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On April 14, 2021, the 46th President of the United States of America, Joe Biden, announced the end of the U.S. War in Afghanistan by saying, "It is time to end America's longest war. It is time for American troops to come home,". After the announcement, the Biden government planned to move all the U.S. troops from Afghanistan within September 11, on the anniversary of the attack that prompted the U.S invasion 20 years ago. On August 10, U.S intelligence warned the U.S govt that the Taliban might take over Kabul (Afghanistan government) within 30-90 days. However, the city fell within five days of the warning. On August 15, the Taliban took control of the country. The U.S. government set a deadline for the withdrawal of U.S. troops from Afghanistan within August 31. When the Taliban took over the country and the U.S army and other Western troops were withdrawing from Afghanistan, the security and freedom of women and children was one of the biggest concerns. Different media published those concerning stories differently. In this paper, the author compares the published reports by two significant media of the 21st century, the Middle East-based Al Jazeera and the western country-based BBC. Globalization theory has been used to validate the article. Metaphorical analysis of contents has been analyzed to carry out the prospective outcome of this article.

The classical algorithm which is dedicated to resolve job sequencing problem with a deadline (JSD) needs exponential time O(\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ n^{2} $$\end{document}n2), where sorting algorithm [O(\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ nlog\left( n \right) $$\end{document}nlogn)-(Merge Sort)] must have to use to sort all the jobs in decreasing order of their profit and it is a greedy technique. To reduce the complexity of this classical algorithm, we nullify the sorting algorithm using dynamic programming approach in the proposed algorithm. The time complexity after using this approach reduces to O(\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ mn $$\end{document}mn), where no sorting algorithm [O(\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ nlog\left( n \right) $$\end{document}nlogn)-(Merge Sort)] needed, which has been shown by proper explanation. Here, we were also given a novel approach to resolve the job sequencing problem using Dynamic Programming and it is a unique approach that always finds an optimal solution. By using this approach, a proper algorithm has been developed in this paper. Besides, finding maximum profit and the sequence of the job to obtain maximum profit, this algorithm gives the sequence of jobs for a specific profit or near a specific profit.

Sequencing of cell-free DNA (cfDNA) in cancer patients’ plasma offers a minimally-invasive solution to detect tumor cell genomic alterations to aid real-time clinical decision-making. The reliability of copy number detection decreases at lower cfDNA tumor fractions, limiting utility at earlier stages of the disease. To test a novel strategy for detection of allelic imbalance, we developed a prostate cancer bespoke assay, PCF_SELECT, that includes an innovative sequencing panel covering ∼25 000 high minor allele frequency SNPs and tailored analytical solutions to enable allele-informed evaluation. First, we assessed it on plasma samples from 50 advanced prostate cancer patients. We then confirmed improved detection of genomic alterations in samples with

Blockchain (BC) and Software Defined Networking (SDN) are some of the most prominent emerging technologies in recent research. These technologies provide security, integrity, as well as confidentiality in their respective applications. Cloud computing has also been a popular comprehensive technology for several years. Confidential information is often shared with the cloud infrastructure to give customers access to remote resources, such as computation and storage operations. However, cloud computing also presents substantial security threats, issues, and challenges. Therefore, to overcome these difficulties, we propose integrating Blockchain and SDN in the cloud computing platform. In this research, we introduce the architecture to better secure clouds. Moreover, we leverage a distributed Blockchain approach to convey security, confidentiality, privacy, integrity, adaptability, and scalability in the proposed architecture. BC provides a distributed or decentralized and efficient environment for users. Also, we present an SDN approach to improving the reliability, stability, and load balancing capabilities of the cloud infrastructure. Finally, we provide an experimental evaluation of the performance of our SDN and BC-based implementation using different parameters, also monitoring some attacks in the system and proving its efficacy., Comment: 12 Pages 16 Figures 3 Tables

Sentiment Analysis is a technique related to text analysis and natural language processing used to detect various types of insights or information from a portion of text. Over the past few years, researchers have done many works regarding this. In Bangladesh, many online services like-e-com become very popular day by day. One of them is online food delivery services. We can order various foods of our choice from online and sometimes people gives reviews based on that food. Those reviews are usually discarded as unstructured data which of them have no work in further. In this piece of research focus primarily on those unstructured data to analyze them in a correct manner to find insight into customers' behavior and their reactions on those online platforms. To do this experiment first we collect data from websites. Later deep learning-based techniques applied here. For baseline structure, we have used both CNN and LSTM models. Then for improving the model accuracy an attention mechanism applied followed by CNN which gives us 98.45% accuracy. We've also evaluated our model performances with some evaluation metrics also. From them, CNN based attention model gives a higher f1-score of 0.93.

Software-Defined Networking (SDN) and Blockchain are leading technologies used worldwide to establish safe network communication as well as build secure network infrastructures. They provide a robust and reliable platform to address threats and face challenges such as security, privacy, flexibility, scalability, and confidentiality. Driven by these assumptions, this paper presents an optimized energy-efficient and secure Blockchain-based software-defined IoT framework for smart networks. Indeed, SDN and Blockchain technologies have proven to be able to suitably manage resource utilization and to develop secure network communication across the IoT ecosystem. However, there is a lack of research works that present a comprehensive definition of such a framework that can meet the requirements of the IoT ecosystem (i.e. efficient energy utilization and reduced end-to-end delay). Therefore, in this research, we present a layered hierarchical architecture for the deployment of a distributed yet efficient Blockchain-enabled SDN-IoT framework that ensures efficient cluster-head selection and secure network communication via the identification and isolation of rouge switches. Besides, the Blockchain-enabled flow-rules record keeps track of the rules enforced in the switches and maintains the consistency within the controller cluster. Finally, we assess the performance of the proposed framework in a simulation environment and show that it can achieve optimized energy-utilization, end-to-end delay, and throughput compared to considered baselines, thus being able to achieve efficiency and security in the smart network.