46 research outputs found
LIGHT, THE RIGHT WAY
No full textRapid urbanization in Dhaka has driven a surge in high-rise office buildings with fully glazed façades, reflecting a global architectural trend favoring transparency and daylight maximization. However, in Dhaka’s hot and humid tropical climate, extensive use of glass façades creates challenges such as visual discomfort, glare, and excessive brightness, which compromise occupant comfort and energy efficiency. This thesis investigates the impact of fully glazed office façades on daylight quality and visual comfort in Dhaka, focusing on daylight contrast and glare issues influenced by building orientation and climatic factors. Through a case study approach combining daylight simulation and on-site occupant surveys, the research evaluates current façade performance. In response, the thesis proposes optimized external shading solutions aimed at balancing daylight penetration with glare reduction to improve visual comfort and occupant well-being. Findings suggest that, without proper shading design, fully glazed façades may not deliver the expected sustainable benefits in Dhaka’s context. Proposed façade shading modifications demonstrate significant improvements in reducing these issues while maintaining natural light penetration. This study highlights the importance of context-sensitive façade design in tropical climates to enhance both energy efficiency and indoor environmental quality
On the Bayesian estimator of interaction models with measurement error and misclassification in covariates
No full textMeasurement error and misclassification in covariates are commonly arising problems
in statistical models. They have negative impacts on statistical inference about the
outcome, including bias and large variability in estimators. Furthermore, in a statistical
model, two or more covariates can interact, which in practice is quite challenging
to deal with. One of the recent techniques is Bayesian method that incorporates the
prior knowledge about parameters. In this research, Bayesian techniques are applied to
the models with interaction terms, while addressing measurement error and misclassification.
Moreover, through extensive simulation studies, Markov Chain Monte Carlo
algorithms are used to implement the Bayesian methods.Includes bibliographical references (pages 82-84)
Technology Development and Characterization of AIInN/GaN HEMTs for High Power Application
No full textAlInN has attracted much attention only recently as a material due to its unique and superior material properties, which is however known to be difficult to be grown among the III-nitride ternary compounds. The electrons confined at the heterointerface of coherently grown AlInN on GaN buffer layers determine crucial electronic properties. This dissertation has been designed targeting the lattice matched AlInN/GaN investigation with very detail to optimize the design, fabrication process, and electronic properties to realize AlInN/GaN HEMTs. Each single step of this process was optimized in order to improve device performance.
The work started with establishing the main features of AlInN/GaN heterostructure in a HEMT configuration through optimizing the device fabrication and investigation of the DC characteristics of planar HEMTs. The study included heterostructures with variable barrier thicknesses along with barrier cap layer. A series of experiments were conducted to analyze the impact of barrier thickness on breakdown and threshold-voltage by fabricating devices with different gate to drain separation and incorporating field plated gate design. In addition, a series of experiments were conducted on barrier scaling study of the heterostructure to develop plasma based selective area recess etching to obtain and demonstrate, first ever reported, normally off high threshold voltage AlInN/GaN metal-insulator HEMTs with high current density of 0.7A/mm and high breakdown voltage of 350V and the highest reported threshold voltage of +1.5V. Moreover, investigation of substrate influence was also performed by fabricating and characterizing AlInN/GaN HEMTs on SiC substrate with different gate dimensions and the transport properties of the devices were discussed.
Next, the device performance has been studied by incorporating Ga in AlInN barrier. Introducing 2% Ga at the AlInN barrier layer is found to increase the current density of about 15% compared to the LM AlInN/GaN HEMTs. This issue has been studied intensively and the preliminary results indicated that even slightest deviations from atomically perfect interfaces leads to the creation of huge piezoelectric fields, increasing the carrier density at the AlInN/GaN interface.
Finally, multifinger AlInN/GaN HEMTs were fabricated to obtain large periphery (LP) devices for high power application. The heart of this work was the design and development of a high yield process technology for high performance LP AlInN/GaN HEMTs. The study of large periphery devices presented the problem of large heat dissipation. Therefore, for future work, new device fabrication and packaging processes for efficient heat dissipation from the top of the device was also proposed
LIGHT, THE RIGHT WAY
No full textRapid urbanization in Dhaka has driven a surge in high-rise office buildings with fully glazed façades, reflecting a global architectural trend favoring transparency and daylight maximization. However, in Dhaka’s hot and humid tropical climate, extensive use of glass façades creates challenges such as visual discomfort, glare, and excessive brightness, which compromise occupant comfort and energy efficiency. This thesis investigates the impact of fully glazed office façades on daylight quality and visual comfort in Dhaka, focusing on daylight contrast and glare issues influenced by building orientation and climatic factors. Through a case study approach combining daylight simulation and on-site occupant surveys, the research evaluates current façade performance. In response, the thesis proposes optimized external shading solutions aimed at balancing daylight penetration with glare reduction to improve visual comfort and occupant well-being. Findings suggest that, without proper shading design, fully glazed façades may not deliver the expected sustainable benefits in Dhaka’s context. Proposed façade shading modifications demonstrate significant improvements in reducing these issues while maintaining natural light penetration. This study highlights the importance of context-sensitive façade design in tropical climates to enhance both energy efficiency and indoor environmental quality
Investigations of the Tribological Effects of Engine Oil Dilution by Vegetable and Animal Fat Feedstock Biodiesel on Selected Surfaces
No full textBiodiesels have become attractive alternative fuel to replace traditional fossil fuels. Biodiesels can be used in diesel engines with no major modification, but its use leads to some degree of engine oil dilution because of biodiesel leaking and scrapping to engine oil pan. Biodiesels can be made from vegetable and animal fat feedstocks. Therefore, the fatty acid methyl ester components of biodiesel may vary upon these sources of feedstock. In this thesis work, engine oil is diluted with vegetable (canola oil, peanut oil and soybean oil biodiesel) and animal (chicken fat) feedstock biodiesels at known percentages and these mixtures are tested in a pinon-disk tribometer. In-process friction force and temperature changes are observed and specific wear on the tested surface and dilution effects on viscosity are measured. The oxidative stability of diluted engine oils is also assessed by observation. Experimental results suggest that a higher fraction of palmitic and a lower fraction of linoleic acid contents of the biodiesel play a role for providing good lubricity when mixed with the engine oil in the tested condition and animal feedstock biodiesel perform better than that of vegetable feedstock biodiesel
Performance of Firth-and logF-type penalized methods in risk prediction for small or sparse binary data
No full textAbstract Background When developing risk models for binary data with small or sparse data sets, the standard maximum likelihood estimation (MLE) based logistic regression faces several problems including biased or infinite estimate of the regression coefficient and frequent convergence failure of the likelihood due to separation. The problem of separation occurs commonly even if sample size is large but there is sufficient number of strong predictors. In the presence of separation, even if one develops the model, it produces overfitted model with poor predictive performance. Firth-and logF-type penalized regression methods are popular alternative to MLE, particularly for solving separation-problem. Despite the attractive advantages, their use in risk prediction is very limited. This paper evaluated these methods in risk prediction in comparison with MLE and other commonly used penalized methods such as ridge. Methods The predictive performance of the methods was evaluated through assessing calibration, discrimination and overall predictive performance using an extensive simulation study. Further an illustration of the methods were provided using a real data example with low prevalence of outcome. Results The MLE showed poor performance in risk prediction in small or sparse data sets. All penalized methods offered some improvements in calibration, discrimination and overall predictive performance. Although the Firth-and logF-type methods showed almost equal amount of improvement, Firth-type penalization produces some bias in the average predicted probability, and the amount of bias is even larger than that produced by MLE. Of the logF(1,1) and logF(2,2) penalization, logF(2,2) provides slight bias in the estimate of regression coefficient of binary predictor and logF(1,1) performed better in all aspects. Similarly, ridge performed well in discrimination and overall predictive performance but it often produces underfitted model and has high rate of convergence failure (even the rate is higher than that for MLE), probably due to the separation problem. Conclusions The logF-type penalized method, particularly logF(1,1) could be used in practice when developing risk model for small or sparse data sets
Performance of Firth-and logF-type penalized methods in risk prediction for small or sparse binary data
No full textSUPPLEMENTARY MATERIAL
No full textSUPPLEMENTARY MATERIALToDifferential scanning calorimetry as a tool to assess the oxidation state of cold-pressed oils during shelf-life Mahbuba Islama, Anna Kaczmareka, Jolanta Tomaszewska-Grasa*a Department of Food Safety and Quality Management, Poznań University of Life Sciences, ul. Wojska Polskiego 31/33, 60-637 Poznań, [email protected], ORCID: 0000-0003-1860-3718; [email protected], ORCID: 0000-0001-7888-0026*Corresponding author: e-mail: [email protected], ORCID: 0000-0003-3964-809
