Economic Value of Water Quality Improvements in Ontario

This study estimates the economic value of lake water quality changes in South Eastern region of Ontario using the hedonic price method. The research combines 58,085 house transaction data between 2005-2014 time periods and water quality (WQ) data from 494 unique lakes. I examine the effect of total phosphorus and Secchi depth (SD) on house price using a log-linear regression. Considering SD as the variable of interest, results indicate that house buyers are willing to pay a 1.9% higher price for a one-meter improvement in SD if the house is located close to the lake WQ station. The marginal willingness to pay (MWTP) for SD reaches the peak, $7,627 per meter, for houses located within 500 meters to 750 meters distance to the lake stations. However, the price premium starts to decrease as the lake distance increases; house buyers are willing to pay 4.4$6, 142) considering houses within 3 kilometres to the lake stations. The estimated local benefits can inform the design of WQ improvement programs

The Pattern of Quality Education: A Comparative Analysis on Public and Private Universities in Bangladesh

From the beginning of the last decade the private universities have been playing massive role at tertiary education in Bangladesh. It has almost changed the total scenario, story line of the education system of the last 200 years. Private universities started with a vision, goal and amid so many barriers and obstacles. It has also sound attainment and contribution to the nation. Quality education is a prerequisite for sustainable development. For finding the determinants of quality tertiary education, studies suggest inclusion of relevant variables, as the customers are well diversified with students, their parents and guardians, and academic and administrative staff- each having different needs and objectives. Thus, this paper tries to incorporate forty nine  “Quality Characteristics” which previously found significant by various studies with a few uniquely appropriate local characteristics. The results show that the quality of private university education mainly depends upon the competence of their academic and administrative staff, the content of their curriculum, reliability of the institution, and the attitude of their staff. Keywords: Quality Dimensions, Customers, Public Universities, Private Universitie

The Interaction Effects of the Factors Influencing Knowledge and Consciousness of the Infectious Diseases: Bangladeshi Population

In this study tabular system of data along with the linear probability models were used to predict the condition of infectious diseases and to identify the impact of influential factors that affect knowledge and consciousness about infectious diseases of the studied population (Here two most important infectious diseases are considered as HIV/AIDS and Hepatitis B) level of the people. It can be mentioned that with 10% increase in the respondent’s educational attainment, the consciousness level could also be increased by 1.26%. However, 10% increase in the habit of watching TV can increase the consciousness about HIV/AIDS by 1.26% which is same as the probability of the increment of educational attainment. In the case of the consciousness about Hepatitis B1 (HB1) virus it can be seen that the with the habit of taking protected drinking water as well as with the higher educational enrollment the consciousness level about HB1 is enhanced. It can be mentioned that with 10% increase in the respondent’s habit of taking protected water, the habit of taking HB1 vaccine could also be increased by 1.36%.  However, with 10% increment in the educational attainment can also be able to increase the probability of taking HB1 vaccine which is effective protection measurement in terms of keeping oneself free from HB1 by 0.97%. Keywords: Hepatitis B1, HIV/AIDS, Linear Probability Model (LPM)

The Function of Micro Credit System in Social Amendment A Case Study on Rajshahi District in Bangladesh

Micro-credits an extremely small loan given to impoverished people to help them become self employed havebecome an important tool in development economics and play an essential role in the fight against poverty, inparticular with respect to the self-sufficient of women. Since Muhammad Yunus, the founder of the Grameen Bank2,received the Nobel Prize for Peace in 2006, microcredit-systems have been increasingly conceptualized as part of aprofit-oriented “financial system approach”.For more than twenty years, microcredit has been widely heralded as theremedy for world poverty. Recent news stories, however, have sullied microcredit’s glowing reputation with reportson scandals, exorbitant compensation to managers, skyrocketing interest rates, and aggressive marketing schemes.Once praised as a universal panacea, microlenders are now being widely attacked as predatory loan sharks. (Korten,2011)However, in this paper we will discuss different approaches to micro-credits dealing with the question of howfar different concepts influence societal gender arrangements and under which circumstances micro-credits are usefultools for the self-sufficient of women in a sustainable way. For this reason, the results of an empirical studyconducted in Rajshahi will be presented in order to develop a multilayer model for the self-sufficient of womenwhich shows possible impacts of micro-credits on the individual level (micro level), the community level (centrallevel) as well as the socio-political level (macro level)Keywords: Self -sufficient Women, Micro credit, Social Amendment, Fund for Development (SFD)

Meeting Basic Needs of Internal Migrants in the Slums of Dhaka:A Temporal Account at Places of Origin and Places of Destination

Purpose: This study makes a comparative assessment of access to basic services, disease issues and economic conditions of disadvantaged internal migrants related to their places of origin and places of destination. Design: This cross-sectional study compares participants’ present and retrospective information (before migration) based on the same types of questions. The analysis took place in seven slums located in the Mohammadpur, Rayerbazar and Jigatola areas of Dhaka City in Bangladesh; 74 participants who had migrated from rural places of origin were interviewed. Findings: The results showed some improvements for the migrants in basic household infrastructure and hygiene practices after migrating to these slums compared to their previous status in places of origin. However, the frequency of diseases increased in the short to medium term after migration, as reported by the participants. The study argues that increased incidents of disease at places of destination can be associated with limited access to free healthcare benefits and the burden of increased living costs compared to the participants’ places of origin. Value: This study considered some key issues of internal migration, with a temporal account before migration at places of origin and after migration at places of destination. The feedback from the disadvantaged migrants who compared their current living conditions with life at their place of origin has not previously been studied in low income countries

Towards a Framework for Acquisition and Analysis of Speeches to Identify Suspicious Contents through Machine Learning

The most prominent form of human communication and interaction is speech. It plays an indispensable role for expressing emotions, motivating, guiding, and cheering. An ill-intentioned speech can mislead people, societies, and even a nation. A misguided speech can trigger social controversy and can result in violent activities. Every day, there are a lot of speeches being delivered around the world, which are quite impractical to inspect manually. In order to prevent any vicious action resulting from any misguided speech, the development of an automatic system that can efficiently detect suspicious speech has become imperative. In this study, we have presented a framework for acquisition of speech along with the location of the speaker, converting the speeches into texts and, finally, we have proposed a system based on long short-term memory (LSTM) which is a variant of recurrent neural network (RNN) to classify speeches into suspicious and nonsuspicious. We have considered speeches of Bangla language and developed our own dataset that contains about 5000 suspicious and nonsuspicious samples for training and validating our model. A comparative analysis of accuracy among other machine learning algorithms such as logistic regression, SVM, KNN, Naive Bayes, and decision tree is performed in order to evaluate the effectiveness of the system. The experimental results show that our proposed deep learning-based model provides the highest accuracy compared to other algorithms