Description:
The six cities air pollution is used to estimate and investigate the marginal curve of a function describing lung growth for set of children in a longitudinal study. This article proposes penalized regression spline technqiue based ona semiparametric mixed models (MM) framework for an additive model. This smoothing approach fits marginal models for longitudinal unbalanced measurements by using a Bayesian inference approach, implemented using a Markov chain Monte Carlo approach with the Gibbs sampler. The unbalanced case in which missing or different number of measurements for a set of subjects is more practical and common in real life studies. This methodology makes it possible to establish a straightforward approach to similar models using R programming, when it is not possible to do so using existing codes.
Description:
We investigate the comparative performance of state-owned commercial banks (SOCBs) and private commercial banks (PCBs) of Bangladesh with respect to efficiency and profitability in financing international trade. Taking a ten-year panel data over 2003-2012 of all four SOCBs and four categorised PCBs, we apply the non-parametric approach data envelopment analysis (DEA) to measure and compare efficiency of the banks using output-oriented Malmquist Productivity Indices (MPI). Furthermore, we develop some specialised profitability ratios on trade financing business of the banks to measure profitability. Our results suggest that PCBs are more efficient and profitable compared to SOCBs' although PCBs provide less trade financing than SOCBs'. The study recommends SOCBs to progress technologically for sustaining themselves in the competitive banking sector of Bangladesh. Moreover, we identify the sources of profitability that would explain the banks' strategic position in trade financing business which would motivate more banks to support international traders through trade financing.
Description:
Measurement of apoptotic markers in tumors can be directly correlated with the cell cycle phase using flow cytometry (FCM). The conventional DNA content analysis requires cell permeabilization to stain nuclei with fluorescent probes such as propidium iodide or use of a costly UV-excitation line for Hoechst 33342 probe. The access to FCM is also still limited to centralized core facilities due to its inherent high costs and complex operation. This work describes development and proof-of-concept validation of a portable and user-friendly microfluidic flow cytometer (μFCM) that can perform multivariate real time analysis on live cells using sampling volumes as small as 10 microliters. The μFCM system employs disposable microfluidic cartridges fabricated using injection molding in poly(methylmethacrylate) transparent thermoplastic. Furthermore, the dedicated and miniaturized electronic hardware interface enables up to six parameter detection using a combination of spatially separated solid-state 473 (10 mW) and 640 nm (20 mW) lasers and x-y stage for rapid laser alignment adjustment. We provide new evidence that a simple 2D flow focusing on a chip is sufficient to measure cellular DNA content in live tumor cells using a far-red DNA probe DRAQ5. The feasibility of using the μFCM system for a dose-response profiling of investigational anti-cancer agents on human hematopoietic cancer cells is also demonstrated. The data show that μFCM can provide a viable novel alternative to conventional FCM for multiparameter detection of caspase activation and dissipation of mitochondrial inner membrane potential (ΔΨm) in relation to DNA content (cell cycle phase) in live tumor cells.
Description:
Measurement of apoptotic markers in tumors can be directly correlated with the cell cycle phase using flow cytometry (FCM). The conventional DNA content analysis requires cell permeabilization to stain nuclei with fluorescent probes such as propidium iodide or use of a costly UV-excitation line for Hoechst 33342 probe. The access to FCM is also still limited to centralized core facilities due to its inherent high costs and complex operation. This work describes development and proof-of-concept validation of a portable and user-friendly microfluidic flow cytometer (
Description:
In this paper, we propose a mobility model and present its simulation tool to generate realistic mobility traces for mobile ad hoc network. The mobility model is capable of creating realistic node movement pattern in the presence of geographic constraints by exploiting the concepts of anchors. The model dynamically places anchors depending upon the context of the environment through which nodes are guided to move towards the destination, and obstacles of arbitrary shapes with or without doorways and any existing pathways, in full or part of the terrain can be incorporated which makes the simulation environment more realistic. The characteristics of the proposed mobility model tested on a real world university campus map at various movement patterns are presented that illustrate the impact of the mobility model on the performance of a routing protocol and usefulness of the proposed scenario generation tool.
Description:
Performance of industrial products is very important for an industry. Conventional methods for performance analysis consider a normality assumption and limited to low dimensional data. Different manufacturing processes very often have products with quality characteristics that do not follow normal distribution. In such cases fitting a known non-normal distribution to these quality characteristics would lead to erroneous results while assessing the performance of products. In this paper, we propose a novel method for non-normal multivariate process performance analysis. We have proposed a Constraint-based Evolutionary Algorithm (EA) approach for optimal estimation of the parameters of non-normal multivariate process. Furthermore, a geometric distance based method has been employed to reduce higher dimensionality of data to lower dimension. The efficacy of the proposed method is assessed by using the proportion of nonconformance (PNC) criterion to summarize the performance of EA approach. The experimental results from constraint-based EA have been compared to those obtained using steepest descent and simulated annealing (SA) approaches.
Description:
Nowadays every business is using different quantitative measures and techniques to assess performance of their products / services. It is well known that different manufacturing processes very often manufacture products with quality characteristics that do not follow normal distribution. In such cases, fitting a known non-normal distribution to these quality characteristics would lead to erroneous results. Furthermore, there is always more than one characteristic Critical to Quality (CTQ) in the process outcomes and very often these quality characteristics are correlated with each other. In this paper, we assess performance of such a bivariate process data which is non-normal as well as correlated. We will use the geometric distance approach to reduce the dimension of the correlated non-normal bivariate data and then fit Burr distribution to the geometric distance variable. The optimal parameters of the fitted Burr distribution are estimated using Evolutionary Algorithm (EA). The results are compared with those using Simulated Annealing (SA) algorithm. The proportion of nonconformance (PNC) for process measurements is then obtained by using the fitted Burr distributions based on the two methods. The results based on both search algorithms are then compared with the exact proportion of nonconformance of the data. Finally, a case study using real data is presented.
Description:
Nowadays every business is using different quantitative measures and techniques to assess performance of their products / services. It is well known that different manufacturing processes very often manufacture products with quality characteristics that do not follow normal distribution. In such cases, fitting a known non-normal distribution to these quality characteristics would lead to erroneous results. Furthermore, there is always more than one characteristic Critical to Quality (CTQ) in the process outcomes and very often these quality characteristics are correlated with each other. In this paper, we assess performance of such a bivariate process data which is non-normal as well as correlated. We will use the geometric distance approach to reduce the dimension of the correlated non-normal bivariate data and then fit Burr distribution to the geometric distance variable. The optimal parameters of the fitted Burr distribution are estimated using Evolutionary Algorithm (EA). The results are compared with those using Simulated Annealing (SA) algorithm. The proportion of nonconformance (PNC) for process measurements is then obtained by using the fitted Burr distributions based on the two methods. The results based on both search algorithms are then compared with the exact proportion of nonconformance of the data. Finally, a case study using real data is presented.
Description:
This paper investigates the impact of time delay in the control of a grid-connected microgrid with renewable energy resources. The considered microgrid has a critical load that needs to be powered and protected in the event of grid voltage disturbance while the microgrid maintains connection to the grid. Three case studies are performed considering three different time delays to indicate the advantages of fast communication system in the performance of renewable microgrids. Detailed simulation results illustrate that the proposed communication system using IEC 61850 substation automation standard provides better voltage and current quality to the critical local load with larger phase and gain margins while keeping the microgid connected to main grid.
Description:
This paper investigates the impact of time delay in the control of a grid-connected microgrid with renewable energy resources. The considered microgrid has a critical load that needs to be powered and protected in the event of grid voltage disturbance while the microgrid maintains connection to the grid. Three case studies are performed considering three different time delays to indicate the advantages of fast communication system in the performance of renewable microgrids. Detailed simulation results illustrate that the proposed communication system using IEC 61850 substation automation standard provides better voltage and current quality to the critical local load with larger phase and gain margins while keeping the microgid connected to main grid.