Neoliberal Urbanism In Transforming Toronto?s Built Urban Landscape: The Case Of Yonge And Dundas Square

Scholars in the 1980s and 1990s often characterized Toronto as the 'city that works'. However, by the late 1990s there was a shift in policy by the provincial government to amalgamate Toronto's five neighbouring municipalities. Amalgamation created a mega city of 2.5 million residents. The reason for amalgamation was to increase Toronto's global competitiveness, a key neoliberal policy framework. Neoliberalism also refers to deregulation of state control over public services. Peck et al. (2009) devised a chart to outline the specific elements of neoliberalism that alter the built urban landscape. These are: the elimination of urban public spaces, speculative redevelopment in working class neighbourhoods, withdrawal from community planning initiatives, the privatization of space for elite/corporate consumption, undertaking of mega-projects to attract corporate investment, creation of gated communities, continuation of gentrification, and the adoption of the 'highest and best use' principle in major land use planning decisions. This major paper applies their criteria to the redevelopment of Yonge-Dundas Square as a case study. I conclude that Peck, et al.'s (2009) elements are indeed useful in considering how neoliberalism influences planning processes, and decision making. My findings suggest a lack of public accessibility to public space, and the reproduction of urban inequalities and disenfranchisement in the city. I discuss how their criteria may inform studies of ongoing and future development in Toront

Environmental & Financial Benefits of 360 kW Photo Voltaic Solar System (On-Grid) in University of Wah

In the 21st century, the utilization and application of renewable energy resources are the need of the hour. Currently, in Pakistan, the cost of electricity per unit is very high and it has a huge effect on financial matters. In this study, we have analyzed the 360 kW Photovoltaic (PV) Solar system (On-Grid) installed at the University of Wah, its effects on the financial aspects, and environment change before and after its installation and operation. There are many types of renewable energy resources but not all of them are environmentally friendly. The University of Wah opted for the PV Solar system because it is environmentally friendly with no carbon emissions and requires very less maintenance. In this paper, we have also discussed, how this system benefits the local community and benefits the environment. All the facts and statistics about the 360 kW PV Solar System (On-Grid) are shared in detail.Keyword: Photovoltaic solar panels, Electricity Demand, Renewable energy, Environmentally friendly, Climate chang

Determinant Attributes of Customer Choice of Banks, Supplying Mortgage Products

The present study focuses on finding out the main attributes that determine the customer’s choice of bank for supplying the mortgage products. The data has been gathered through questionnaires from 400 customers using mortgage products of different banks. Reviewing the literature four variable are taken for study to determine the dependent variable customer choice of banks using mortgage products and they include cost of bank, quality of services, confidence of customer in bank and convenience of customer using mortgage product. Results were analyzed using ordinary least square (OLS) regression and correlation techniques and findings of the data have been tested which appeared as significant statistically. The results indicated that choice of customers for the mortgage product depends on all the independent variables like quality of services, cost of mortgage product, confidence level of customers build by the bank and convenience of the customers. Further analysis can be done on exploring more independent variables, which are important for customers in choosing a bank providing mortgage products

Sentiment Analysis in the Era of Web 2.0: Applications, Implementation Tools and Approaches for the Novice Researcher

Nowadays, people find it easier to express opinions via social media-formally known as Web 2.0. Sentiment analysis is an essential field under natural language processing in Computer Science that deals with analyzing people's opinions on the subject matter and discovering the polarity they contain. These opinions could be processed in collective form (as a document) or segments or units as sentences or phrases. Sentiment analysis can be applied in education, research optimization, politics, business, education, health, science and so on, thus forming massive data that requires efficient tools and techniques for analysis. Furthermore, the standard tools currently used for data collection, such as online surveys, interviews, and student evaluation of teachers, limit respondents in expressing opinions to the researcher's surveys and could not generate huge data as Web 2.0 becomes bigger. Sentiment analysis techniques are classified into three (3): Machine learning algorithms, lexicon and hybrid. This study explores sentiment analysis of Web 2.0 for novice researchers to promote collaboration and suggest the best tools for sentiment data analysis and result efficiency. Studies show that machine learning approaches result in large data sets on document-level sentiment classification. In some studies, hybrid techniques that combine machine learning and lexicon-based performance are better than lexicon. Python and R programming are commonly used tools for sentiment analysis implementation, but SentimentAnalyzer and SentiWordnet are recommended for the novice. Keywords:   Sentiment Analysis; Web 2.0; Applications; Tools; Novic

Surgical Management of Intracranial Aneurysms and Subarachnoid Haemorrhage : An Overview

Egas Moniz discovered an aneurysm by cerebral Angiography in 1933.1       Cushing introduced first aneurysmal clip in 1911, Mayfield modified the existing spring clip with cross leg (Schwartz) by making it a smaller, tweezer – like applicator.2       An intracranial vascular procedure was first repor-ted with aid of operating microscope which introduced simultaneously magnification and illumination.3       Dott in 1933performed 1st planned intracranial surgery for a saccular aneurysm.4       Dandy in 1937 clipped the neck of aneurysm with a metallic clip.5       Yasirgill of Zurich and Drake of London Ontario, published a lot onaneurysms of anterior & posterior circulation.6,7       An elaborated study of natural history of aneurysm was published by the pakarinen in 196.7

Sentiment analysis of student's opinion on programming assessment using naive bayes algorithm on small data

Student opinion could be used to facilitate institutions to improve the quality of teaching and learning by delivering the appropriate teaching method based on the student’s learning experience. The purpose of this study is to investigate the efficiency of data mining techniques for the sentiment analysis of student opinion on programming subject assessment. Two machine learning algorithms, which are Support Vector Machine (SVM) and Naïve Bayes (NB) have been identified to be the best in sentiment analysis on large data. SVM performs better than NB on big data but the case may not be the same on small dataset. The research aim is to design a framework that will investigate the efficiency of Naïve Bayes algorithm on two sentiment classification classes namely positive and negative on small dataset. A comparative performance measure is done using SVM and lexicon-based approach. Learning programming is considered as a difficult course for the beginners, specifically for the first-year student. The opinions of 175 first-year undergraduate students at School of Computing, Universiti Teknologi Malaysia 2018/2019 session regarding their experience in the assessment of skill-based test 1 and test 2 were collected via an online survey. The result of classifying students’ opinions using the NB algorithm had a negative prediction accuracy of 92% and a positive prediction accuracy of 75%. NB had a prediction accuracy of 85% which outperformed both the SVM with 70% and lexicon-based approach with 60% accuracy. The result shows that NB works better than SVM and Lexicon-based approach on small dataset. The findings from the analysis of the survey show that the student’s sentiment is classified as negative, which implies that the skill-based test is difficult and gives scary emotions to the students which may further affect students interest in programming assessment. The key finding of this study discovers that the policy of awarding zero scores to students’ whose program did not compile successfully, hinders the programming assessment of first-year undergraduate students in the School of Computing, Universiti Teknologi Malaysia

Agricultural Management Strategy on Food Security in Taraba State

The increasing population of the world is becoming worrisome compare with the food production or agricultural activities that is considered to be backward or inadequate because of certain factors that thwart agricultural activities like the climate change and lack of modern agricultural equipments for commercial agricultural activities, family, community and government are developing a means to an end on how food security and other agricultural activities can be boaster to meet up the growing population. This paper suggest strategic of agricultural management that will support food security in Taraba state in order to meet up the growing population in the state. The paper further recommends food security measures for the state and the Nation at large. Keywords: agricultural management strategy, food security and Taraba Stat

Development and Validation of Lecturer Teaching Assessment Scale for Nigerian Universities

This study is part of a research funded through the Tertiary Education Trust Fund (TETFund) research grant, Abuja Nigeria. The authors are therefore grateful to the TETFund office Abuja and Taraba State University Management for facilitating the grant. Abstract The present study developed and examined the factorial validity of scores on the Lecturer Teaching Assessment Scale across lecturers of universities in North-east Nigeria.  This study presents a validation report of the Lecturer’s Teaching Assessment Scale (LECTAS) developed for the assessment of lecturer’s teaching effectiveness in Universities. It also examined the factor structure of the LECTAS, its logical validity, and internal consistency reliability coefficients. The study adopted the Developmental and survey research designs. A total of 2600 students that completed the developed LECTAS constituted the sample for the study. The 34-item LECTAS was used to collect data for the study. Collected data were subjected to reliability and factor analyses. Results showed that the scale is valid and reliable in assessing lecturers teaching output. The LECTAS was adjudged to possess construct validity. The results revealed that the LECTAS was reliable (Cronbach Alpha reliability coefficient of 0.932. Thus, the LECTAS possessed adequate psychometric qualities that make it suitable to assess lecturers’ teaching effectiveness in Nigerian universities. Keywords: Development, Factor Analysis, Teaching Assessment, Validation, Scaling DOI: 10.7176/JEP/10-5-0

Arthritis imaging using a near-infrared fluorescence folate-targeted probe

A recently developed near-infrared fluorescence-labeled folate probe (NIR2-folate) was tested for in vivo imaging of arthritis using a lipopolysaccharide intra-articular injection model and a KRN transgenic mice serum induction mouse model. In the lipopolysaccharide injection model, the fluorescence signal intensity of NIR2-folate (n = 12) and of free NIR2 (n = 5) was compared between lipopolysaccharide-treated and control joints. The fluorescence signal intensity of the NIR2-folate probe at the inflammatory joints was found to be significantly higher than the control normal joints (up to 2.3-fold, P < 0.001). The NIR2-free dye injection group showed a persistent lower enhancement ratio than the NIR2-folate probe injection group. Excessive folic acid was also given to demonstrate a competitive effect with the NIR2-folate. In the KRN serum transfer model (n = 4), NIR2-folate was applied at different time points after serum transfer, and the inflamed joints could be detected as early as 30 hours after arthritogenic antibody transfer (1.8-fold increase in signal intensity). Fluorescence microscopy, histology, and immunohistochemistry validated the optical imaging results. We conclude that in vivo arthritis detection was feasible using a folate-targeted near-infrared fluorescence probe. This receptor-targeted imaging method may facilitate improved arthritis diagnosis and early assessment of the disease progress by providing an in vivo characterization of active macrophage status in inflammatory joint diseases