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                <text>The mid and late 2000s witnessed a proliferation of political parties in European party systems. Marxist, Libertarian, Pirate, and Animal parties, as well as radical-right and populist parties, have become part of an increasingly heterogeneous political spectrum generally dominated by the mainstream centre-left and centre-right. The question this article explores is what led to the surge of these parties during the first decade of the 21st century. While it is tempting to look at structural arguments or the recent late-2000s financial crisis to explain this proliferation, the emergence of these parties predates the debt-crisis and can not be described by structural shifts alone . This paper argues that the proliferation of new radical parties came about not only as a result of changes in the political space, but rather due to the very perceived presence and even strengthening of what Katz and Mair (1995) famously dubbed the "cartelization" of mainstream political parties.
&amp;nbsp;
Full text available at: https://doi.org/10.22215/rera.v7i1.210</text>
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                <text>This book scrutinizes how contemporary practices of security have come torely on many different translations of security, risk, and danger.Institutions of national security policies are currently undergoing radicalconceptual and organisational changes, and this book presents a novelapproach for how to study and politically address the new situation.Complex and uncertain threat environments, such as terrorism, climatechange, and the global financial crisis, have paved the way for new forms ofsecurity governance that have profoundly transformed the ways in whichthreats are handled today. Crucially, there is a decentralisation of themanagement of security, which is increasingly handled by a broad set ofsocietal actors that previously were not considered powerful in the conductof security a!airs. This transformation of security knowledge andmanagement changes the meaning of traditional concepts and practices,and calls for investigation into the many meanings of security implied whencontemporary societies manage radical dangers, risks, and threats. It isnecessary to study both what these meanings are and how they developedfrom the security practices of the past. Addressing this knowledge gap, thebook asks how di!erent ideas about threats, risk, and dangers meet in thecurrent practices of security, broadly understood, and with what politicalconsequences.This book will be of interest to students of critical security studies,anthropology, risk studies, science and technology studies andInternational Relations.</text>
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                <text>Czech Journal of International Relations; Vol. 56 No. 4 (2021); 177-184</text>
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                <text>Trine Villumsen Berling, Ulrik Pram Gad, Karen Lund Petersen and Ole Wæver: Translations of Security: A Framework for the Study of Unwanted Futures</text>
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                <text>Indiana International &amp; Comparative Law Review; Vol. 20 No. 2 (2010); 195-212</text>
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                <text>Kanaker, Hasan</text>
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                <text>Cloud computing technology is known as a distributed computing network, which consists of a large number of servers connected via the internet. This technology involves many worthwhile resources, such as applications, services, and large database storage. Users have the ability to access cloud services and resources through web services. Cloud computing provides a considerable number of benefits, such as effective virtualized resources, cost efficiency, self-service access, flexibility, and scalability. However, many security issues are present in cloud computing environment. One of the most common security challenges in the cloud computing environment is the trojan horses. Trojan horses can disrupt cloud computing services and damage the resources, applications, or virtual machines in the cloud structure. Trojan horse attacks are dangerous, complicated and very difficult to be detected. In this research, eight machine learning classifiers for trojan horse detection in a cloud-based environment have been investigated. The accuracy of the cloud trojan horses detection rate has been investigated using dynamic analysis, Cukoo sandbox, and the Weka data mining tool. Based on the conducted experiments, the SMO and Multilayer Perceptron have been found to be the best classifiers for trojan horse detection in a cloud-based environment. Although SMO and Multilayer Perceptron have achieved the highest accuracy rate of 95.86%, Multilayer Perceptron has outperformed SMO in term of Receiver Operating Characteristic (ROC) area.</text>
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                <text>Copyright (c) 2022 Dr. Hasan Kanaker, Dr.Nader Salameh , Dr.Samer A. B. Awwad , Dr. Nurul H.A. Ismail , Dr. Jamal Zraqou , Dr. Abdulla M. F. Al Ali</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 24 (2022); pp. 81-106</text>
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                <text>Trojan Horse Infection Detection  in Cloud Based Environment  Using Machine Learning</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 12 (2022); pp. 94-102</text>
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                <text>1865-7923</text>
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                <text>Since the time it was unveiled in the White House on January 28, 2020, Peace to Prosperity: A Vision to Improve the Lives of the Palestinian and Israeli People or more commonly known as Trump Plan, is a non-starter. As it was being announced, two main protagonists—President Donald Trump and Prime Minister Benjamin Netanyahu—were fighting for their political survival. The US Senate was deliberating the House Resolution to impeach President Trump and moments before the White House event, Israel's Attorney General Avichai Mandelblit formally filed charges of corruption against Netanyahu in a court in Jerusalem. However, both leaders managed to weather the political storm; if the Senate acquitted the US President, the inconclusive March 2, 2020, Knesset elections—the third within a year—injected fresh hopes for the Likud leader. However, even the little hopes people had about the Plan were firmly buried in the pandemic coronavirus and the unfolding worldwide health emergency, mounting human casualties, and the impending global economic collapse.</text>
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                <text>Copyright (c) 2020 Center For Land Warfare Studies (CLAWS), New Delhi, India</text>
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                <text>CLAWS Journal; Vol. 13 No. 1 (2020): Summer 2020; 48-64</text>
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                <text>2319-5177</text>
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                <text>Donald Trump</text>
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                <text>Trump Peace Plan: A Good Diagnosis But Bad Medication</text>
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                  <text>Artha Journal of Social Sciences</text>
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                <text>Thomas, Rosamma</text>
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                <text>This paper is an historical auto-ethnographic account by a middle aged journalist who has worked in the English language media in India for about 20 years. English language media staff is among the best paid in the country. Even so, work conditions are far from ideal, and the pandemic this year has rendered several journalists jobless. This is a personal account of one career trajectory that spans book publishing, work on national radio, newspapers and a news agency. Growth prospects are curtailed for women in the news media; one boss at the Times of India¸ India’s largest English daily, told the author that her “body language” betrayed a lack of interest in work.
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                <text>Artha Journal of Social Sciences; Vol. 19 No. 3 (2020): Artha Journal of Social Sciences; 61-70</text>
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                <text>Indiana University Robert H. McKinney School of Law</text>
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