The Influential Motivations of Green IT Device Use and the Role of Reference Group Perspective

In this study we investigate the determinants of behavior intention to use green IT device for reducing electronic consumption by focusing on the end user aspects of a pro-environmental behavior. We tried to understand motivation theory in explaining the causal relationship between motivation aspects and perceived usefulness. By using a reference group theory, we emphasized on how the reference group moderates the motivations and perceived usefulness relationship. We used Partial Least Square (PLS) to analyze the data sample of 104 and found that intrinsic motivation (perceived enjoyment) is significantly related to the perceived usefulness as well as extrinsic motivation (saving money, legislative pressure) is strongly related to the perceived usefulness. In sum, the perceived usefulness has a strong impact on sustainable use of green IT device. Also, we found that a reference group moderates partially the independent variables and mediation variable

Moderating Role of Long-term Orientation on Augmented Reality Adoption

Recently, the tourism and hospitality industry is providing tourists with an enhanced experience via various cutting-edge technologies such as augmented reality (AR). In addition, there has been an increased interest on the effects of cultural traits on human behaviours. The aim of this paper is to examine how Long- and Short-term orientation moderates the relationship between experience economy provided by AR applications and users’ perceived value. Data were collected from 145 participants at Deoksugung Palace in Seoul, South Korea and 119 participants at An Post Museum, Dublin, Ireland. We found that South Korean tourists, who are representatives of long-term orientation culture in this study, put a high value on educational factors of AR applications, whereas Irish tourists, who are representative of short-term orientation culture, regard escapist experiences of AR applications highly

Agent based mobile negotiation for personalized pricing of last minute theatre tickets

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.This paper proposes an agent based mobile negotiation framework for personalized pricing of last minutes theatre tickets whose values are dependent on the time remaining to the performance and the locations of potential customers. In particular, case based reasoning and fuzzy cognitive map techniques are adopted in the negotiation framework to identify the best initial offer zone and adopt multi criteria decision in the scoring function to evaluate offers. The proposed framework is tested via a computer simulation in which personalized pricing policy shows higher market performance than other policies therefore the validity of the proposed negotiation framework.The Ministry of Education, Science and Technology (Korea

Factors associated with stroke in patients with paroxysmal atrial fibrillation beyond CHADS2 score

Background: This study was conducted to investigate factors associated with stroke in pa­tients with paroxysmal atrial fibrillation (PAF) beyond CHADS2 score in terms of left ventricular (LV) diastolic function or left atrial (LA) function. Methods: One hundred and sixty-one patients with PAF and age less than 75 (mean age 61 ± 10; 69 male) who underwent transthoracic echocardiography were investigated. Patients were divided into two groups according to the stroke status (group 1 — no stroke vs. group 2 — presence of stroke). Baseline echocardiographic parameters and LA segmental (4 segments: basal septal, lateral, inferior, and anterior) strain rate (SR) during normal sinus rhythm were analyzed. Results: CHAD score (except S2) was similar between the two groups (0.6 ± 0.7 vs. 0.9 ± 0.7, p = 0.125). Patients with stroke had slightly lower body mass index (24.5 ± 2.7 vs. 23.4 ± ± 2.4, p = 0.052). Echocardiographic parameters did not show any differences in both systolic and diastolic functions between the two groups, however elevated E/E’ ratio was noted (9.5 ± ± 3.8 vs. 11.6 ± 3.9, p = 0.010) due to higher E velocity (63.5 ± 15.9 vs. 70.9 ± 16.0 cm/s, p = 0.046). In the analysis of LA SR, there are no differences of SR among the 4 segments. However, standard deviations (SD) of time to peak SR (SD of tA-SR) of the 4 segments were higher in patients with stroke (10.9 ± 9.9 vs. 22.1 ± 18.1 ms, p = 0.009) which indicates dyssynchronous contraction of LA. In multivariate analysis, SD of tA-SR (OR 1.074, CI 1.024–1.128, p = 0.004) and elevated E/E’ (OR 1.189, CI 1.006–1.406, p = 0.048) were independently associated with stroke in patients with PAF. Conclusions: Elevated E velocity, E/E’ and SD of tA-SR were associated with occurrence of stroke in patients with PAF even with similar CHAD scores. Increased SD of tA-SR and E/E’ were independently associated with stroke in patients with PAF.

Machine Learning-Based Analysis of Adolescent Gambling Factors

Background and aims: Problem gambling among adolescents has recently attracted attention because of easy access to gambling in online environments and its serious effects on adolescent lives. We proposed a machine learning-based analysis method for predicting the degree of problem gambling. Methods: Of the 17,520 respondents in the 2018 National Survey on Youth Gambling Problems dataset (collected by the Korea Center on Gambling Problems), 5,045 students who had gambled in the past 3 months were included in this study. The Gambling Problem Severity Scale was used to provide the binary label information. After the random forest-based feature selection method, we trained four models: random forest (RF), support vector machine (SVM), extra trees (ETs), and ridge regression. Results: The online gambling behavior in the past 3 months, experience of winning money or goods, and gambling of personal relationship were three factors exhibiting the high feature importance. All four models demonstrated an area under the curve (AUC) of >0.7; ET showed the highest AUC (0.755), RF demonstrated the highest accuracy (71.8%), and SVM showed the highest F1 score (0.507) on a testing set. Discussion: The results indicate that machine learning models can convey meaningful information to support predictions regarding the degree of problem gambling. Conclusion: Machine learning models trained using important features showed moderate accuracy in a large-scale Korean adolescent dataset. These findings suggest that the method will help screen adolescents at risk of problem gambling. We believe that expandable machine learning-based approaches will become more powerful as more datasets are collected.11Ysciessciscopu

Multi-agent knowledge integration mechanism using particle swarm optimization

This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established. Storage difficulties stem from of the integration of the logic underlying multiple experts' decision-making processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.Ministry of Education, Science and Technology (Korea

Role of host tissues for sustained humoral effects after endothelial progenitor cell transplantation into the ischemic heart

Noncellular differentiation effects have emerged as important mechanisms mediating therapeutic effects of stem or progenitor cell transplantation. Here, we investigated the expression patterns and sources of humoral factors and their regional and systemic biological effects after bone marrow (BM)-derived endothelial progenitor cell (EPC) transplantation into ischemic myocardium. Although most of the transplanted EPCs disappeared within a week, up-regulation of multiple humoral factors was sustained for longer than two weeks, which correlated well with the recovery of cardiac function. To determine the source of the humoral factors, we injected human EPCs into immunodeficient mice. Whereas the expression of human EPC (donor)-derived cytokines rapidly decreased to a nondetectable level within a week, up-regulation of mouse (recipient)-derived cytokines, including factors that could mobilize BM cells, was sustained. Histologically, we observed higher capillary density, a higher proliferation of myocardial cells, a lower cardiomyocyte apoptosis, and reduced infarct size. Furthermore, after EPC transplantation, BM-derived stem or progenitor cells were increased in the peripheral circulation and incorporated into the site of neovascularization and myocardial repair. These data indicate that myocardial EPC transplantation induces humoral effects, which are sustained by host tissues and play a crucial role in repairing myocardial injury

Military Facility Cost Estimation System Using Case-Based Reasoning in Korea

This manuscript was submitted on January 22, 2010; approved on July 30, 2010; published online on August 3, 2010. Discussion period open until October 1, 2011; separate discussions must be submitted for individual papers.Numerous cost estimations are made repetitively in the initial stages of construction projects in response to ongoing scope changes and often need to be recalculated frequently. In practice, the square foot method, considered an effective method for time-saving, is widely used. However, this method requires a great amount of effort to calculate a unit price and does not consider the uniqueness of each case. Thus, the use of the square foot method could bring about unwanted consequences. For example, in the case of military projects in Korea, significant differences have been reported between estimations made using this method and the actual costs. In an effort to deal with this challenging issue, this research develops a military facility cost estimation (MilFaCE) system, based on case-based reasoning (CBR), using case data from 422 construction projects at 16 military facilities. Based on system validation experiments involving 10 military officers (engineers), the effectiveness of the system in terms of estimation accuracy and user-friendliness is confirmed. Consequently, this research can be a CBR application example of construction cost estimation and a basis for further research into the development of cost estimate systems. DOI: 10.1061/(ASCE)CP.1943-5487.0000082. (C) 2011 American Society of Civil Engineers.This research was supported by grants (R&D06CIT-A03 and 05CIT-01) from the Korea Ministry of Land, Transport, and Marine Affairs and the Ministry of Defense.

Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus

Background There was limited evidence to evaluate the association between lifestyle habits and continuous glucose monitoring (CGM) metrics. Thus, we aimed to depict the behavioral and metabolic determinants of CGM metrics in insulin-treated patients with type 2 diabetes mellitus (T2DM). Methods This is a prospective observational study. We analyzed data from 122 insulin-treated patients with T2DM. Participants wore Dexcom G6 and Fitbit, and diet information was identified for 10 days. Multivariate-adjusted logistic regression analysis was performed for the simultaneous achievement of CGM-based targets, defined by the percentage of time in terms of hyper, hypoglycemia and glycemic variability (GV). Intake of macronutrients and fiber, step counts, sleep, postprandial C-peptide-to-glucose ratio (PCGR), information about glucose lowering medications and metabolic factors were added to the analyses. Additionally, we evaluated the impact of the distribution of energy and macronutrient during a day, and snack consumption on CGM metrics. Results Logistic regression analysis revealed that female, participants with high PCGR, low glycosylated hemoglobin (HbA1c) and daytime step count had a higher probability of achieving all targets based on CGM (odds ratios [95% confidence intervals] which were 0.24 [0.09 to 0.65], 1.34 [1.03 to 1.25], 0.95 [0.9 to 0.99], and 1.15 [1.03 to 1.29], respectively). And participants who ate snacks showed a shorter period of hyperglycemia and less GV compared to those without. Conclusion We confirmed that residual insulin secretion, daytime step count, HbA1c, and women were the most relevant determinants of adequate glycemic control in insulin-treated patients with T2DM. In addition, individuals with snack consumption were exposed to lower times of hyperglycemia and GV