of Do Not Track regulations is getting much higher. In Korea, however, it has never existed. So, this study is examining the case of the major countries have been enforcing the law and regulations of DNT. After that, it is classified with four domain (law/regulation, corporation, individual, society) to include all stakeholders of OBA. Furthermore, this study may have academic significance by suggesting DNT framework through analysis of them. Providing DNT mechanism consisted of three type (behavioral information, control, DNT system), it can be useful guidelines for companies to support decision making as introduced DNT. As analyzed between DNT and stakeholders based on the study of OBA market, it will be useful basic material of OBA study later.
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