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"Introduction to computational modeling in organizations, virtual organizations, the impact of organizational interventions on behaviors, examining the fit between empirical data and theoretical simulations, modeling faking on personality teste, simulating effects of pay-for-performance systems on pay-performance relationships, information distribution, participation, and group decision, computational modeling with petri nets, pressures to uniformity and the evolution of cultural norms, modeling change in fields of organizations, organizational adaptation in volatile environments, and lessons learned and insights gained."

"This book addresses patient-specific modeling. It integrates computational modeling, experimental procedures, imagine clinical segmentation and mesh generation with the finite element method (FEM) to solve problems in computational biomedicine and bioengineering. Specific areas of interest include cardiovascular problems, ocular and muscular systems and soft tissue modeling. "

"ehavior' is an increasingly important concept in the scientific, societal, economic, cultural, political, military, living and virtual worlds. Behavior computing, or behavior informatics, consists of methodologies, techniques and practical tools for examining and interpreting behaviours in these various worlds. Behavior computing contributes to the in-depth understanding, discovery, applications and management of behavior intelligence. With contributions from leading researchers in this emerging field Behavior Computing: Modeling, Analysis, Mining and Decision includes chapters on: representation and modeling behaviors behavior ontology behaviour analysis behaviour pattern mining clustering complex behaviors classification of complex behaviors behaviour impact analysis social behaviour analysis organizational behaviour analysis behaviour computing applications Behavior Computing: Modeling, Analysis, Mining and Decision provides a dedicated source of reference for the theory and applications of behavior informatics and behavior computing. Researchers, research students and practitioners in behavior studies, including computer science, behavioral science, and social science communities will find this state of the art volume invaluable"

"Proses produksi yang ramah lingkungan dikembangkan untuk mengolah limbah kaca menjadi blok kaca dengan kandungan energi yang rendah. Tingkat efisiensi energi blok kaca tersebut dicapai dengan tingkat transmisi panas secara konduksi (U) sebesar ≤3,177 W/m2.K maupun radiasi (SHGC) ≤ 0,25 serta tingkat transmisi cahaya tampak (VT) ≥ 0,27. Rongga diaplikasikan untuk menurunkan U dengan penurunan VT secara tidak signifikan. Metode analitis dipilih untuk menghitung U model blok kaca tanpa mempertimbangkan pengaruh konveksi. Untuk menganalisis VT dan SHGC setiap model dilakukan simulasi tingkat terang dan beban kalor di dalam bangunan dengan program Ecotect. Pengaruh konveksi diamati dari hasil simulasi CFD yang menggambarkan kecepatan aliran udara di dalam rongga dan gradien suhu pada blok kaca. Efisiensi yang dicapai oleh aplikasi model blok kaca ini mencapai 96% lebih rendah dibandingkan dengan pemakaian energi pada aplikasi dengan kaca 3 mm. Studi simulasi ini masih mengabaikan keberadaan perekat antar lapisan kaca yang berpotensi menurunkan VT dan SHGC blok kaca.

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An environmentally friendly process was developed to produce a low embodied energy glass block from waste glasses. The energy efficiency of the glass block is represented by its thermal conductance (U) 3.177 W/m2.K and solar transmittance (SHGC) ≤0.25 as well as visible light transmission (VT) ≥0.27. A cavity was applied to reduce U value while insignificantly reducing VT. Analytical method was used to calculate the U value of glass blocks, ignoring the effect of convection. Ecotect program was used to analyze light level (VT) and heat load (SHGC) of each model.

Effect of convection was simulated using a CFD program, which showed air velocity inside the cavity and temperature gradient in glass blocks. Comparing to an application with 3 mm float glass, energy efficiency obtained through applying the glass blocks could reach 96%. This simulation study ignored the presence of adhesive among glass layers that potentially reduces the VT and the SHGC of the glass blocks."