Predicting the stock prices’ movement has been considered a tedious task due to the stock market's volatile behavior. This study is an attempt to predict stock prices based on 15 trading factors by applying deep learning algorithm support vector machine (SVM) on daily price data of three stocks of COVID-19, collected from secondary sources and processed through Python software. The finding of this study suggests that the linear kernel gives 53%, the polynomial kernel gives 46% and the radical basis function (RBF) kernel gives 62% validation accuracy, which shows the RBF kernel predictive ability is highest than others during high volatility. The current study contributes to the stock return literature-originated machine learning algorithms during the unprecedented market condition. The finding of this study is helpful for investors and traders who calculate stock return in their portfolio diversified decisions, regulators, and policymakers in the formulation of their regulations & implementation decisions while the market condition is unprecedented. Thus, the support vector machine (SVM) algorithm offers an accurate prediction of stock return to investors who invest during high volatility.

Anemia remains a major public health concern in all nations, particularly affecting children worldwide. This disorder, which is defined as low hemoglobin or red blood cells in the blood, has multiple causes, the most common one being iron deficiency. The prevalence of anemia among children in Pakistan have been modeled by conducting a thorough statistical analysis emphasizing on inferential statistics and estimation techniques. The study explores the classical and non-classical essential categories of estimating methodologies. The work specifically looks into Bayesian estimation methods under squared error loss function (SELF) and weighted square error loss function (WSELF) for a new generalization of the Exponential Distribution introduced by Nadarajah Haghighi(2017) named as Nadarajah Haghighi Distribution (NHD). The Bayesian estimation of the parameters of NH distribution is run under uniform prior (Non-Informative) and exponential prior (Informative prior). The Lindley approximation method is utilized in this study to solve Bayesian integral. This methodology's practical application focuses on determining Pakistan's under-five-year-old population's anemia prevalence. Both maximum likelihood and Bayesian estimators by means of Monte Carlo simulations and practical application are used to thoroughly compared. Notably, it is empirically reveal that Bayesian estimation technique performs better than the classical estimation technique both in case of simulation and in modeling the prevalence of anemia among Pakistani children.

This study delves into the optimization strategies of Amazon Web Services (AWS) cloud computing solutions tailored specifically for businesses. It provides an in-depth exploration of the transformative impact that cloud computing has had on modern business operations, emphasizing the pivotal role played by AWS in delivering scalable, flexible, and cost-effective resources. With projections indicating the global public cloud services market's growth to $332.3 billion in 2021, it becomes evident that cloud solutions are increasingly relied upon, with AWS commanding a significant 32% market share. This paper highlights the importance of optimizing AWS solutions, considering its extensive range of services designed to meet diverse business needs. However, transitioning to cloud environments brings challenges related to data security, compliance, integration, and migration complexities, as evidenced by pertinent studies and literature reviews. This research synthesizes insights gleaned from various studies, emphasizing the adaptability and cost-effectiveness of AWS while stressing the critical role of robust security measures in its implementation across industries and geographic regions. Understanding prevalent business requisites and challenges in cloud adoption, including scalability, cost efficiency, reliability, availability, and compliance, is essential for organizations seeking to harness cloud technology effectively. Furthermore, this paper provides an overview of AWS's services encompassing computing, storage, databases, machine learning, and AI, showcasing how these empower businesses to streamline operations, foster innovation, and scale dynamically. It elucidates successful instances where AWS was strategically implemented in Netflix, Airbnb, Jollibee Group, and Capital One, demonstrating its impact on scalability, innovation, and service enhancement. The paper outlines anticipated trends in AWS and cloud computing, focusing on user-friendly tools, advancements in machine learning, infrastructure improvements, increased automation, and deeper integration of AI and advanced analytics. Ultimately, this research emphasizes business's need to optimize AWS solutions, navigate complexities, foster innovation, and achieve operational excellence in an increasingly competitive market.

In this article, we proposed an improved family of estimators for population coefficient of variation (CV) under simple random sampling, which needed two helping variables. The expression for bias and mean square error (MSE) are derived up to first order of approximation, and investigated the performance of the proposed family with existing estimators in both actual and simulated conditions, found that new estimators showing lower mean square errors as compare to the existing once, it is concluded that the suggested family of estimators achieved better results.

The significance and importance of corporate social responsibility requires that companies must take into consideration the multi-stakeholder interests ranging from environment, economic and other social impacts of corporate actions. The profiteering of corporations has made business actions questionable which is particularly evident in developing states.This article encompasses issues of corruption and bribery in commercial transactions as a corporate social responsibility aspect and sheds light on shareholders’ derivative right of actions for the implementation of CSR issues. It also looks into mandatory bars on derivative claims and relationship of CSR to derivative claims considering the social responsibilities of shareholders in corporations. This potentially establishes that breach of duties on the part of directors and other corporate wrongs damaging society at large are required to be taken to courts and need to be remedied.

The study is focused to analyze the framing of the islamophobia in the international media in context of the terror attacks on the Muslims and Non-Muslims where the newspapers from six countries including United States, India, United Kingdom, Canada, Australia and Pakistan are focused to study to analyze the major terror incidents from 2014 to 2019 in different countries of the world. The key focus was to analyze the frames including perpetrator of the terror incidents; Islam/Muslims are Progressive or Violent; Criticism on Muslims and Non-Muslims Perpetrators; Target are Muslims or Non-Muslims and Positive or Negative image of Islam/Muslims presented. The content analysis method is used to analyze the content about framing of the major terror incidents targeting both the Muslims and Non-Muslims. The study concludes that the selected international press presented Islam in context of anti-Muslim wave as they presented Islam and Muslims in a negative context mostly linking them with violence and non-Muslims are more target of terrorism than the Muslims. The study presents that the Muslims and Islam is targeted more despite the fact that they have also been target of the terrorism and extremism losing hundreds of lives. Only Pakistani newspaper presented a positive image of Islam and the Muslims convincing about the fact that Muslims are equal target of terrorism and extremism and Muslims also have suffered by terrorism.

The concept of process of recognition of human rights is century old phenomenon, but at the same time children and women have been deprived to be in the category of rights holders. The major problem with their deprivation has been named as “capacity to exercise”, that?s why they have not been put in the category of “capacity to hold” even. Many proponents of philosophy and human rights have argued in favor and against as well, that the children have rights or not, or they have limited rights that can be exercise through paternalism i.e. parents or guardian. This paper discusses one of the theories i.e. will theory of rights, debating over that whether children may have rights independently or not.

Human development index matters a lot for the economic condition of a country. It can be calculated with the help of the education index, health index, and GDP. So, by looking only at the value of the human development index (HDI), the economy of the country can be judged. The contribution of this research project is the identification of factors related to human development. The factors include the availability of the basic necessities, facilities related to education, health, and income. For this purpose, different important factors have been observed for the Multan district by taking MICS (2007-2008) survey data. Logistic regression is applied for the purpose of analysis. Significant factors are noted in each regression analysis based on the dependent factor.