Search results for: analyzing text data

Authors: Yuan-Jye Tseng, Ching-Yen Chen

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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

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Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: A. Anastasiou, K. S. Tingay

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Background: Discovering suitable datasets is an important part of health research, particularly for projects working with clinical data from patients organized in cohorts (cohort data), but with the proliferation of so many national and international initiatives, it is becoming increasingly difficult for research teams to locate real world datasets that are most relevant to their project objectives. We present a method for identifying healthcare institutes in the European Union (EU) which may hold haemato-oncology (HO) data. A key enabler of this research was the bibInsight platform, a scientometric data management and analysis system developed by the authors at Swansea University. Method: A PubMed search was conducted using HO clinical terms taken from previous work. The resulting XML file was processed using the bibInsight platform, linking affiliations to the Global Research Identifier Database (GRID). GRID is an international, standardized list of institutions, including the city and country in which the institution exists, as well as a category of the main business type, e.g., Academic, Healthcare, Government, Company. Countries were limited to the 28 current EU members, and institute type to 'Healthcare'. An article was considered valid if at least one author was affiliated with an EU-based healthcare institute. Results: The PubMed search produced 21,310 articles, consisting of 9,885 distinct affiliations with correspondence in GRID. Of these articles, 760 were from EU countries, and 390 of these were healthcare institutes. One affiliation was excluded as being a veterinary hospital. Two EU countries did not have any publications in our analysis dataset. The results were analysed by country and by individual healthcare institute. Networks both within the EU and internationally show institutional collaborations, which may suggest a willingness to share data for research purposes. Geographical mapping can ensure that data has broad population coverage. Collaborations with industry or government may exclude healthcare institutes that may have embargos or additional costs associated with data access. Conclusions: Data reuse is becoming increasingly important both for ensuring the validity of results, and economy of available resources. The ability to identify potential, specific data sources from over twenty thousand articles in less than an hour could assist in improving knowledge of, and access to, data sources. As our method has not yet specified if these healthcare institutes are holding data, or merely publishing on that topic, future work will involve text mining of data-specific concordant terms to identify numbers of participants, demographics, study methodologies, and sub-topics of interest.

Keywords: data reuse, data discovery, data linkage, journal articles, text mining

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Authors: Anh Duong

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The three-phase reading lesson has been put forth around the world as the new and innovative framework which is corresponding to the learner-centered trend in English language teaching and learning. Among three stages, pre-reading attracts many teachers’ and researchers’ attention for its vital role in preparing students with knowledge and interest in reading class. The researcher’s desire to exemplify effectiveness of activities prior to text reading has provoked the current study. Three main aspects were investigated in this paper, i.e. teachers’ and student’s perception of pre-reading stage, teachers’ exploitation of pre-reading techniques and teachers’ recommendation of effective pre-reading activities. Aiming at pre-reading techniques for first-year students at English Department, this study involved 200 fresh-men and 10 teachers from Division 1 to participate in the questionnaire survey. Interviews with the teachers and classroom observation were employed as a tool to take an insight into the responses gained from the early instrument. After a detailed procedure of analyzing data, the researcher discovered that thanks to the participants’ acclamation of pre-reading stage, this phase was frequently conducted by the surveyed teachers. Despite the fact that pre-reading activities apparently put a hand in motivating students to read and creating a joyful learning atmosphere, they did not fulfill another function as supporting students’ reading comprehension. Therefore, a range of techniques and notices when preparing and conducting pre-reading phase was detected from the interviewed teachers. The findings assisted the researcher to propose some related pedagogical implications concerning teachers’ source of pre-reading techniques, variations of suggested activities and first-year reading syllabus.

Keywords: pre-reading stage, pre-reading techniques, teaching reading, language teaching

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Authors: Christiane Paulus

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Post-Islamism assumes that the Quran should not be viewed in terms of what Lyotard identifies as a ‘meta-narrative'. However, its socio-ethical content can be viewed as critical of power discourse (Foucault). Practicing religion seems to be limited to rites and individual spirituality, taqwa. Alternatively, can we build on Muhammad Abduh's classic-modern reform and develop it through a postmodernist frame? This is the main question of this study. Through his general and vague remarks on the context of the Quran, Abduh was the first to refer to the historical and cultural distance of the text as an obstacle for interpretation. His application, however, corresponded to the modern absolute idea of authentic sharia. He was followed by Amin al-Khuli, who hermeneutically linked the content of the Quran to the theory of evolution. Fazlur Rahman and Nasr Hamid abu Zeid remain reluctant to go beyond the general level in terms of context. The hermeneutic circle, therefore, persists in challenging, how to get out to overcome one’s own assumptions. The insight into and the acceptance of the lasting ambivalence of understanding can be grasped as a postmodern approach; it is documented in Derrida's discovery of the shift in text meanings, difference, also in Lyotard's theory of différend. The resulting mixture of meanings (Wolfgang Welsch) can be read together with the classic ambiguity of the premodern interpreters of the Quran (Thomas Bauer). Confronting hermeneutic difficulties in general, Niklas Luhmann proves every description an attribution, tautology, i.e., remaining in the circle. ‘De-tautologization’ is possible, namely by analyzing the distinctions in the sense of objective, temporal and social information that every text contains. This could be expanded with the Kantian aesthetic dimension of reason (critique of pure judgment) corresponding to the iʽgaz of the Coran. Luhmann asks, ‘What distinction does the observer/author make?’ Quran as a speech from God to the first listeners could be seen as a discourse responding to the problems of everyday life of that time, which can be viewed as the general goal of the entire Qoran. Through reconstructing koranic Lifeworlds (Alfred Schütz) in detail, the social structure crystallizes the socio-economic differences, the enormous poverty. The koranic instruction to provide the basic needs for the neglected groups, which often intersect (old, poor, slaves, women, children), can be seen immediately in the text. First, the references to lifeworlds/social problems and discourses in longer koranic passages should be hypothesized. Subsequently, information from the classic commentaries could be extracted, the classical Tafseer, in particular, contains rich narrative material for reconstructing. By selecting and assigning suitable, specific context information, the meaning of the description becomes condensed (Clifford Geertz). In this manner, the text gets necessarily an alienation and is newly accessible. The socio-ethical implications can thus be grasped from the difference of the original problem and the revealed/improved order/procedure; this small step can be materialized as such, not as an absolute solution but as offering plausible patterns for today’s challenges as the Agenda 2030.

Keywords: postmodern hermeneutics, condensed description, sociological approach, small steps of reform

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Cristina Felipeto, Catherine Bore, Eduardo Calil

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This work aims to analyze and compare the punctuation marks (PM) in school texts of Brazilian and French students and the comments on these PM made spontaneously by the students during the ongoing text. Assuming textual genetics as an investigative field within a dialogical and enunciative approach, we defined a common methodological design in two 1st year classrooms (7 years old) of the primary school, one classroom in Brazil (Maceio) and the other one in France (Paris). Through a multimodal capture system of writing processes in real time and space (Ramos System), we recorded the collaborative writing proposal in dyads in each of the classrooms. This system preserves the classroom’s ecological characteristics and provides a video recording synchronized with dialogues, gestures and facial expressions of the students, the stroke of the pen’s ink on the sheet of paper and the movement of the teacher and students in the classroom. The multimodal register of the writing process allowed access to the text in progress and the comments made by the students on what was being written. In each proposed text production, teachers organized their students in dyads and requested that they should talk, combine and write a fictional narrative. We selected a Dyad of Brazilian students (BD) and another Dyad of French students (FD) and we have filmed 6 proposals for each of the dyads. The proposals were collected during the 2nd Term of 2013 (Brazil) and 2014 (France). In 6 texts written by the BD there were identified 39 PMs and 825 written words (on average, a PM every 23 words): Of these 39 PMs, 27 were highlighted orally and commented by either student. In the texts written by the FD there were identified 48 PMs and 258 written words (on average, 1 PM every 5 words): Of these 48 PM, 39 were commented by the French students. Unlike what the studies on punctuation acquisition point out, the PM that occurred the most were hyphens (BD) and commas (FD). Despite the significant difference between the types and quantities of PM in the written texts, the recognition of the need for writing PM in the text in progress and the comments have some common characteristics: i) the writing of the PM was not anticipated in relation to the text in progress, then they were added after the end of a sentence or after the finished text itself; ii) the need to add punctuation marks in the text came after one of the students had ‘remembered’ that a particular sign was needed; iii) most of the PM inscribed were not related to their linguistic functions, but the graphic-visual feature of the text; iv) the comments justify or explain the PM, indicating metalinguistic reflections made by the students. Our results indicate how the comments of the BD and FD express the dialogic and subjective nature of knowledge acquisition. Our study suggests that the initial learning of PM depends more on its graphic features and interactional conditions than on its linguistic functions.

Keywords: collaborative writing, erasure, graphic marks, learning, metalinguistic awareness, textual genesis

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Authors: Isahakyan Heghine

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Intertextuality, being in the centre of attention of both linguists and literary critics, is vividly expressed in the outstanding British novelist and philosopher J. Fowles' works. 'The Magus’ is a deep psychological and philosophical novel with vivid intertextual links with the Greek mythology and authors from different epochs. The aim of the paper is to show how intertextuality might serve as a dialogue between two authors (J. Fowles and J. Donne) disguised in the dialogue of two protagonists of the novel : Conchis and Nicholas. Contrastive viewpoints concerning man's isolation, loneliness are stated in the dialogue. Due to the conceptual analysis of the text it becomes possible both to decode the conceptual information of the text and find out its intertextual links.

Keywords: dialogue, conceptual analysis, isolation, intertextuality

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

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Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.

Keywords: EEG, epilepsy, phase correlation, seizure

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Authors: Elizabeta Krstić Vukelja

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Digitization of personal data is a consequence of the development of information and communication technologies that create a new work environment with many advantages and challenges, but also potential threats to privacy and personal data protection. Regulation (EU) 2016/679 of the European Parliament and of the Council is becoming a law and obligation that should address the issues of personal data protection and information security. The existence of the Regulation leads to the conclusion that national legislation in the field of virtual environment, protection of the rights of EU citizens and processing of their personal data is insufficiently effective. In the health system, special emphasis is placed on the processing of special categories of personal data, such as health data. The healthcare industry is recognized as a particularly sensitive area in which a large amount of medical data is processed, the digitization of which enables quick access and quick identification of the health insured. The protection of the individual requires quality IT solutions that guarantee the technical protection of personal categories. However, the real problems are the technical and human nature and the spatial limitations of the application of the Regulation. Some conclusions will be drawn by analyzing the implementation of the basic principles of the Regulation on the example of the Croatian health care system and comparing it with similar activities in other EU member states.

Keywords: regulation, healthcare system, personal dana protection, quality data assurance

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Authors: Vince Liégeois

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Language of immediacy and distance: Within their discourse theory, Koch & Oesterreicher establish a distinction between a language of immediacy and a language of distance. The former refers to those discourses which are oriented more towards a spoken norm, whereas the latter entails discourses oriented towards a written norm, regardless of whether they are realised phonically or graphically. This means that an utterance can be realised phonically but oriented more towards the written language norm (e.g., a scientific presentation or eulogy) or realised graphically but oriented towards a spoken norm (e.g., a scribble or chat messages). Research desiderata: The methodological approach from Koch & Oesterreicher has often been criticised for not providing a corpus-linguistic methodology, which makes it difficult to work with quantitative data or address large text collections within this research paradigm. Consequently, the Koch & Oesterreicher approach has difficulties gaining ground in those research areas which rely more on corpus linguistic research models, like text linguistics and LSP-research. A combinatory approach: Accordingly, we want to establish a combinatory approach with corpus-based linguistic methodology. To this end, we propose to (i) include data about the context of an utterance (e.g., monologicity/dialogicity, familiarity with the speaker) – which were called “conditions of communication” in the original work of Koch & Oesterreicher – and (ii) correlate the linguistic phenomenon at the centre of the inquiry (e.g., evaluation markers) to a group of linguistic phenomena deemed typical for either distance- or immediacy-language. Based on these two parameters, linguistic phenomena and texts could then be mapped on an immediacy-distance continuum. Pilot study: To illustrate the benefits of this approach, we will conduct a pilot study on evaluation phenomena in French television weather reports, a form of domain-sensitive discourse which has often been cited as an example of a “text genre”. Within this text genre, we will look at so-called “evaluation markers,” e.g., fixed strings like bad weather, stifling hot, and “no luck today!”. These evaluation markers help to communicate the coming weather situation towards the lay audience but have not yet been studied within the Koch & Oesterreicher research paradigm. Accordingly, we want to figure out whether said evaluation markers are more typical for those weather reports which tend more towards immediacy or those which tend more towards distance. To this aim, we collected a corpus with different kinds of television weather reports,e.g., as part of the news broadcast, including dialogue. The evaluation markers themselves will be studied according to the explained methodology, by correlating them to (i) metadata about the context and (ii) linguistic phenomena characterising immediacy-language: repetition, deixis (personal, spatial, and temporal), a freer choice of tense and right- /left-dislocation. Results: Our results indicate that evaluation markers are more dominantly present in those weather reports inclining towards immediacy-language. Based on the methodology established above, we have gained more insight into the working of evaluation markers in the domain-sensitive text genre of (television) weather reports. For future research, it will be interesting to determine whether said evaluation markers are also typical for immediacy-language-oriented in other domain-sensitive discourses.

Keywords: corpus-based linguistics, evaluation markers, language of immediacy and distance, weather reports

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Jaehyung An, Sungjoo Lee

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Patent documents constitute an up-to-date and reliable source of knowledge for reflecting technological advance, so patent analysis has been widely used for identification of technological trends and formulation of technology strategies. But, identifying technological information from patent data entails some limitations such as, high cost, complexity, and inconsistency because it rely on the expert’ knowledge. To overcome these limitations, researchers have applied to a quantitative analysis based on the keyword technique. By using this method, you can include a technological implication, particularly patent documents, or extract a keyword that indicates the important contents. However, it only uses the simple-counting method by keyword frequency, so it cannot take into account the sematic relationship with the keywords and sematic information such as, how the technologies are used in their technology area and how the technologies affect the other technologies. To automatically analyze unstructured technological information in patents to extract the semantic information, it should be transformed into an abstracted form that includes the technological key concepts. Specific sentence structure ‘SAO’ (subject, action, object) is newly emerged by representing ‘key concepts’ and can be extracted by NLP (Natural language processor). An SAO structure can be organized in a problem-solution format if the action-object (AO) states that the problem and subject (S) form the solution. In this paper, we propose the new methodology that can extract the SAO structure through technical elements extracting rules. Although sentence structures in the patents text have a unique format, prior studies have depended on general NLP (Natural language processor) applied to the common documents such as newspaper, research paper, and twitter mentions, so it cannot take into account the specific sentence structure types of the patent documents. To overcome this limitation, we identified a unique form of the patent sentences and defined the SAO structures in the patents text data. There are four types of technical elements that consist of technology adoption purpose, application area, tool for technology, and technical components. These four types of sentence structures from patents have their own specific word structure by location or sequence of the part of speech at each sentence. Finally, we developed algorithms for extracting SAOs and this result offer insight for the technology innovation process by providing different perspectives of technology.

Keywords: NLP, patent analysis, SAO, semantic-analysis

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Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

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E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

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Authors: Elena V. Syurina, Sophie Renckens, Martina Valente

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Objective: The objective of this study was to investigate the nature of the conversation around orthorexia nervosa (ON) on Instagram. Methods: The present study was conducted using mixed methods, combining a concurrent triangulation and sequential explanatory design. First, 3027 pictures posted on Instagram using #Orthorexia were analyzed. Then, a questionnaire about Instagram use related to ON was completed entirely by 185 respondents. These two quantitative data sources were statistically analyzed and triangulated afterwards. Finally, 9 interviews were conducted, to more deeply investigate what is being said about ON on Instagram and what the motivations to post about it are. Results: Four main categories of pictures were found to be represented in Instagram posts about ON: ‘food’, ‘people’, ‘text’, and ‘other.’ Savory and unprocessed food was most highly represented within the food category, and pictures of people were mostly pictures of the account holder. People who self-identify as having ON were more likely to post about ON, and they were significantly more likely to post about ‘food’, ‘people’ and ‘text.’ The goal of the posts was to raise awareness around ON, as well as to provide support for people who believe to be suffering from it. Conclusion: Since the conversation around ON on Instagram is supportive, it could be beneficial to consider Instagram use in the treatment of ON. However, more research is needed on a larger scale.

Keywords: orthorexia nervosa, Instagram, social media, disordered eating

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Authors: Atabong Awung Lekeazem

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The purpose of this paper is to identify the impact or role of incentives on employee’s performance with a particular emphasis on Korean workers. The process involves defining and explaining the different types of motivation. In defining them, we also bring out the difference between the two major types of motivations. The second phase of the paper shall involve gathering data/information from a sample population and then analyzing the data. In the analysis, we shall get to see the almost similar mentality or value which Koreans attach to motivation, which a slide different view coming only from top management personnel. The last phase shall have us presenting the data and coming to a conclusion from which possible knowledge on how managers and potential managers can ignite the best out of their employees.

Keywords: motivation, employee’s performance, Korean workers, business information systems

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Authors: Saeed Hosseini, Ali Reza Tahavvor

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Sound processing is one the subjects that newly attracts a lot of researchers. It is efficient and usually less expensive than other methods. In this paper the flow generated sound is used to estimate the flow speed of free flows. Many sound samples are gathered. After analyzing the data, a parameter named wave power is chosen. For all samples, the wave power is calculated and averaged for each flow speed. A curve is fitted to the averaged data and a correlation between the wave power and flow speed is founded. Test data are used to validate the method and errors for all test data were under 10 percent. The speed of the flow can be estimated by calculating the wave power of the flow generated sound and using the proposed correlation.

Keywords: the flow generated sound, free stream, sound processing, speed, wave power

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Authors: Thelma Palaoag, Melanie Basa, Jezreel Mark Panilo

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Checking short-answer questions and essays, whether it may be paper or electronic in form, is a tiring and tedious task for teachers. Evaluating a student’s output require wide array of domains. Scoring the work is often a critical task. Several attempts in the past few years to create an automated writing assessment software but only have received negative results from teachers and students alike due to unreliability in scoring, does not provide feedback and others. The study aims to create an application that will be able to check short-answer questions which incorporate information extraction. Information extraction is a subfield of Natural Language Processing (NLP) where a chunk of text (technically known as unstructured text) is being broken down to gather necessary bits of data and/or keywords (structured text) to be further analyzed or rather be utilized by query tools. The proposed system shall be able to extract keywords or phrases from the individual’s answers to match it into a corpora of words (as defined by the instructor), which shall be the basis of evaluation of the individual’s answer. The proposed system shall also enable the teacher to provide feedback and re-evaluate the output of the student for some writing elements in which the computer cannot fully evaluate such as creativity and logic. Teachers can formulate, design, and check short answer questions efficiently by defining keywords or phrases as parameters by assigning weights for checking answers. With the proposed system, teacher’s time in checking and evaluating students output shall be lessened, thus, making the teacher more productive and easier.

Keywords: information extraction, short-answer question, natural language processing, application

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Authors: Preeti Kumari, Ridhi Kapoor

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 In any communication, security is the most important issue in today’s world. In this paper, steganography is the process of hiding the important data into other data, such as text, audio, video, and image. The interest in this topic is to provide availability, confidentiality, integrity, and authenticity of data. The steganographic technique that embeds hides content with unremarkable cover media so as not to provoke eavesdropper’s suspicion or third party and hackers. In which many applications of compression, encryption, decryption, and embedding methods are used for digital image steganography. Due to compression, the nose produces in the image. To sustain noise in the image, the LSB insertion technique is used. The performance of the proposed embedding system with respect to providing security to secret message and robustness is discussed. We also demonstrate the maximum steganography capacity and visual distortion.

Keywords: steganography, LSB, encoding, information hiding, color image

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Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

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Authors: Riikka Elina Kallio

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“The walls have ears” phrase is defining the era of dictatorship in Portugal (1926–1974) and political unrest decades in Finland (1917–1948). The phrase is referring to the policing of the political, secret police, PIDE (Policia Internacional e de Defesa do Estado 1933–1969) in Portugal and VALPO (Valtiollinen Poliisi 1939–1948) in Finland. Free speech at any public space and even in private events could be fatal. The members of the PIDE/VALPO or informers/collaborators could be listening. Strict censorship under the Salazar´s regime was controlling media for example newspapers, music, and the film industry. Similarly, the politically affected censorship influenced the media in Finland in those unrest decades. This article examines the similarities and the differences in the images of the political police in Finland and Portugal, by analyzing Finnish and Portuguese films from the nineteen-thirties to nineteensixties. The text addresses two main research questions: what are the common and different features in the representations of the Finnish and Portuguese political police in films between the 1930s and 1960s, and how did the national censorship affect these representations? This study approach is interdisciplinary, and it combines film studies and criminology. Close reading is a practical qualitative method for analyzing films and in this study, close reading emphasizes the features of the police officer. Criminology provides the methodological tools for analysis of the police universal features and European common policies. The characterization of the police in this study is based on Robert Reiner´s 1980s and Timo Korander´s 2010s definitions of the police officer. The research material consisted of the Portuguese films from online film archives and Finnish films from Movie Making Finland -project´s metadata which offered suitable material by data mining the keywords such as poliisi, poliisipäällikkö and konstaapeli (police, police chief, police constable). The findings of this study suggest that even though there are common features of the images of the political police in Finland and Portugal, there are still national and cultural differences in the representations of the political police and policing.

Keywords: censorship, film studies, images, PIDE, political police, VALPO

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Authors: Inas Hussein

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Communication in the modern world is increasingly becoming multimodal due to globalization and the digital space we live in which have remarkably affected how people communicate. Accordingly, Multimodal Discourse Analysis (MDA) is an emerging paradigm in discourse studies with the underlying assumption that other semiotic resources such as images, colours, scientific symbolism, gestures, actions, music and sound, etc. combine with language in order to  communicate meaning. One of the effective multimodal media that combines both verbal and non-verbal elements to create meaning is political cartoons. Furthermore, since political and social issues are mirrored in political cartoons, these are regarded as potential objects of discourse analysis since they not only reflect the thoughts of the public but they also have the power to influence them. The aim of this paper is to analyze some selected cartoons on the recognition of Jerusalem as Israel's capital by the American President, Donald Trump, adopting a multimodal approach. More specifically, the present research examines how the various semiotic tools and resources utilized by the cartoonists function in projecting the intended meaning. Ten political cartoons, among a surge of editorial cartoons highlighted by the Anti-Defamation League (ADL) - an international Jewish non-governmental organization based in the United States - as publications in different Arabic-language newspapers in Egypt, Saudi Arabia, UAE, Oman, Iran and UK, were purposively selected for semiotic analysis. These editorial cartoons, all published during 6^th–18^th December 2017, invariably suggest one theme: Jewish and Israeli domination of the United States. The data were analyzed using the framework of Visual Social Semiotics. In accordance with this methodological framework, the selected visual compositions were analyzed in terms of three aspects of meaning: representational, interactive and compositional. In analyzing the selected cartoons, an interpretative approach is being adopted. This approach prioritizes depth to breadth and enables insightful analyses of the chosen cartoons. The findings of the study reveal that semiotic resources are key elements of political cartoons due to the inherent political communication they convey. It is proved that adequate interpretation of the three aspects of meaning is a prerequisite for understanding the intended meaning of political cartoons. It is recommended that further research should be conducted to provide more insightful analyses of political cartoons from a multimodal perspective.

Keywords: Multimodal Discourse Analysis (MDA), multimodal text, political cartoons, visual modality

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Authors: Krizette Ladera

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Fathers are there not only to provide the financial stability of a family but a father is also there to provide the love and support that usually people would see as the mother’s responsibility. To describe the lived experiences and how fathers make sense of their lived experiences with their children who have cerebral palsy is the main objective of the study. A qualitative research using a thematic analysis was used for the study. The qualitative research focused on the personal narratives, self-report and expression of the participant’s memory in terms of how they tell their stories. The interpretative phenomenological analysis was used to focus on the experience of the participants on how they will describe their experiences, and to also add on that the IPA will also attempt to describe and explain the meaning of human experiences using interview, specifically on the father who have a child that suffers from cerebral palsy. For the sampling technique, the snowball technique was used to gather participants from the referral of other participants. The five non-randomly selected fathers will be served as the participants for the research. A self-made interview with an open-ended question was used as the research instrument; it includes profiling of the respondent as well as their experiences in taking care of their child that suffers from cerebral palsy. In analyzing a data, the researcher used the thematic analysis where in the interview was made into a transcript, then it was organized and divided themes. After that, the relations of each themes, was identified and it was later documented and translated into written text format using thematic grouping. Finally, the researcher analyzed each data according to its themes and put it in a table to be presented in the result section of the study And as for the result of the study, the researcher was able to come up with the four (4) main themes that most of the participants experienced and those are: The experiences in finding out about the condition of the Child, disclosing the condition of the child to the family and its emotional effect, The experiences of living the day of day realities in providing the physical, financial, emotional and a well balanced environment to the child, and the religious perspectives of the fathers. Along with those four (4) themes comes the subtheme which explains the themes in a more detailed explanation.

Keywords: cerebral palsy, children, fathers, lived experiences

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Authors: Mai Ghazal, Ahmed Hammad

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Cost overruns in construction projects are considered as worldwide challenges since the cost performance is one of the main measures of success along with schedule performance. To overcome this problem, studies were conducted to investigate the cost overruns' factors, also projects' historical data were analyzed to extract new and useful knowledge from it. This research is studying and analyzing the effect of some factors causing cost overruns using the historical data from completed construction projects. Then, using these factors to estimate the probability of cost overrun occurrence and predict its percentage for future projects. First, an intensive literature review was done to study all the factors that cause cost overrun in construction projects, then another review was done for previous researcher papers about mining process in dealing with cost overruns. Second, a proposed data warehouse was structured which can be used by organizations to store their future data in a well-organized way so it can be easily analyzed later. Third twelve quantitative factors which their data are frequently available at construction projects were selected to be the analyzed factors and suggested predictors for the proposed model.

Keywords: construction management, construction projects, cost overrun, cost performance, data mining, data warehousing, knowledge discovery, knowledge management

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

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Authors: Tengku Sepora Tengku Mahadi

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Where the speed of book writing lags behind the high need for such material for tertiary studies, translation offers a way to enhance the equilibrium in this demand-supply equation. Nevertheless, translation is confronted by obstacles that threaten its effectiveness. The primary challenge to the production of efficient translations may well be related to the text-type and in terms of its complexity. A text that is intricately written with unique rhetorical devices, subject-matter foundation and cultural references will undoubtedly challenge the translator. Longer time and greater effort would be the consequence. To understand these text-related challenges, the present paper set out to analyze a lawbook entitled Learning the Law by David Melinkoff. The book is chosen because it has often been used as a textbook or for reference in many law courses in the United Kingdom and has seen over thirteen editions; therefore, it can be said to be a worthy book for studies in law. Another reason is the existence of a ready translation in Malay. Reference to this translation enables confirmation to some extent of the potential problems that might occur in its translation. Understanding the organization and the language of the book will help translators to prepare themselves better for the task. They can anticipate the research and time that may be needed to produce an effective translation. Another premise here is that this text-type implies certain ways of writing and organization. Accordingly, it seems practicable to adopt the functional theory of language as suggested by Michael Halliday as its theoretical framework. Concepts of the context of culture, the context of situation and measures of the field, tenor and mode form the instruments for analysis. Additional examples from similar materials can also be used to validate the findings. Some interesting findings include the presence of several other text-types or sub-text-types in the book and the dependence on literary discourse and devices to capture the meanings better or add color to the dry field of law. In addition, many elements of culture can be seen, for example, the use of familiar alternatives, allusions, and even terminology and references that date back to various periods of time and languages. Also found are parts which discuss origins of words and terms that may be relevant to readers within the United Kingdom but make little sense to readers of the book in other languages. In conclusion, the textual analysis in terms of its functions and the linguistic and textual devices used to achieve them can then be applied as a guide to determine the effectiveness of the translation that is produced.

Keywords: functional theory of language, lawbook text-type, rhetorical devices, culture

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Authors: Mina Darabi Amin

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In 1972, Hans Robert Jauss introduced the Reception Theory a version of Reader-response criticism, that suggests the literary critics to re-examine the relationship between the author, the work and the reader. The revealing of these relationships has shown that, besides the creation, the reception and the reading of the text have different levels which exempt it from a continuous reference to the meaning intended by the artist and could lead to multiplicity of possible interpretations according to the ‘Horizon of Expectations’. This theory could be associated with another intellectual process called ‘translation’, a process that is always confronted by different levels of readers in the target language and different levels of reception by these readers. By adopting the perspective of Reception theory in translation, we could ignore a particular kind of translation and consider the initiation to a literary text, its translation and its reception as a continuous process. Just like the creation of the text, the translation and its reception, are not made once and for all; they are confronted with different levels of reception and interpretation which are made and remade endlessly. After having known and crossing the first levels, the Horizons of Expectation could be extended and the reader could be initiated to the higher levels. On the other hand, we could say that the faithful and free translation are not opposed to each other, but depending on the type of reception by the readers and in a particular moment, the existence of both is necessary. In fact, it is the level of reception in readers and their Horizon of Expectations that determine the degree of fidelity and freedom of translation.

Keywords: reception theory, reading, literary translation, horizons of expectation, reader

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Authors: Trayan Kushev, E. Shaunn Mattingly, Andrew S. Manikas

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This study utilizes computer-aided text analysis (CATA) on the descriptions of 248,614 Kickstarter crowdfunding campaigns to reveal that backers are more likely to provide funding to projects that contain a higher percentage of creativity-speak words. Further, this relationship is observed to be stronger for product-based campaigns (e.g., games, technology, design) and weaker for content-based campaigns (e.g., film, music, publishing). In addition, both positive linguistic tone and the use of words expressing gratitude in the text of the campaign strengthen the positive effect of creativity-speak on campaign success.

Keywords: creativity-speak, crowdfunding, entrepreneurship, gratitude, tone

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

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Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

Procedia PDF Downloads 99