Development and Identification of Metrics to Predict the Impact of Dimension Reduction Techniques on Classical Machine Learning Algorithms for Still Highway Images

We are witnessing an influx of data - images, texts, video, etc. Their high dimensionality and large volume make it challenging to apply machine learning to obtain actionable insight. This thesis explores several aspects pertaining to dimensional reduction: dimension reduction methods, metrics to measure distortion, image preprocessing, etc. Faster training and inference time on reduced data and smaller models which can be deployed on commodity hardware are a critical advantage of dimension reduction. For this study, classical machine learning methods were explored owing to their solid mathematical foundation and interpretability. The dataset used is a time series of images from several camera feeds observing the traffic, weather and road conditions along highways. The time-series nature of dataset gives rise to interesting questions which are investigated in this work. For instance, can machine learning models trained on past data be used on future camera feed data? This is highly desirable and yet difficult due to the changing weather, road conditions, traffic conditions and scenery. Can dimension reduction models obtained from past data be used for reducing dimensionality of future data? This thesis also examines the difference between the performance of machine learning methods before and after application of dimension reduction. It tests some existing metrics to measure quality of dimension-reduced data set and introduces several new ones. It also examines the application of image pre-processing methods to boost the performance of classifiers. The classification performance with and without random sampling has been studied as well

Meursault’s indifferent stance: a conscious acceptance of capitalism

Volume 3, Issue 1, January 201

Modified signomial geometric programming (MSGP) and its applications

A "signomial" is a mathematical function, contains one or more independent variables. Richard J. Duffin and Elmor L. Peterson introduced the term "signomial". Signomial geometric programming (SGP) optimization technique often provides a much better mathematical result of real-world nonlinear optimization problems. In this research paper, we have proposed unconstrained and constrained signomial geometric programming (SGP) problem with positive or negative integral degree of difficulty. Here a modified form of signomial geometric programming (MSGP) has been developed and some theorems have been derived. Finally, these are illustrated by proper examples and applications

Fuzzy E.O.Q model with constant demand and shortages: A fuzzy signomial geometric programming (FSGP) approach

In this paper, a fuzzy economic order quantity (E.O.Q) model with shortages under fully backlogging and constant demand is formulated and solved. Here the model is solved by fuzzy signomial geometric programming (FSGP) technique. Fuzzy signomial geometric programming (FSGP) technique provides a powerful technique for solving many non-linear problems. Here we have proposed a new idea that is fuzzy modified signomial geometric programming (FMSGP) and some necessary theorems have been derived. Finally, these are illustrated by some numerical examples and applications

A fuzzy inventory model with unit production cost, time depended holding cost, with-out shortages under a space constraint: a parametric geometric programming approach

In this paper, an Inventory model with unit production cost, time depended holding cost, with-out shortages is formulated and solved. We have considered here a single objective inventory model. In most real world situation, the objective and constraint function of the decision makers are imprecise in nature, hence the coefficients, indices, the objective function and constraint goals are imposed here in fuzzy environment. Geometric programming provides a powerful tool for solving a variety of imprecise optimization problem. Here we have used nearest interval approximation method to convert a triangular fuzzy number to an interval number then transform this interval number to a parametric interval-valued functional form and solve the parametric problem by geometric programming technique. Here two necessary theorems have been derived. Numerical example is given to illustrate the model through this Parametric Geometric-Programming method

HOUSEHOLDS’ WILLINGNESS TO PAY FOR IMPROVED DRINKING WATER- A CASE STUDY ON KHULNA CITY CORPORATION USING DISCRETE CHOICE MODEL

The purpose of the study is to find out the willingness to pay for improved drinking water services using Discrete Choice Model (DCM). To carry out the study, concept profiling has been done and data have been collected randomly from 120 households from two areas, Basupara and Najirghat of Ward-26 of KCC. Multinomial Logit Model (MLM) has been taken to into consideration to see relative willingness to pay (WTP) for accessing improved drinking water services being in status quo position. The study explores that, people who have the willingness to pay BDT 450 are 9.67 times higher than the willingness to pay BDT 250. On the other hand, people who have the willingness to pay BDT 600 are about 2.38 times more likely to choose Alternative-2 option than those who have the willingness to pay BDT 250.&nbsp

Proof without Words: (a+b+c)^2,(a+b-c)^2,(a+b+c)^2-(a+b-c)^2

In this proof without words, we prove wordlessly the following theorems,(a+b+c)^2=a^2+b^2+c^2+2ab+2bc+2ca(a+b-c)^2=a^2+b^2+c^2+2ab-2bc-2ca(a+b+c)^2-(a+b-c)^2=4c(a+b

Proof Without Words: Arithmetic Mean / Geometric Mean Inequality

The author proves almost wordlessly the Arithmetic Mean / Geometric Mean Inequality

Divergence among Students for E- Learning Skills in Different Districts of Jammu & Kashmir

In today’s world due to the development of technology a student can gain more information through online environment, many higher education institutions have both traditional learning and e-learning in order to deliver best knowledge and train the students in their specialized courses. E-Learning has changed our world of learning for the students, now a days students has started using social networking websites to learn and share day to day activity, it provides features like uploading and sharing photo, sending and receiving messages and searching and connecting friends and communities. The social websites enables people to be active and selective in their exposure to communicating and sharing. The aim of this research paper is to discuss about e-learning through students perception that what a student thinks about the e-learning system i.e. in e-learning students learning is personalized, he can learn anytime, anywhere, can learn based on his pace, etc. All these questions were distributed to the students of different institutions of different districts of Jammu and Kashmir through questionnaires and were also asked through personal interview and it shows us how familiar students are with use of e-learning. The result was then analyzed for analysis for variance of variance (ANOVA) in a randomized block design with three replicates using and SPSS to understand the significance of difference between the elements. It is clear from the results that most of the students are familiar with the e-learning system and are supporting e-learning

THE IMPACT OF BRAND TRUST AND BRAND RELATIONSHIP QUALITY ON BRAND LOYALTY IN THE CONTEXT OF EMERGING MARKET LIKE PAKISTAN

Purpose: The concept of brand loyalty is of critical importance to the business as it plays a dominant role in providing competitive advantages for the companies and brands in devising their marketing strategies. With the advent of modern digital platforms of consumer interaction with the brands, the focus of marketing is shifting towards relationships from the traditional approach of marketing mix. So, the emphasis is made by researchers on the determinants and approaches of building relationships between consumer and brand that eventually foster brand loyalty. Methodology: Sample size for this study was 160 with a respondent response rate of 94.3 %. Survey method through questionnaire was adopted to collect data for this study. Constructs were adopted from relevant and established literature. It had 5 items related to demographic based on nominal scale. Additionally, it had 42 items related to the prime objectives of the study. It was based on 7 points grading scale. After preliminary analysis including normality, validity and reliability, an analysis of multiple regression was carried out to test the desired hypothesis. Findings: The study found that brand trust was the strongest predictor of consumers’ brand loyalty towards a particular preferred brand, followed by brand relationship quality, perceived quality and brand identification. The study has taken a narrow perspective with limited number of variables. Further studies would incorporate higher number of variables. Additionally, other studies could incorporate the mediating and moderating roles of independent variables and demographic & other factors. Conclusion: The firm should focus to enhance the trust related to brand among customers to stabilize the consumers’ brand loyalty