Ensemble Machine Learning Approaches for Detection of SQL Injection Attack

In the current era, SQL Injection Attack is a serious threat to the security of the ongoing cyber world particularly for many web applications that reside over the internet. Many webpages accept the sensitive information (e.g. username, passwords, bank details, etc.) from the users and store this information in the database that also resides over the internet. Despite the fact that this online database has much importance for remotely accessing the information by various business purposes but attackers can gain unrestricted access to these online databases or bypass authentication procedures with the help of SQL Injection Attack. This attack results in great damage and variation to database and has been ranked as the topmost security risk by OWASP TOP 10. Considering the trouble of distinguishing unknown attacks by the current principle coordinating technique, a strategy for SQL injection detection dependent on Machine Learning is proposed. Our motive is to detect this attack by splitting the queries into their corresponding tokens with the help of tokenization and then applying our algorithms over the tokenized dataset. We used four Ensemble Machine Learning algorithms: Gradient Boosting Machine (GBM), Adaptive Boosting (AdaBoost), Extended Gradient Boosting Machine (XGBM), and Light Gradient Boosting Machine (LGBM). The results yielded by our models are near to perfection with error rate being almost negligible. The best results are yielded by LGBM with an accuracy of 0.993371, and precision, recall, f1 as 0.993373, 0.993371, and 0.993370, respectively. The LGBM also yielded less error rate with False Positive Rate (FPR) and Root Mean Squared Error (RMSE) to be 0.120761 and 0.007, respectively. The worst results are yielded by AdaBoost with an accuracy of 0.991098, and precision, recall, f1 as 0.990733, 0.989175, and 0.989942, respectively. The AdaBoost also yielded high False Positive Rate (FPR) to be 0.009

ANTIDIABETIC POTENTIAL OF PERSIMMON PULP POWDER ON ALLOXAN INDUCED DIABETIC RABBITS

Diabetes, a condition when blood glucose level goes beyond the normal range. Natural treatments particularly through bioactive components from fruit and vegetable sources are becoming popular worldwide and are broadly accepted because of no side effects and cost effectiveness. The present study was planned to investigate the antidiabetic potential of persimmon pulp powder by using alloxan induced diabetic rabbits as an animal model. For this purpose, fifteen rabbits were induced Diabetes mellitus by alloxan and divided into three groups. Persimmon pulp powder supplemented diets (0%, 10% and 20%) were given to the diabetic rabbits for the duration of 21 days. The blood samples of rabbits were examined for glucose, serum creatinine and urea levels on weekly basis. The results indicated that there was a significant decline in glucose as well as creatinine and urea levels in blood of diabetic rabbits. The reduction of blood glucose level was ranged from 357.66 mg/dL to 256.45 mg/dL on administration of 20% persimmon peel powder in the feed of rabbits. Similarly, serum creatinine and urea levels were also significantly reduced 1.42 mg/dl and 1.22 mg/dl and 47.50 mg/dl and 24.22 mg/dl, respectively because of supplementation of 20% persimmon pulp powder. It is concluded from the results that persimmon pulp powder might be a potential natural antidiabetic treatment of diabetic complications

DIETARY DIVERSITY AND RURAL LABOR PRODUCTIVITY: EVIDENCE FROM PAKISTAN

The relationship between rural labor productivity and food diversity was analyzed from the household consumption survey data of Pakistan. The elasticity of wage to diversity (0.77) was higher than to food expenditure (0.13). Lowering the prices of meats and fruits and vegetables will have the greatest impact on labor productivity.Food Consumption/Nutrition/Food Safety, Labor and Human Capital,

Determinants of Organ Donor Registration Rates Among Young Americans

In this paper I examine the factors that affect the likelihood an individual is a registered organ donor. Unlike many studies which focus on subpopulations in specific regions, I utilize national data to get a broader assessment of individuals from around the country across a number of racial and religious classifications. Using a probit model and controlling for a variety of parameters, I find that some racial and religious variables are negatively and significantly associated with organ donor registration rates, while education and being female are positively associated with organ donor registration rates. I conclude by discussing the implications of my results and the potential for future research

Designing an e-Model for Open and Distance Learning in Pakistan

This descriptive research focused on designing an e-model for open and distance learning (ODL) in Pakistan. After studying various e-models, blended learning and issues relating to ODL in Pakistan, the researcher designed and executed an e-model on a group of students. The researcher designed and offered online Postgraduate Diploma in Teaching of English as a Foreign Language (TEFL) offered by Allama Iqbal Open University (AIOU) Islamabad, Pakistan. The participants’ feedback supported e-model as a solution to their problems which they were facing in traditional ODL programs. The online courses improved their learning, reduced their expenses incurred on attending tutorials, improved tutor-students and student-student interaction. Keywords: e-learning, open and distance learning, English language teachin

Emotional Intelligence and Language Competence: A Case Study of the English Language Learners at Taif University English Language Centre

Variation in general abilities of human beings gave birth to the concept of intelligence. Since 1990, when for the first time emotional intelligence was introduced, it has become a buzzword in many fields including education, management studies, and artificial intelligence. Within the context of foreign language learning, it is being applied in educational institutions for language competence. An empirical study was conducted on English language learners at Taif University English Language Centre (TUELC) to find out relationship between their Emotional Intelligence (EI) and language competence. For this study, a group of 200 (male and female) students were selected randomly studying English at the undergraduate level. Data collected through EI Inventory was matched with their academic achievement in English language based on assessment of four skills. The result revealed a close relationship between EI and language competence of undergraduate students at TUELC and EI also affects students’ English language competence