Agricultural efficiency of rice farmers in Myanmar : a case study in selected areas

This paper try to analyze unique data set for rice producing agricultural households in some selected areas of Bago and Yangon divisions to examine the households' profit efficiency and the relationship between farm and household attributes and profit inefficiency using a Cobb-Douglas production frontier function. The frequency distribution reveals that the mean technical inefficiency is 0.1627 with a minimum of 3 percent and maximum of 73 percent which indicates that, on average, about 16% of potential maximum output is lost owing to technical inefficiency in both studied areas. While 85% of the sample farms exhibit profit inefficiency of 20% or less, about 40% of the sample farms is found to exhibit technical inefficiency of 20% or less, indicating that among the sample farms technical inefficiency is much lower than profit inefficiency.Myanmar, Rice, Farmers, Agricultural economies, Household, Efficiency, Production frontier function

Modeling of quad-station module cluster tools using petri nets

The semiconductor industry is highly competitive, and with the recent chip shortage, the throughput of wafers has become more important than ever. One of the tools that the industry has deployed is to use of quad-station modules instead of the traditional single-station modules that allow for higher throughput and better wafer consistency by processing multiple wafers at the same time and distributing work. The industry trend is to use multiple transfer chamber robots to stack the quad-station modules in a series, particularly for etch products. In this work, the quad-station cluster tool wafer movement is modeled by using Petri net as a process-bounded system. The system analysis and simulations are performed by using timed and colored Petri nets. The results are useful to deepen our understanding of the discrete-event dynamics of quad-station module cluster tools and offer the highly needed insight into their efficient and deadlock-free operation

Business Intelligence (BI) System for Budgeting and Customer Satisfaction

This research is about a casino company that wishes to use Business Intelligence (BI) system to solve their budgeting problems while attracting customers. They provided the dataset required to analyse their two casino branches and find what actions that they need take, with the help of visualizations. After analysing the visualizations, it was clear that there were many machines that their customers are not found of and that video machines are the most popular among the three types of machines. The least played type of machine was vpoker and only two manufactures provide them with the machines. The likely reason for people do not playing vpoker is that it requires mental strength and mathematics. It was also clear that customers come to the casinos in April, possibly due to holidays. With the help of new technologies, they can gather more information from their customers, without upsetting them and increasing the security to prevent vandalism and destruction of property by angry customers

Agricultural efficiency of rice farmers in Myanmar : a case study in selected areas

This paper try to analyze unique data set for rice producing agricultural households in some selected areas of Bago and Yangon divisions to examine the households\u27 profit efficiency and the relationship between farm and household attributes and profit inefficiency using a Cobb-Douglas production frontier function. The frequency distribution reveals that the mean technical inefficiency is 0.1627 with a minimum of 3 percent and maximum of 73 percent which indicates that, on average, about 16% of potential maximum output is lost owing to technical inefficiency in both studied areas. While 85% of the sample farms exhibit profit inefficiency of 20% or less, about 40% of the sample farms is found to exhibit technical inefficiency of 20% or less, indicating that among the sample farms technical inefficiency is much lower than profit inefficiency

Modification of Diesel Engine to Producer Gas Engine

This paper describes considerations and procedure of conversion from diesel engine to producer gas engine. In this paper, the performance of producer gas engine is compared to the original diesel engine and the factors affecting on performance of the producer gas engine are mentioned. After converting the 26.5 kW diesel engines to producer gas engine, the power output of producer gas engine is 40% less than that of original diesel engine. However producer gas engines are used for saving fuel cost and more economic for long time span. The comparison based on 8 kW electricity output that running for 4 hours in a day found that fuel cost for producer gas engine is Ks (Kyats) 2167 and the fuel cost for diesel engine is Ks.(Kyats) 7680, this means save cost of Ks (Kyats) 2008960 along the engine life span

An analysis of benefits to women from different financial services : case study in Meiktila district, Mandalay region

This analysis focuses on women’s inclusion in financial services, and the factors that influence their ability to access financial resources. It traces patterns in the development of, and access to microcredit programs and their effects on women’s (and their children’s) lives. Women in the Mandalay region of Myanmar were interviewed (2019) regarding microcredit financing and access, the effects on poverty reduction, women’s empowerment, and any social benefits accrued through an increase in household income

Fuzzy Logic Based Dam Water Shutter Control System by Using Water Level and Rainfall Condition in Raining Season

A robust water shutter management system ensures that the water does not overflow and destroy or damage the dam. During the rainy season, care must be taken when dams conserve water, if the reservoir volume is too high, the risk of dam failure may be increased. So water level control is a special matter in the rainy season. Fuzzy logic sets provide better control than binary logic-based methods because they are used to determine the meaning of qualitative values for controller inputs and outputs, such as small, medium, and large control actions. This system used the fuzzy logic control theory in the water shutter management system to get smoothness motor control values of small, very small, medium, large, and very large. The system uses ultrasonic sensors to detect water levels, rain sensors to detect rain, and fuzzy logic controls to control the PWM duty cycle to the shutter gate motor driver circuit based on the detection of these two sensors. This control strategy is implemented with Arduino Uno

ANALYSIS AND SYNTHESIS OF PRECISION RESOLVER SYSTEM

Ph.DDOCTOR OF PHILOSOPH

New imaging signatures of cardiac alterations in ischaemic heart disease and cerebrovascular disease using CMR radiomics

Background: Ischaemic heart disease (IHD) and cerebrovascular disease are two closely inter-related clinical entities. Cardiovascular magnetic resonance (CMR) radiomics may capture subtle cardiac changes associated with these two diseases providing new insights into the brain-heart interactions.Objective: To define the CMR radiomics signatures for IHD and cerebrovascular disease and study their incremental value for disease discrimination over conventional CMR indices.Methods: We analysed CMR images of UK Biobank's subjects with pre-existing IHD, ischaemic cerebrovascular disease, myocardial infarction (MI), and ischaemic stroke (IS) (n = 779, 267, 525, and 107, respectively). Each disease group was compared with an equal number of healthy controls. We extracted 446 shape, first-order, and texture radiomics features from three regions of interest (right ventricle, left ventricle, and left ventricular myocardium) in end-diastole and end-systole defined from segmentation of short-axis cine images. Systematic feature selection combined with machine learning (ML) algorithms (support vector machine and random forest) and 10-fold cross-validation tests were used to build the radiomics signature for each condition. We compared the discriminatory power achieved by the radiomics signature with conventional indices for each disease group, using the area under the curve (AUC), receiver operating characteristic (ROC) analysis, and paired t-test for statistical significance. A third model combining both radiomics and conventional indices was also evaluated.Results: In all the study groups, radiomics signatures provided a significantly better disease discrimination than conventional indices, as suggested by AUC (IHD:0.82 vs. 0.75; cerebrovascular disease: 0.79 vs. 0.77; MI: 0.87 vs. 0.79, and IS: 0.81 vs. 0.72). Similar results were observed with the combined models. In IHD and MI, LV shape radiomics were dominant. However, in IS and cerebrovascular disease, the combination of shape and intensity-based features improved the disease discrimination. A notable overlap of the radiomics signatures of IHD and cerebrovascular disease was also found.Conclusions: This study demonstrates the potential value of CMR radiomics over conventional indices in detecting subtle cardiac changes associated with chronic ischaemic processes involving the brain and heart, even in the presence of more heterogeneous clinical pictures. Radiomics analysis might also improve our understanding of the complex mechanisms behind the brain-heart interactions during ischaemia

Debiasing Cardiac Imaging with Controlled Latent Diffusion Models

The progress in deep learning solutions for disease diagnosis and prognosis based on cardiac magnetic resonance imaging is hindered by highly imbalanced and biased training data. To address this issue, we propose a method to alleviate imbalances inherent in datasets through the generation of synthetic data based on sensitive attributes such as sex, age, body mass index, and health condition. We adopt ControlNet based on a denoising diffusion probabilistic model to condition on text assembled from patient metadata and cardiac geometry derived from segmentation masks using a large-cohort study, specifically, the UK Biobank. We assess our method by evaluating the realism of the generated images using established quantitative metrics. Furthermore, we conduct a downstream classification task aimed at debiasing a classifier by rectifying imbalances within underrepresented groups through synthetically generated samples. Our experiments demonstrate the effectiveness of the proposed approach in mitigating dataset imbalances, such as the scarcity of younger patients or individuals with normal BMI level suffering from heart failure. This work represents a major step towards the adoption of synthetic data for the development of fair and generalizable models for medical classification tasks. Notably, we conduct all our experiments using a single, consumer-level GPU to highlight the feasibility of our approach within resource-constrained environments. Our code is available at https://github.com/faildeny/debiasing-cardiac-mri