A farm level study of the impact of climate change on agriculture and farmers' adaptation in Bangladesh

This research investigates the impact of climate change on agriculture and farmers’ adaptation in a setting of a developing country. Empirical investigation is based on first hand survey data collected from rice farms situated in different climatic zones across Bangladesh.This thesis is composed of seven chapters. Chapter 1 discusses the background and motivation, aims, scope and rationale for choosing Bangladesh as the context for this research. A brief overview of the Bangladesh economy, its agriculture and the climate change situation from the historical perspective is contained in Chapter 2. Chapter 3 describes in detail the data collection procedure and some basic statistics of the data.Chapter 4 explores the impact of climate change (changes in temperature and rainfall) on cost, yield and net revenue of rice farms. While previous studies only explored the impact either on net revenue (Ricardian approach) of farms or on the yield (Production function approach) of a crop, this chapter explores the impact of climate change on cost of production as well as on yield and net revenue. Therefore, this study adds to the existing literature by providing a fuller picture regarding the impact of climate change on agriculture from a micro perspective.To see how farmers’ make adaptation decisions in response to perceived climate change, Chapter 5 investigates farmers’ perception of climate change and its determinants. Findings here add to the existing limited literature to understand farmers’ perception and the factors that influence perception.Chapter 6 then analysed farmers’ adaptation strategies so far taken, the barriers they face and the determinants of adaptation decisions. Moreover, for the first time in the literature this study examines the determinants of overcoming obstacles related to different adaptation strategies for the facilitation of farm-level adaptation in developing countries.Finally, Chapter 7 concludes the thesis with a summary of findings with relevant policy recommendations, the contribution of this research and some possible directions for future research

Estimation of Rain Attenuation at EHF bands for Earth-to-Satellite Links in Bangladesh

Due to heavy congestion in lower frequency bands, engineers are looking for new frequency bands to support new services that require higher data rates, which in turn needs broader bandwidths. To meet this requirement, extremely high frequency (EHF), particularly Q (36 to 46 GHz) and V (46 to 56 GHz) bands, is the best viable solution because of its complete availability. The most serious challenge the EHF band poses is the attenuation caused by rain. This paper investigates the effect of the rain on Q and V bands' performances in Bangladeshi climatic conditions. The rain attenuations of the two bands are predicted for the four main regions of Bangladesh using ITU rain attenuation model. The measured rain statistics is used for this prediction. It is observed that the attenuation due to rain in the Q/V band reaches up to 150 dB which is much higher than that of the currently used Ka band. The variability of the rain attenuation is also investigated over different sessions of Bangladesh. The attenuation varies from 40 dB to 170 dB depending on the months. Finally, the amount of rain fade required to compensate the high rain attenuation is also predicted for different elevation angles.Comment: Int'l Conf. on Electrical, Computer and Communication Engineering (IEEE sponsored), Cox's Bazar, Bangladesh, February 2017, pp. 589-59

An application of an auditory periphery model in speaker identification

The number of applications of automatic Speaker Identification (SID) is growing due to the advanced technologies for secure access and authentication in services and devices. In 2016, in a study, the Cascade of Asymmetric Resonators with Fast Acting Compression (CAR FAC) cochlear model achieved the best performance among seven recent cochlear models to fit a set of human auditory physiological data. Motivated by the performance of the CAR-FAC, I apply this cochlear model in an SID task for the first time to produce a similar performance to a human auditory system. This thesis investigates the potential of the CAR-FAC model in an SID task. I investigate the capability of the CAR-FAC in text-dependent and text-independent SID tasks. This thesis also investigates contributions of different parameters, nonlinearities, and stages of the CAR-FAC that enhance SID accuracy. The performance of the CAR-FAC is compared with another recent cochlear model called the Auditory Nerve (AN) model. In addition, three FFT-based auditory features – Mel frequency Cepstral Coefficient (MFCC), Frequency Domain Linear Prediction (FDLP), and Gammatone Frequency Cepstral Coefficient (GFCC), are also included to compare their performance with cochlear features. This comparison allows me to investigate a better front-end for a noise-robust SID system. Three different statistical classifiers: a Gaussian Mixture Model with Universal Background Model (GMM-UBM), a Support Vector Machine (SVM), and an I-vector were used to evaluate the performance. These statistical classifiers allow me to investigate nonlinearities in the cochlear front-ends. The performance is evaluated under clean and noisy conditions for a wide range of noise levels. Techniques to improve the performance of a cochlear algorithm are also investigated in this thesis. It was found that the application of a cube root and DCT on cochlear output enhances the SID accuracy substantially

The bee poems: Plath’s desire to recover a self

Volume 2, Issue 2, July 200

Statistical approaches to explore clinical heterogeneity in psychosis

Psychotische stoornissen tonen een zeer heterogeen klinisch beeld; iets wat vaak over het hoofd wordt gezien. Doel van dit proefschrift is om inzicht te krijgen in de heterogeniteit, stabiliteit en familiaire kwetsbaarheid van mensen met een psychose en hun broers/zussen. Om deze heterogeniteit en stabiliteit aan te tonen werd gebruikt gemaakt van classical clustering, linear, generalized linear mixed effects en group-based trajectory modeling (GBTM). Wat betref heterogeniteit, lieten we zien dat Duda en Hart de geschikte index is om cluster te identificeren. Daarmee bevestigden wij eerder studie over cognitieve subtypes vanuit het GROUP-project. Vervolgens toonden we de waarde van deze subtypes aan in de loop van de stoornis met behulp van GBTM. Stabiliteit bleek een belangrijk kenmerk bij cognitie te zijn, maar niet bij negatieve symptomen. Familiaire kwetsbaarheid kwam tot uiting in cognitie ( siblings presteerden tussen controles en patiënten), in somatische comorbiditeit (risico voor siblings lag ook tussen beide) en in psychotische belevingen (meer aanwezig bij siblings dan bij controles). Binnen dit proefschrift werd een aantal verschillende predictoren geïdentificeerd. Het cognitieve profiel van de patiënten voorspelden de cognitie van siblings. Bovendien bleek de Theory of Mind bij siblings een voorspeller voor psychotische belevingen, drie jaar later. Negatieve symptomen voorspelden functioneren in de tijd. Bij multimorbiditeit bleek familiaire kwetsbaarheid de belangrijkste voorspeller. Tenslotte was migratie de belangrijkste risicofactor voor duur van de onbehandelde psychose. Concluderend, heterogeniteit bij psychosen is een klinisch relevant concept. Subtypering van patiënten opent nieuwe wegen naar inzicht en behandeling van mensen met een psychose

MODELING TURBULENT GAS-LIQUID BUBBLY FLOW IN A VERTICAL PIPE

Bubbly gas-liquid turbulent flow occurs in various industrial applications, for example oil and gas production, petrochemical plants, nuclear reactors, etc. The analysis of bubbly gas-liquid turbulent flow remains a challenging task due to complexities such as the dispersed gas phase effects on the continuous liquid phase turbulence, interphase momentum exchange, and redistribution of the gas volume fraction due to bubble coalescence and breakup. The focus of this thesis is to develop a computational model to address these challenges. The model developed in this thesis uses a state-of-the-art two-fluid method, which minimizes computational resources and is based on the Reynolds-Averaged Navier-Stokes (RANS) equations. The predictions obtained for bubbly upward flow in a vertical pipe were validated against the available experimental data. The first part of this thesis, chapter 2, documents a one-dimensional Eulerian-Eulerian two-fluid model for mono-disperse bubbly gas-liquid flow. The main challenge is the prediction of the gas volume fraction profile, based on the radial force balance of the non-drag forces for the gas phase. The shape of the volume fraction profile across the pipe changes depending on the bubble size. The volume fraction profile exhibits a peak value near the wall and at the centre line of the pipe for smaller and larger bubbles, respectively, which is consistent with experimental measurements. For the model tested, the turbulence kinetic energy was observed to increase for larger size bubbles compared to the smaller size bubbles. The second part of the thesis, chapter 3, reports a thorough investigation of the effect of bubbles on the liquid phase turbulence, referred to as turbulence modulation. The presence of bubbles in the flow can either enhance or attenuate the liquid phase turbulence. For the same flow conditions, the effect of the turbulence modulation shows both enhancement and suppression for the turbulence kinetic energy in different locations in the pipe. A budget analysis of the turbulence transport equations was used to provide insight on the relative importance of the turbulence modulation and to identify the region where it plays a significant role. The turbulence modulation was often found to have an insignificant effect on the prediction for the mean flow variables. The third part of the thesis, chapter 4, describes a numerical study of poly-disperse gas-liquid flow, which contains bubbles of different diameter. For a poly-disperse distribution of gas bubbles, the model must account for the consequences of bubbles either breaking up or coalescing with each other. To explore their effect, an inhomogeneous multiple size group (iMUSIG) approach with a bubble coalescence and breakup model was implemented. The developed model was shown to correctly redistribute the gas volume fraction among the bubble groups based on the coalescence and breakup processes. The turbulence modulation for the poly-disperse flow was found to be larger than for the mono-disperse case, which indicates one additional effect of a poly-disperse distribution of gas bubbles. Overall, this thesis research implemented a two-fluid model that is able to capture important features of bubbly gas-liquid flow for both mono-disperse and poly-disperse cases. Some significant features of the model are: the use of a radial force balance for the gas volume fraction evaluation; a turbulence modulation contribution based on source terms in the turbulence transport equations; and incorporating the effect of coalescence and breakup processes and the resultant exchange of gas volume fraction among different bubble groups. As such, the thesis documents an improved predictive model for RANS simulations of bubbly gas-liquid flow in industrial applications

Evaluation of TRMM rainfall products for hydrological uses at different scales

The principal objectives of the thesis are two: firstly to study the accuracy of the satellite rainfall products in climatologically distinctive places at different scales and secondly to find the possibility of using satellite-rain gauge blended rainfall products for hydrological purposes. Three case study areas Catalunya, Bangladesh, and South Africa have been chosen for the analysis using the satellite rainfall products (TMPA) and rain gauge records for the period from January 2005 to December 2009. The areal pattern of rainfall has been presented using satellite rainfall products over the case study areas. Both daily and monthly products are showing good agreement with rain gauge records although it is highly variable with space and seasonality. From the results, it can be shown that TRMM satellite identified the seasonal variability of rainfall. Moreover, the mean TRMM rainfall products show same pattern as like mean rain gauge observations in daily and monthly scale in all case study areas.Finally, a blending technique is applied (originally used for radar-rain gauge blending) to conform satellite rainfall products to rain gauge observations. This blended product is also tested against the rain gauge records to verify the improvement of the blended rainfall products over the original satellite products. Results of blended rainfall products enlightens few aspects or issues that should consider before applying blending technique including density of rain gauge network and resolution of TRMM pixel