Search results for: text recognition

Authors: Komal V. Aher, Sanjay B. Waykar

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Nowadays every individual having mobile device with them. In both computer vision and information retrieval Image search is currently hot topic with many applications. The proposed intelligent image search system is fully utilizing multimodal and multi-touch functionalities of smart phones which allows search with Image, Voice, and Text on mobile phones. The system will be more useful for users who already have pictures in their minds but have no proper descriptions or names to address them. The paper gives system with ability to form composite visual query to express user’s intention more clearly which helps to give more precise or appropriate results to user. The proposed algorithm will considerably get better in different aspects. System also uses Context based Image retrieval scheme to give significant outcomes. So system is able to achieve gain in terms of search performance, accuracy and user satisfaction.

Keywords: color space, histogram, mobile device, mobile visual search, multimodal search

Procedia PDF Downloads 357

Authors: Lee Soo-Kyoung, Kim Young-Su

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This study established a network related to metabolic syndrome intervention by conducting a social network analysis of titles, keywords, and abstracts, and it identified emerging topics of research. It visualized an interconnection between critical keywords and investigated their frequency of appearance to construe the trends in metabolic syndrome intervention measures used in studies conducted over 38 years (1979–2017). It examined a collection of keywords from 8,285 studies using text rank analyzer, NetMiner 4.0. The analysis revealed 5 groups of newly emerging keywords in the research. By examining the relationship between keywords with reference to their betweenness centrality, the following clusters were identified. Thus if new researchers refer to existing trends to establish the subject of their study and the direction of the development of future research on metabolic syndrome intervention can be predicted.

Keywords: intervention, metabolic syndrome, network analysis, research, the trend

Procedia PDF Downloads 193

Authors: Zheng Baichuan, Li Shenghui, Li Bingqian, Zhang Ning, Chen Kai

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Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons.

Keywords: knowledge graph, entity alignment, transformer, deep learning

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Authors: Juha Kettunen

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This study analyzes the quality and the size of the strategic network of higher education institutions. The study analyses the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented of the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: balanced scorecard, higher education, social networking, strategic planning

Procedia PDF Downloads 329

Authors: Quentin Lobbe, David Chavalarias, Alexandre Delanoe

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The ICT revolution has given birth to an unprecedented world of digital traces and has impacted a wide number of knowledge-driven domains such as science, education or policy making. Nowadays, we are daily fueled by unlimited flows of articles, blogs, messages, tweets, etc. The internet itself can thus be considered as an unsteady hyper-textual environment where websites emerge and expand every day. But there are structures inside knowledge. A given text can always be studied in relation to others or in light of a specific socio-cultural context. By way of their textual traces, human beings are calling each other out: hypertext citations, retweets, vocabulary similarity, etc. We are in fact the architects of a giant web of elements of knowledge whose structures and shapes convey their own information. The global shapes of these digital traces represent a source of collective knowledge and the question of their visualization remains an opened challenge. How can we explore, browse and interact with such shapes? In order to navigate across these growing constellations of words and texts, interdisciplinary innovations are emerging at the crossroad between fields of social and computational sciences. In particular, complex systems approaches make it now possible to reconstruct the hidden structures of textual knowledge by means of multi-scale objects of research such as semantic maps and phylomemies. The phylomemy reconstruction is a generic method related to the co-word analysis framework. Phylomemies aim to reveal the temporal dynamics of large corpora of textual contents by performing inter-temporal matching on extracted knowledge domains in order to identify their conceptual lineages. This study aims to address the question of visualizing the global shapes of online political discussions related to the French presidential and legislative elections of 2017. We aim to build phylomemies on top of a dedicated collection of thousands of French political tweets enriched with archived contemporary news web articles. Our goal is to reconstruct the temporal evolution of online debates fueled by each political community during the elections. To that end, we want to introduce an iterative data exploration methodology implemented and tested within the free software Gargantext. There we combine synchronic and diachronic axis of visualization to reveal the dynamics of our corpora of tweets and web pages as well as their inner syntagmatic and paradigmatic relationships. In doing so, we aim to provide researchers with innovative methodological means to explore online semantic landscapes in a collaborative and reflective way.

Keywords: online political debate, French election, hyper-text, phylomemy

Procedia PDF Downloads 178

Authors: Preeti Yadav, Dandeswar Bisoyi, Debkumar Chakrabarti

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Mascots provide memories to viewers, and numerous promotional campaigns with different appearances, continue to trigger viewers and capture their interest. This study investigates the effect of Indian food mascot designs and influence on enhancing communication; thereby, building long-term brand recognition by the consumers. This paper presents a descriptive approach to Indian food mascot design as an advertising tool, and its research adopts a quantitative methodology. The study confirms that mascots have an ability to communicate a message in an effective manner; all though they are simple in terms of design and fashion trend, they have the capability to build positive reactions.

Keywords: food mascot, brand recognitions, advertising, humour

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Authors: Claudia Rodriguez-Espinosa, Erika Elizabeth Pérez Múzquiz

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Since the creation of the “Pueblos Mágicos” program in 2001, a series of social and cultural events had directly affected the heritage conservation of the 121 registered localities until 2018, when the federal government terminated the program. Many studies have been carried out that seek to analyze from different perspectives and disciplines the consequences that these appointments have generated in the “Pueblos Mágicos.” Multidisciplinary groups such as the one headed by Carmen Valverde and Liliana López Levi, have brought together specialists from all over the Mexican Republic to create a set of diagnoses of most of these settlements, and although each one has unique specificities, there is a constant in most of them that has to do with the loss of cultural heritage and that is related to transculturality. There are several factors identified that have fostered a cultural loss, as a direct reflection of the economic crisis that prevails in Mexico. It is important to remember that the origin of this program had as its main objective to promote the growth and development of local economies since one of the conditions for entering the program is that they have less than 20,000 inhabitants. With this goal in mind, one of the first actions that many “Pueblos Mágicos” carried out was to improve or create an infrastructure to receive both national and foreign tourists since this was practically non-existent. Creating hotels, restaurants, cafes, training certified tour guides, among other actions, have led to one of the great problems they face: globalization. Although by itself it is not bad, its impact in many cases has been negative for heritage conservation. The entry into and contact with new cultures has led to the undervaluation of cultural traditions, their transformation and even their total loss. This work seeks to present specific cases of transformation and loss of cultural heritage, as well as to reflect on the problem and propose scenarios in which the negative effects can be reversed. For this text, 36 “Pueblos Mágicos” have been selected for study, based on those settlements that are cited in volumes I and IV (the first and last of the collection) of the series produced by the multidisciplinary group led by Carmen Valverde and Liliana López Levi (researchers from UNAM and UAM Xochimilco respectively) in the project supported by CONACyT entitled “Pueblos Mágicos. An interdisciplinary vision”, of which we are part. This sample is considered representative since it forms 30% of the total of 121 “Pueblos Mágicos” existing at that moment. With this information, the elements of its intangible heritage loss or transformation have been identified in every chapter based on the texts written by the participants of that project. Finally, this text shows an analysis of the effects that this federal program, as a public policy applied to 132 populations, has had on the conservation or transformation of the intangible cultural heritage of the “Pueblos Mágicos.” Transculturality, globalization, the creation of identities and the desire to increase the flow of tourists have impacted the changes that traditions (main intangible cultural heritage) have had in the 18 years that the federal program lasted.

Keywords: public policies, cultural tourism, heritage preservation, pueblos mágicos program

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Authors: Mark McKeown

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Press articles opining on how China has become the West’s biggest threat have become so common as to feel like old news. Since the United States shifted diplomatic recognition from Taiwan to the People’s Republic of China in 1979 the relationship between the world’s two largest economies has been at best a brittle one. This coiled tension has grown as trade between the two countries snaked ever upwards. As a byproduct of globalization Apple have focused much of their production and assembly in China. This has left the U.S. Big Tech company with several challenges. This paper focusses on the tightrope Apple now has to traverse. The majority of the data and analysis within this paper is sourced from my current ongoing PhD research on the influence of Big Tech lobbying on U.S. foreign policy. One of the main conclusions from this analysis is Apple has to adopt a carefully nuanced strategy of appeasement to avoid friction, with both the governments of China and the United States.

Keywords: apple, China, Taiwan, war

Procedia PDF Downloads 51

Authors: Sergey A. Burikov, Tatiana A. Dolenko, Kirill A. Gushchin, Sergey A. Dolenko

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The paper presents the results of clusterization by Kohonen self-organizing maps (SOM) applied for analysis of array of Raman spectra of multi-component solutions of inorganic salts, for determination of types of salts present in the solution. It is demonstrated that use of SOM is a promising method for solution of clusterization and classification problems in spectroscopy of multi-component objects, as attributing a pattern to some cluster may be used for recognition of component composition of the object.

Keywords: Kohonen self-organizing maps, clusterization, multi-component solutions, Raman spectroscopy

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Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

Procedia PDF Downloads 120

Authors: Aliya Ashraf, Mehreen Sirshar, Fatima Akhtar, Farwa Kazmi, Jawaria Wazir

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Vision, the basis for performing navigational tasks, is absent or greatly reduced in visually impaired people due to which they face many hurdles. For increasing the navigational capabilities of visually impaired people a desktop application ODAPTA is presented in this paper. The application uses camera to capture video from surroundings, apply various image processing algorithms to get information about path and obstacles, tracks them and delivers that information to user through voice commands. Experimental results show that the application works effectively for straight paths in daylight.

Keywords: visually impaired, ODAPTA, Region of Interest (ROI), driver fatigue, face detection, expression recognition, CCD camera, artificial intelligence

Procedia PDF Downloads 534

Authors: Basit Shahzad, Abdullatif M. Abdullatif

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Recent advancements in Information and Communication Technologies (ICT) and easy access to Internet have made social media the first choice for information sharing related to any important events or news. On Twitter, trend is a common feature that quantifies the level of popularity of a certain news or event. In this work, we examine the impact of Twitter trends on real world events by hypothesizing that Twitter trends have an influence on print media in Pakistan. For this, Twitter is used as a platform and Twitter trends as a base line. We first collect data from two sources (Twitter trends and print media) in the period May to August 2016. Obtained data from two sources is analyzed and it is observed that social media is significantly influencing the print media and majority of the news printed in newspaper are posted on Twitter earlier.

Keywords: twitter trends, text mining, effectiveness of trends, print media

Procedia PDF Downloads 249

Authors: Heejin Yun, Juanjuan Zang

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This study aims to analyze the text terms posted on an online community of people from the same hometown and to understand the topic and trend of nostalgia composed online. For this purpose, this study collected 144 writings which the natives of Yeongjong Island, Incheon, South-Korea have posted on an online community. And it analyzed association relations. As a result, online community texts means that just defining nostalgia as ‘a mind longing for hometown’ is not an enough explanation. Second, texts composed online have abstractness rather than persons’ individual stories. This study figured out the relationship that had the most critical and closest mutual association among the terms that constituted nostalgia through literature research and association rule concerning nostalgia. The result of this study has a characteristic that it summed up the core terms and emotions related to nostalgia.

Keywords: nostalgia, cultural memory, data mining, association rule

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Authors: Adnan H. M. Al-Helali, Hamza A. Ali

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Growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC) and Image Fidelity (IF) over the previous techniques.

Keywords: fractal image, information hiding, Mandelbrot et fractal, steganography

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Authors: H. Nagendra, Vinod Kumar, S. Mukherjee

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In this study, the potential benefits of playing action video game among congenitally deaf and dumb subjects is reported in terms of EEG ratio indices. The frontal and occipital lobes are associated with development of motor skills, cognition, and visual information processing and color recognition. The sixteen hours of First-Person shooter action video game play resulted in the increase of the ratios β/(α+θ) and β/θ in frontal and occipital lobes. This can be attributed to the enhancement of certain aspect of cognition among deaf and dumb subjects.

Keywords: cognitive enhancement, video games, EEG band powers, deaf and dumb subjects

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Spencer Jay Knafelc

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Some mental health practitioners and theorists have suggested that we approach remedying psychological problems by centering and intervening upon patients’ narrations. Such theorists and their corresponding therapeutic approaches see persons as narrators of their lives, where the stories they tell constitute and reflect their sense-making of the world. Psychological problems, according to these approaches to therapy, are often the result of problematic narratives. The solution is the construction of more salubrious narratives through therapy. There is trouble lurking within the history of these narrative approaches. These thinkers tend to denigrate the importance of truth, insisting that narratives are not to be thought of as aiming at truth, and thus the truth of our self-narratives is not important. There are multiple motivations for the tendency to eschew truth’s importance within the tradition of narrative approaches to therapy. The most plausible and interesting motivation comes from the observation that, in general, all dominant approaches to therapy are equally effective. The theoretical commitments of each approach are quite different and are often ostensibly incompatible (psychodynamic therapists see psychological problems as resulting from unconscious conflict and repressed desires, Cognitive-Behavioral approaches see them as resulting from distorted cognitions). This strongly suggests that there must be some cases in which therapeutic efficacy does not depend on truth and that insisting that patient’s therapeutic narratives be true in all instances is a mistake. Lewis’ solution is to suggest that narratives are metaphors. Lewis’ account appreciates that there are many ways to tell a story and that many different approaches to mental health treatment can be appropriate without committing us to any contradictions, providing us with an ostensibly coherent way to treat narratives as non-literal, instead of seeing them as tools that can be more or less apt. Here, it is argued that Lewis’ metaphor approach fails. Narratives do not have the right kind of structure to be metaphors. Still, another way to understand Lewis’ view might be that self-narratives, especially when articulated in the language of any specific approach, should not be taken literally. This is an idea at the core of the narrative theorists’ tendency to eschew the importance of the ordinary understanding of truth. This very tendency will be critiqued. The view defended in this paper more accurately captures the nature of self-narratives. The truth of one’s self-narrative is important. Not only do people care about having the right conception of their abilities, who they are, and the way the world is, but self-narratives are composed of beliefs, and the nature of belief is to aim at truth. This view also allows the recognition of the importance of developing accurate representations of oneself and reality for one’s psychological well-being. It is also argued that in many cases, truth factors in as a mechanism of change over the course of therapy. Therapeutic benefit can be achieved by coming to have a better understanding of the nature of oneself and the world. Finally, the view defended here allows for the recognition of the nature of the tension between values: truth and efficacy. It is better to recognize this tension and develop strategies to navigate it as opposed to insisting that it doesn’t exist.

Keywords: philosophy, narrative, psychotherapy, truth

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

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Authors: Damanjit Kaur, Avani Bhatia

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Color constancy is significant for human vision since color is a pictorial cue that helps in solving different visions tasks such as tracking, object recognition, or categorization. Therefore, several computational methods have tried to simulate human color constancy abilities to stabilize machine color representations. Two different kinds of methods have been used, i.e., normalization and constancy. While color normalization creates a new representation of the image by canceling illuminant effects, color constancy directly estimates the color of the illuminant in order to map the image colors to a canonical version. Color constancy is the capability to determine colors of objects independent of the color of the light source. This research work studies the most of the well-known color constancy algorithms like white point and gray world.

Keywords: color constancy, gray world, white patch, modified white patch

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Authors: Igor A. Podgorny

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TurboTax AnswerXchange is a social Q/A system supporting users working on federal and state tax returns. Content quality and popularity in the AnswerXchange can be predicted with propensity models using attributes of the question and answer. Using uplift modeling, we identify features of questions and answers that can be modified during the question-asking and question-answering experience in order to optimize the AnswerXchange content quality. We demonstrate that adding details to the questions always results in increased question popularity that can be used to promote good quality content. Responding to close-ended questions assertively improve content quality in the AnswerXchange in 90% of cases. Answering knowledge questions with web links increases the likelihood of receiving a negative vote from 60% of the askers. Our findings provide a rationale for employing the uplift modeling approach for AnswerXchange operations.

Keywords: customer relationship management, human-machine interaction, text mining, uplift modeling

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Authors: Johan Anker

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The purpose of this paper is to discuss the nature of gender construction in modern dystopian fiction, the development of this genre in Young Adult Literature and reasons for the enormous appeal on the adolescent readers. A recent award winning South African text in this genre, The Mark by Edith Bullring (2014), will be used as example while also comparing this text to international bestsellers like Divergent (Roth:2011), The Hunger Games (Collins:2008) and others. Theoretical insights from critics and academics in the field of children’s literature, like Ames, Coats, Bradford, Booker, Basu, Green-Barteet, Hintz, McAlear, McCallum, Moylan, Ostry, Ryan, Stephens and Westerfield will be referred to and their insights used as part of the analysis of The Mark. The role of relevant and recurring themes in this genre, like global concerns, environmental destruction, liberty, self-determination, social and political critique, surveillance and repression by the state or other institutions will also be referred to. The paper will shortly refer to the history and emergence of dystopian literature as genre in adult and young adult literature as part of the long tradition since the publishing of Orwell’s 1984 and Huxley’s Brave New World. Different factors appeal to adolescent readers in the modern versions of this hybrid genre for young adults: teenage protagonists who are questioning the underlying values of a flawed society like an inhuman or tyrannical government, a growing understanding of the society around them, feelings of isolation and the dynamic of relationships. This unease leads to a growing sense of the potential to act against society (rebellion), and of their role as agents in a larger community and independent decision-making abilities. This awareness also leads to a growing sense of self (identity and agency) and the development of romantic relationships. The specific modern tendency of a female protagonist as leader in the rebellion against state and state apparatus, who gains in agency and independence in this rebellion, an important part of the identification with and construction of gender, while being part of the traditional coming-of-age young adult novel will be emphasized. A comparison between the traditional themes, structures and plots of young adult literature (YAL) with adult dystopian literature and those of recent dystopian YAL will be made while the hybrid nature of this genre and the 'sense of unease' but also of hope, as an essential part of youth literature, in the closure to these novels will be discussed. Important questions about the role of the didactic nature of these texts and the political issues and the importance of the formation of agency and identity for the young adult reader, as well as identification with the protagonists in this genre, are also part of this discussion of The Mark and other YAL novels.

Keywords: agency, dystopian literature, gender construction, young adult literature

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Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

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This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

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Authors: Adnan H. M. Al-Helali, Hamza A. Ali

Abstract:

The growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC), and Image Fidelity (IF) over the pervious techniques.

Keywords: fractal image, information hiding, Mandelbrot set fractal, steganography

Procedia PDF Downloads 608

Authors: Baldev Setia, Raj Rajeshwari, Maneesh Kumar

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Present paper is an analysis of water transmission mains failed due to surge analysis by using basic software known as Surge Analysis Program (SAP). It is a real time failure case study of a pipe laid in Una, Himachal Pradesh. The transmission main is a 13 kilometer long pipe with 7.9 kilometers as pumping main and 5.1 kilometers as gravitational main. The analysis deals with mainly pumping mains. The results are available in two text files. Besides, several files are prepared with specific view to obtain results in a graphical form. These results help to observe the pressure difference and surge occurrence at different locations along the pipe profile, which help to redesign the transmission main with different but suitable safety measures against possible surge. A technically viable and economically feasible design has been provided as per the relevant manual and standard code of practice.

Keywords: surge, water hammer, transmission mains, SAP 2000

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Authors: Carlos Tarmeño Noriega, Igor Aguilar Alonso

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Fungal diseases are common in vineyards; they cause a decrease in the quality of the products that can be sold, generating distrust of the customer towards the seller when buying fruit. Currently, technology allows the classification of fruits according to their characteristics thanks to artificial intelligence. This study proposes the implementation of a control system that allows the identification of the main fungal diseases present in the Italia grape, making use of a convolutional neural network (CNN), OpenCV, and TensorFlow. The methodology used was based on a collection of 20 articles referring to the proposed research on quality control, classification, and recognition of fruits through artificial vision techniques.

Keywords: computer vision, convolutional neural networks, quality control, fruit market, OpenCV, TensorFlow

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Authors: Tobias Milz, L. Macpherson, Varvara Vetrova

Abstract:

The law is a fundamental pillar of human societies as it shapes, controls and governs how humans conduct business, behave and interact with each other. Recent advances in computer-assisted technologies such as NLP, data science and AI are creating opportunities to support the practice, research and study of this pervasive domain. It is therefore not surprising that there has been an increase in investments into supporting technologies for the legal industry (also known as “legal tech” or “law tech”) over the last decade. A sub-discipline of particular appeal is concerned with assisted legal research. Supporting law researchers and practitioners to retrieve information from the vast amount of ever-growing legal documentation is of natural interest to the legal research community. One tool that has been in use for this purpose since the early nineteenth century is legal citation indexing. Among other use cases, they provided an effective means to discover new precedent cases. Nowadays, computer-assisted network analysis tools can allow for new and more efficient ways to reveal the “hidden” information that is conveyed through citation behavior. Unfortunately, access to openly available legal data is still lacking in New Zealand and access to such networks is only commercially available via providers such as LexisNexis. Consequently, there is a need to create, analyze and provide a legal citation network with sufficient data to support legal research tasks. This paper describes the development and analysis of a legal citation Network for New Zealand containing over 300.000 decisions from 125 different courts of all areas of law and jurisdiction. Using python, the authors assembled web crawlers, scrapers and an OCR pipeline to collect and convert court decisions from openly available sources such as NZLII into uniform and machine-readable text. This facilitated the use of regular expressions to identify references to other court decisions from within the decision text. The data was then imported into a graph-based database (Neo4j) with the courts and their respective cases represented as nodes and the extracted citations as links. Furthermore, additional links between courts of connected cases were added to indicate an indirect citation between the courts. Neo4j, as a graph-based database, allows efficient querying and use of network algorithms such as PageRank to reveal the most influential/most cited courts and court decisions over time. This paper shows that the in-degree distribution of the New Zealand legal citation network resembles a power-law distribution, which indicates a possible scale-free behavior of the network. This is in line with findings of the respective citation networks of the U.S. Supreme Court, Austria and Germany. The authors of this paper provide the database as an openly available data source to support further legal research. The decision texts can be exported from the database to be used for NLP-related legal research, while the network can be used for in-depth analysis. For example, users of the database can specify the network algorithms and metrics to only include specific courts to filter the results to the area of law of interest.

Keywords: case citation network, citation analysis, network analysis, Neo4j

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Authors: Shannon Steinmetz, Ellen Gethner

Abstract:

In this paper, a theoretical foundation is developed for patterned segmentation of audio using the geometry of music and statistical manifold. We demonstrate image content clustering using conic space sonification. The algorithm takes a geodesic curve as a model estimator of the three-parameter Gamma distribution. The random variable is parameterized by musical centricity and centric velocity. Model parameters predict audio segmentation in the form of duration and frame count based on the likelihood of musical geometry transition. We provide an example using a database of randomly selected images, resulting in statistically significant clusters of similar image content.

Keywords: sonification, musical information geometry, image, content extraction, automated quantification, audio segmentation, pattern recognition

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Authors: Artur Matuck, Guilherme F. Nobre

Abstract:

Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art

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Authors: Mueller Jann, Hoffmann Christian Hugo

Abstract:

Conventional quantitative risk management in banking is a risk factor of its own, because it rests on assumptions such as independence and availability of data which do not hold when rare events of extreme consequences are involved. There is a growing recognition of the need for alternative risk measures that do not make these assumptions. We propose a novel method for modeling the risk associated with investment products, in particular derivatives, by using a formal language for specifying financial contracts. Expressions in this language are interpreted in the category of values annotated with (a formal representation of) uncertainty. The choice of uncertainty formalism thus becomes a parameter of the model, so it can be adapted to the particular application and it is not constrained to classical probabilities. We demonstrate our approach using a simple logic-based uncertainty model and a case study in which we assess the risk of counter party default in a portfolio of collateralized loans.

Keywords: risk model, uncertainty monad, derivatives, contract algebra

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Authors: Baldev Setia, Raj Rajeshwari, Maneesh Kumar

Abstract:

Present paper is an analysis of water transmission mains failed due to surge analysis by using basic software known as Surge Analysis Program (SAP). It is a real time failure case study of a pipe laid in Una, Himachal Pradesh. The transmission main is a 13 kilometres long pipe with 7.9 kilometres as pumping main and 5.1 kilometres as gravitational main. The analysis deals with mainly pumping mains. The results are available in two text files. Besides, several files are prepared with specific view to obtain results in a graphical form. These results help to observe the pressure difference and surge occurrence at different locations along the pipe profile, which help to redesign the transmission main with different but suitable safety measures against possible surge. A technically viable and economically feasible design has been provided as per the relevant manual and standard code of practice.

Keywords: surge, water hammer, transmission mains, SAP 2000

Procedia PDF Downloads 393