Applying mobile augmented reality (AR) to teach interior design students in layout plans: Evaluation of learning effectiveness based on the ARCS model of learning motivation theory

In this paper we present a mobile augmented reality (MAR) application supporting teaching activities in interior design. The application supports students in learning interior layout design, interior design symbols, and the effects of different design layout decisions. Utilizing the latest AR technology, users can place 3D models of virtual objects as e.g., chairs or tables on top of a design layout plan and interact with these on their mobile devices. Students can experience alternative design decision in real-time and increases the special perception of interior designs. Our system fully supports the import of interior deployment layouts and the generation of 3D models based on design artefacts based on typical design layout plan design symbols and allows the user to investigate different design alternatives. We applied John Keller’s Attention, Relevance, Confidence, and Satisfaction (ARCS) learning motivation model to validate our solution to examine the students’ willingness and verify the ability of students to improve learning through MAR technology. We compared a sample experimental group of N = 52 test-subjects with a sample of N = 48 candidates in a control group. Learning indicators as learning interest, confidence, satisfaction and effective have been utilized to assess the students’ learning motivation through the use of MAR technology. The learning results have been determined by the independent sample t testing. The significance of the post-test had a p-value \u3c 0.05 difference. The result of the study clearly shows that the reference group utilizing MAR technology as a learning aid show a higher learning effectiveness as the control group. Thus, we conclude that MAR technology does enhance students’ learning ability for interior design and making appropriate design decisions

Toward Sustainability:Using Big Data to Explore Decisive Supply Chain Risk Factors Under Uncertainty

Rapid market changes aimed at sustainability have led to supply chain risks and uncertainties in the Taiwanese light-emitting diode industry. These risks and uncertainties can be captured by social media, quantitative and qualitative data (referred to herein as big data), but the industry has been unable to manage this information boom to respond to customer needs. These various types of data have their own characteristics that affect decision making about developing firm capabilities. This study aggregates the various data to undertake an extensive investigation of supply chain risks and uncertainties. Specifically, this study proposes using the fuzzy and grey Delphi methods to identify a set of reliable attributes and, based on these attributes, transforming big data to a manageable scale to consider their impacts. Subsequently, both the fuzzy and grey Decision Making Trial and Evaluation Laboratories applied to determine the causal relationships for supply chain risks and uncertainties. The results reveal that capacity and operations have greater influence than other supply chain attributes and that risks stemming from triggering events are difficult to diagnose and control. The implications, conclusions and findings are addressed

A Hybrid Approach to Explore the Risk Dependency Structure among Agribusiness Firms

Although the risk management of agricultural firms is important, studies on the extreme risk dependence among agribusiness firms are minimal due to the diversity and complexity of the risks faced by agricultural firms. In this study, we developed a hybrid approach to analyse and uncover the potential risk dependence among agricultural firms. We examined thirty-two agricultural companies to study their dependence structure for risk losses. Three primary findings emerged. First, risk dependence is strong with an average value of 0.96. Second, the dependence structure is hierarchical and includes two network communities. Third, some key agricultural firms were identified in the dependence structure. These key firms are critical for the transmission of negative impacts across agricultural firms. Correspondingly, we suggest measures and strategies (such as improving the level of technological innovation and joint risk resistance capability) to reduce the impact of risk dependence

Invasive fungal infection among hematopoietic stem cell transplantation patients with mechanical ventilation in the intensive care unit

<p>Abstract</p> <p>Background</p> <p>Invasive fungal infection (IFI) is associated with high morbidity and high mortality in hematopoietic stem cell transplantation (HSCT) patientsThe purpose of this study was to assess the characteristics and outcomes of HSCT patients with IFIs who are undergoing MV at a single institution in Taiwan.</p> <p>Methods</p> <p>We performed an observational retrospective analysis of IFIs in HSCT patients undergoing mechanical ventilation (MV) in an intensive care unit (ICU) from the year 2000 to 2009. The characteristics of these HSCT patients and risk factors related to IFIs were evaluated. The status of discharge, length of ICU stay, date of death and cause of death were also recorded.</p> <p>Results</p> <p>There were 326 HSCT patients at the Linkou Chang-Gung Memorial Hospital (Taipei, Taiwan) during the study period. Sixty of these patients (18%) were transferred to the ICU and placed on mechanical ventilators. A total of 20 of these 60 patients (33%) had IFIs. Multivariate analysis indicated that independent risk factors for IFI were admission to an ICU more than 40 days after HSCT, graft versus host disease (GVHD), and high dose corticosteroid (<it>p </it>< 0.01 for all). The overall ICU mortality rate was 88% (53 of 60 patients), and was not significantly different for patients with IFIs (85%) and those without IFIs (90%, <it>p </it>= 0.676).</p> <p>Conclusion</p> <p>There was a high incidence of IFIs in HSCT patients requiring MV in the ICU in our study cohort. The independent risk factors for IFI are ICU admission more than 40 days after HSCT, GVHD, and use of high-dose corticosteroid.</p

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV