Enhancing an image’s compression while keeping quality standards utilizing new mathematical technology

The rapid development of technology led to the need to keep pace with it, especially in the field of image processing, because of its importance in the need to get better results. In this paper, new discrete Chebyshev wavelet transforms (DChWT) derived from Chebyshev polynomials (ChP) were proposed and characterized. In terms of orthogonality and approximation (convergence) in the field of mathematics, (ChP) were qualified to transform into discrete wavelets called (DChWT), depending on the mother function with operators (s, r), and were used in image processing to analyze them in the low filter and the high filter so that the image is analyzed into coefficients. Proximity and detail coefficients, which lead to dividing the image into four parts, low left (LL), in which the proximity coefficients are concentrated while the rest of the parts are centered on the detail coefficients, which are high left (HL), low right (LR), and high right (HR), and image compression through the new filter, which has proven its efficiency at level (8) in our results. The results of the proposed wavelets in this work were reached in calculating quality standards in the image obtained after the compression process after comparing them with the results obtained using the standard wavelet used in HaarSymlet 2, Conflict 2, and Daubecheis 2. The most important of these standards is a mean square error (MSE), peak signal-to-noise ratio (PSNR), bit per pixel (BPP), compression ratio (CR), and table one. In this paper, the efficiency of the proposed new wavelets is explained after adding it to MATLAB and according to a specific program to drop in with the basic wavelets to take on their role in important tasks in the image processing area, like artificial intelligenc

Um estudo comparativo das abordagens de detecção e reconhecimento de texto para cenários de computação restrita

Orientadores: Ricardo da Silva Torres, Allan da Silva PintoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Textos são elementos fundamentais para uma efetiva comunicação em nosso cotidiano. A mobilidade de pessoas e veículos em ambientes urbanos e a busca por um produto de interesse em uma prateleira de supermercado são exemplos de atividades em que o entendimento dos elementos textuais presentes no ambiente são essenciais para a execução da tarefa. Recentemente, diversos avanços na área de visão computacional têm sido reportados na literatura, com o desenvolvimento de algoritmos e métodos que objetivam reconhecer objetos e textos em cenas. Entretanto, a detecção e reconhecimento de textos são problemas considerados em aberto devido a diversos fatores que atuam como fontes de variabilidades durante a geração e captura de textos em cenas, o que podem impactar as taxas de detecção e reconhecimento de maneira significativa. Exemplo destes fatores incluem diferentes formas dos elementos textuais (e.g., circular ou em linha curva), estilos e tamanhos da fonte, textura, cor, variação de brilho e contraste, entre outros. Além disso, os recentes métodos considerados estado-da-arte, baseados em aprendizagem profunda, demandam altos custos de processamento computacional, o que dificulta a utilização de tais métodos em cenários de computação restritiva. Esta dissertação apresenta um estudo comparativo de técnicas de detecção e reconhecimento de texto, considerando tanto os métodos baseados em aprendizado profundo quanto os métodos que utilizam algoritmos clássicos de aprendizado de máquina. Esta dissertação também apresenta um método de fusão de caixas delimitadoras, baseado em programação genética (GP), desenvolvido para atuar tanto como uma etapa de pós-processamento, posterior a etapa de detecção, quanto para explorar a complementariedade dos algoritmos de detecção de texto investigados nesta dissertação. De acordo com o estudo comparativo apresentado neste trabalho, os métodos baseados em aprendizagem profunda são mais eficazes e menos eficientes, em comparação com os métodos clássicos da literatura e considerando as métricas adotadas. Além disso, o algoritmo de fusão proposto foi capaz de aprender informações complementares entre os métodos investigados nesta dissertação, o que resultou em uma melhora das taxas de precisão e revocação. Os experimentos foram conduzidos considerando os problemas de detecção de textos horizontais, verticais e de orientação arbitráriaAbstract: Texts are fundamental elements for effective communication in our daily lives. The mobility of people and vehicles in urban environments and the search for a product of interest on a supermarket shelf are examples of activities in which the understanding of the textual elements present in the environment is essential to succeed in such tasks. Recently, several advances in computer vision have been reported in the literature, with the development of algorithms and methods that aim to recognize objects and texts in scenes. However, text detection and recognition are still open problems due to several factors that act as sources of variability during scene text generation and capture, which can significantly impact detection and recognition rates of current algorithms. Examples of these factors include different shapes of textual elements (e.g., circular or curved), font styles and sizes, texture, color, brightness and contrast variation, among others. Besides, recent state-of-the-art methods based on deep learning demand high computational processing costs, which difficult their use in restricted computing scenarios. This dissertation presents a comparative study of text detection and recognition techniques, considering methods based on deep learning and methods that use classical machine learning algorithms. This dissertation also presents an algorithm for fusing bounding boxes, based on genetic programming (GP), developed to act as a post-processing step for a single text detector and to explore the complementarity of text detection algorithms investigated in this dissertation. According to the comparative study presented in this work, the methods based on deep learning are more effective and less efficient, in comparison to classic methods for text detection investigated in this work, considering the adopted metrics. Furthermore, the proposed GP-based fusion algorithm was able to learn complementary information from the methods investigated in this dissertation, which resulted in an improvement of precision and recall rates. The experiments were conducted considering text detection problems involving horizontal, vertical and arbitrary orientationsMestradoCiência da ComputaçãoMestre em Ciência da ComputaçãoCAPE

Cybernationalism and cyberactivism in China

El nacionalismo en la era de Internet se está convirtiendo cada vez más en un factor esencial que influye en la agenda-setting de la sociedad china, así como en las relaciones de China con los países extranjeros, especialmente con Occidente. Para China, una mejor comprensión de la estructura teórica universal y de los patrones de comportamiento del nacionalismo facilitaría la articulación social general de esta tendencia y potenciaría su papel positivo en la agenda-setting social. Por otra parte, un estudio del cibernacionalismo chino basado en una perspectiva china en el mundo académico occidental es un intento de transculturación. Desde el punto de vista de las relaciones internacionales y la geopolítica actuales, que son bastante urgentes, este intento ayudaría a mejorar la compatibilidad de China con el actual orden mundial dominado por Occidente, a reducir la desinformación entre China y otros países y a sentar las bases culturales e ideológicas para otras colaboraciones internacionales. Teniendo en cuenta el estado actual de la investigación sobre el nacionalismo chino y la naturaleza participativa de las masas del cibernacionalismo, esta disertación se centra en el cibernacionalismo en las tres partes siguientes. El primero es un estudio de los orígenes históricos del cibernacionalismo chino. Esta sección incluye tanto una exploración del consenso social en la antigua China como un estudio de la influencia del nacionalismo en la historia china moderna. El estudio de los orígenes históricos no sólo nos muestra la secuencia cronológica de la experiencia del desarrollo y la evolución tanto del proto-nacionalismo como del nacionalismo en China, sino que también revela un impulso decisivo para las reivindicaciones y comportamientos actuales del cibernacionalismo. La segunda parte trata del proceso de formación y ascenso del cibernacionalismo desde el siglo XXI. El importante antecedente del paso del nacionalismo al cibernacionalismo es el proceso de informatización de la sociedad china. Una vez completado el estudio de la situación básica de la sociedad china de Internet, especialmente el estudio de los medios sociales como espacio público, podemos vincular Internet con el nacionalismo y examinar el nuevo desarrollo del nacionalismo en la era de la participación de masas. El objetivo final es conectar el proto-nacionalismo, el nacionalismo y el cibernacionalismo, y seguir construyendo una comprensión del cibernacionalismo que sea coherente tanto con los principios universales del nacionalismo como con el contexto chino. Por último, validamos los resultados derivados del estudio anterior a través de la realidad social, es decir, estudiando las prácticas de ciberactivismo del cibernacionalismo para juzgar su suficiencia general así como su validez. Llevaremos a cabo varios estudios de caso de natural language processing basados en big data para reproducir la lógica de comportamiento y el impacto real del ciberactivismo de la manera más cercana posible a la realidad de Internet, evitando al mismo tiempo los defectos de argumentación unilateral y de infrarrepresentación de los estudios de caso tradicionales.Nationalism in the Internet age is increasingly becoming an essential factor influencing agendasetting within Chinese society, as well as China’s relations with foreign countries, especially the West. For China, a better understanding of the universal theoretical structure and behavioral patterns of nationalism would facilitate the overall social articulation of this trend and enhance its positive role in social agenda setting. On the other hand, a study of Chinese cybernationalism based on a Chinese perspective in western academia is an attempt at transculturation. From the viewpoint of the current rather urgent international relations and geopolitics, such an attempt would help to enhance China’s compatibility with the current western-dominated world order, reduce misinformation between China and other countries, and lay the cultural and ideological groundwork for various other international collaborations. Considering the current state of Chinese nationalism research and the mass participatory nature of cybernationalism, this dissertation focuses on cybernationalism in the following three parts. The first is a study of the historical origins of Chinese cybernationalism. This section includes both an exploration of the social consensus in ancient China and a survey of the influence of nationalism in modern Chinese history. The historical origins study not only shows us the chronological sequence of experiencing the development and evolution of both proto-nationalism and nationalism in China, but also reveals a decisive impetus for the current claims and behaviors of cybernationalism. The second part deals with the process of formation and rise of cybernationalism since the 21st century. The important background for the move from nationalism to cybernationalism is the informatization process of Chinese society. After we have completed the study of the basic situation of Chinese Internet society, especially the study of social media as a public space, we can link the Internet with nationalism and examine the new development of nationalism in the era of mass participation. The ultimate goal is to connect the proto-nationalism, nationalism, cybernationalism, and furtherly construct an understanding of cybernationalism that is consistent with both the universal principles of nationalism and the Chinese context. Finally, we validate the results derived from the previous study through social reality, i.e., by studying the cyberactivism practices of cybernationalism to judge its general sufficiency as well as validity. We will conduct several natural language processing case studies based on big data to reproduce the behavioral logic and actual impact of cyberactivism in the closest possible way to the Internet reality while avoiding the unilateral argumentation and under-representation flaws of traditional case studies

Counter-Terrorism, Ethics and Technology

This open access book brings together a range of contributions that seek to explore the ethical issues arising from the overlap between counter-terrorism, ethics, and technologies. Terrorism and our responses pose some of the most significant ethical challenges to states and people. At the same time, we are becoming increasingly aware of the ethical implications of new and emerging technologies. Whether it is the use of remote weapons like drones as part of counter-terrorism strategies, the application of surveillance technologies to monitor and respond to terrorist activities, or counterintelligence agencies use of machine learning to detect suspicious behavior and hacking computers to gain access to encrypted data, technologies play a significant role in modern counter-terrorism. However, each of these technologies carries with them a range of ethical issues and challenges. How we use these technologies and the policies that govern them have broader impact beyond just the identification and response to terrorist activities. As we are seeing with China, the need to respond to domestic terrorism is one of the justifications for their rollout of the “social credit system.” Counter-terrorism technologies can easily succumb to mission creep, where a technology’s exceptional application becomes normalized and rolled out to society more generally. This collection is not just timely but an important contribution to understand the ethics of counter-terrorism and technology and has far wider implications for societies and nations around the world

State of the art 2015: a literature review of social media intelligence capabilities for counter-terrorism

Overview This paper is a review of how information and insight can be drawn from open social media sources. It focuses on the specific research techniques that have emerged, the capabilities they provide, the possible insights they offer, and the ethical and legal questions they raise. These techniques are considered relevant and valuable in so far as they can help to maintain public safety by preventing terrorism, preparing for it, protecting the public from it and pursuing its perpetrators. The report also considers how far this can be achieved against the backdrop of radically changing technology and public attitudes towards surveillance. This is an updated version of a 2013 report paper on the same subject, State of the Art. Since 2013, there have been significant changes in social media, how it is used by terrorist groups, and the methods being developed to make sense of it.  The paper is structured as follows: Part 1 is an overview of social media use, focused on how it is used by groups of interest to those involved in counter-terrorism. This includes new sections on trends of social media platforms; and a new section on Islamic State (IS). Part 2 provides an introduction to the key approaches of social media intelligence (henceforth ‘SOCMINT’) for counter-terrorism. Part 3 sets out a series of SOCMINT techniques. For each technique a series of capabilities and insights are considered, the validity and reliability of the method is considered, and how they might be applied to counter-terrorism work explored. Part 4 outlines a number of important legal, ethical and practical considerations when undertaking SOCMINT work