Search results for: text alignment

Authors: Deborah O. Ajumobi, Michael Kyobe

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Studies show that women entrepreneurs are constrained and faced with challenges that inhibit the growth and performance of their businesses. However, with their human competencies, mobile technology and the appropriate business strategy, women-led SMEs can steer their businesses to better performance. While the need for SMEs to align these three elements has been suggested, there is limited knowledge on how SMEs can achieve this and no studies to the authors’ knowledge have examined this in women-led SMEs. This study therefore seeks to fill this gap by investigating how Women-led SMEs can best align these three elements to enhance business performance. In light of this, extensive literature review and theoretical work on the phenomenon has been conducted. Given the existence of the interplay between these three elements, we argue that the perspective of alignment as gestalts is most appropriate in determining the best way women-Led SMEs may align these aspects.

Keywords: women-led SMEs, human Competencies, mobile technology, business strategy, alignment

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Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

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Web scraping and text mining are popular computer science methods deployed by public health researchers to augment traditional epidemiological surveillance. However, within veterinary disease surveillance, such techniques are still in the early stages of development and have not yet been fully utilised. This study presents an exploration into the utility of incorporating internet-based data to better understand the smallholder farming communities within Scotland by using online text extraction and the subsequent mining of this data. Web scraping of the livestock fora was conducted in conjunction with text mining of the data in search of common themes, words, and topics found within the text. Results from bi-grams and topic modelling uncover four main topics of interest within the data pertaining to aspects of livestock husbandry: feeding, breeding, slaughter, and disposal. These topics were found amongst both the poultry and pig sub-forums. Topic modeling appears to be a useful method of unsupervised classification regarding this form of data, as it has produced clusters that relate to biosecurity and animal welfare. Internet data can be a very effective tool in aiding traditional veterinary surveillance methods, but the requirement for human validation of said data is crucial. This opens avenues of research via the incorporation of other dynamic social media data, namely Twitter and Facebook/Meta, in addition to time series analysis to highlight temporal patterns.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, smallholding, social media, web scraping, sentiment analysis, geolocation, text mining, NLP

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Authors: Wafa Slaibi Alsharafat

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Genetic algorithms (GA) are random algorithms as random numbers that are generated during the operation of the algorithm determine what happens. This means that if GA is applied twice to optimize exactly the same problem it might produces two different answers. In this project, we propose an evolutionary algorithm and Genetic Algorithm (GA) to be implemented in symmetric encryption and decryption. Here, user's message and user secret information (key) which represent plain text to be transferred into cipher text.

Keywords: GA, encryption, decryption, crossover

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Authors: Smita Pallavi, Raj Ratn Pranesh, Sumit Kumar

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Information representation as tables is compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used; however, industry still faces challenges in detecting and extracting tables from OCR (Optical Character Recognition) documents or images. This paper proposes an algorithm that detects and extracts multiple tables from OCR document. The algorithm uses a combination of image processing techniques, text recognition, and procedural coding to identify distinct tables in the same image and map the text to appropriate the corresponding cell in dataframe, which can be stored as comma-separated values, database, excel, and multiple other usable formats.

Keywords: table extraction, optical character recognition, image processing, text extraction, morphological transformation

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Authors: Ricardo Bragança, Tom Vinaimont

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This paper discusses the introduction of processes of self-determined learning (heutagogy) into a graduate course on financial modeling, using elements of entangled pedagogy and Biggs’ constructive alignment. To encourage learners to take control of their own learning journey and develop critical thinking and problem-solving skills, each session in the course receives tailor-made media-enhanced pedagogical assets. The design of those assets specifically supports entangled pedagogy, which opposes technological or pedagogical determinism in support of the collaborative integration of pedagogy and technology. Media assets for each of the ten sessions in this course consist of three components. The first component in this three-pronged approach is a game-cut-like cinematographic representation that introduces the context of the session. The second component represents a character from an open-source-styled community that encourages self-determined learning. The third component consists of a character, which refers to the in-person instructor and also aligns learning outcomes and assessment tasks, using Biggs’ constructive alignment, to the cinematographic and open-source-styled component. In essence, the course's metamorphosis helps students apply the concepts they've studied to actual financial modeling issues. The audio-visual media assets create a storyline throughout the course based on gamified and real-world applications, thus encouraging student engagement and interaction. The structured entanglement of pedagogy and technology also guides the instructor in the design of the in-class interactions and directs the focus on outcomes and assessments. The transformation process of this graduate course in financial modeling led to an institutional teaching award in 2021. The transformation of this course may be used as a model for other courses and programs in many disciplines to help with intended learning outcomes integration, constructive alignment, and Assurance of Learning.

Keywords: innovative education, active learning, entangled pedagogy, heutagogy, constructive alignment, project based learning, financial modeling, graduate business education

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Authors: Alireza Dantism

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Presently, describing the function of a protein sequence is one of the most common problems in biology. Usually, this problem can be facilitated by studying the three-dimensional structure of proteins. In the absence of a protein structure, comparative modeling often provides a useful three-dimensional model of the protein that is dependent on at least one known protein structure. Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) mainly based on its alignment with one or more proteins of known structure (templates). Comparative modeling consists of four main steps 1. Similarity between the target sequence and at least one known template structure 2. Alignment of target sequence and template(s) 3. Build a model based on alignment with the selected template(s). 4. Prediction of model errors 5. Optimization of the built model There are many computer programs and web servers that automate the comparative modeling process. One of the most important advantages of these servers is that it makes comparative modeling available to both experts and non-experts, and they can easily do their own modeling without the need for programming knowledge, but some other experts prefer using programming knowledge and do their modeling manually because by doing this they can maximize the accuracy of their modeling. In this study, a web-based tool has been designed to predict the tertiary structure of proteins using PHP and Python programming languages. This tool is called EasyModel. EasyModel can receive, according to the user's inputs, the desired unknown sequence (which we know as the target) in this study, the protein sequence file (template), etc., which also has a percentage of similarity with the primary sequence, and its third structure Predict the unknown sequence and present the results in the form of graphs and constructed protein files.

Keywords: structural bioinformatics, protein tertiary structure prediction, modeling, comparative modeling, modeller

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Authors: Nadya Inda Syartanti

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This research aims to identify, classify, and analyze descriptively the aspects of grammatical and lexical cohesion in the speech text of Japan’s Prime Minister Shinzo Abe entitled Nihon wa Modotte kimashita delivered in Washington DC, the United States on February 23, 2013, as a research data source. The method used is qualitative research, which uses descriptions through words that are applied by analyzing aspects of grammatical and lexical cohesion proposed by Halliday and Hasan (1976). The aspects of grammatical cohesion consist of references (personal, demonstrative, interrogative pronouns), substitution, ellipsis, and conjunction. In contrast, lexical cohesion consists of reiteration (repetition, synonym, antonym, hyponym, meronym) and collocation. Data classification is based on the 6 aspects of the cohesion. Through some aspects of cohesion, this research tries to find out the frequency of using grammatical and lexical cohesion in Shinzo Abe's speech text entitled Nihon wa Modotte kimashita. The results of this research are expected to help overcome the difficulty of understanding speech texts in Japanese. Therefore, this research can be a reference for learners, researchers, and anyone who is interested in the field of discourse analysis.

Keywords: cohesion, grammatical cohesion, lexical cohesion, speech text, Shinzo Abe

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Mária Csernoch, Piroska Biró

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The legends about “user-friendly” and “easy-to-use” birotical tools (computer-related office tools) have been spreading and misleading end-users. This approach has led us to the extremely high number of incorrect documents, causing serious financial losses in the creating, modifying, and retrieving processes. Our research proved that there are at least two sources of this underachievement: (1) The lack of the definition of the correctly edited, formatted documents. Consequently, end-users do not know whether their methods and results are correct or not. They are not aware of their ignorance. They are so ignorant that their ignorance does not allow them to realize their lack of knowledge. (2) The end-users’ problem-solving methods. We have found that in non-traditional programming environments end-users apply, almost exclusively, surface approach metacognitive methods to carry out their computer related activities, which are proved less effective than deep approach methods. Based on these findings we have developed deep approach methods which are based on and adapted from traditional programming languages. In this study, we focus on the most popular type of birotical documents, the text-based documents. We have provided the definition of the correctly edited text, and based on this definition, adapted the debugging method known in programming. According to the method, before the realization of text editing, a thorough debugging of already existing texts and the categorization of errors are carried out. With this method in advance to real text editing users learn the requirements of text-based documents and also of the correctly formatted text. The method has been proved much more effective than the previously applied surface approach methods. The advantages of the method are that the real text handling requires much less human and computer sources than clicking aimlessly in the GUI (Graphical User Interface), and the data retrieval is much more effective than from error-prone documents.

Keywords: deep approach metacognitive methods, error-prone birotical documents, financial losses, human and computer resources

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Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

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Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Mouheb Mehdoui, Amel Fraisse, Mounir Zrigui

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This paper explores the potential of short texts through semantic enrichment and disambiguation techniques. By employing context fusion, we aim to enhance the comprehension and utility of concise textual information. The methodologies utilized are grounded in recent advancements in natural language processing, which allow for a deeper understanding of semantics within limited text formats. Specifically, topic classification is employed to understand the context of the sentence and assess the relevance of added expressions. Additionally, word sense disambiguation is used to clarify unclear words, replacing them with more precise terms. The implications of this research extend to various applications, including information retrieval and knowledge representation. Ultimately, this work highlights the importance of refining short text processing techniques to unlock their full potential in real-world applications.

Keywords: information traffic, text summarization, word-sense disambiguation, semantic enrichment, ambiguity resolution, short text enhancement, information retrieval, contextual understanding, natural language processing, ambiguity

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Authors: Jean-Francois Caron

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This text explores the value of moral acts performed by war criminals, and the extent to which they should alleviate the punishment these individuals ought to receive for violating the rules of war. Without neglecting the necessity of retribution in war crimes cases, it argues from an ethical perspective that we should not rule out the possibility of considering lesser punishments for war criminals who decide to perform a moral act, as it might produce significant positive moral outcomes. This text also analyzes how such a norm could be justified from a moral perspective.

Keywords: war criminals, pardon, amnesty, retribution

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: Mahul Bhattacharyya, Niladri Sekhar Dash

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The present research paper is an experimental attempt to investigate the nature of variation in the register in three major text domains, namely, social, cultural, and political texts collected from the corpus of Bangla printed mass media texts. This present study uses a corpus of a moderate amount of Bangla mass media text that contains nearly one million words collected from different media sources like newspapers, magazines, advertisements, periodicals, etc. The analysis of corpus data reveals that each text has certain lexical properties that not only control their identity but also mark their uniqueness across the domains. At first, the subject domains of the texts are classified into two parameters namely, ‘Genre' and 'Text Type'. Next, some empirical investigations are made to understand how the domains vary from each other in terms of lexical properties like both function and content words. Here the method of comparative-cum-contrastive matching of lexical load across domains is invoked through word frequency count to track how domain-specific words and terms may be marked as decisive indicators in the act of specifying the textual contexts and subject domains. The study shows that the common lexical stock that percolates across all text domains are quite dicey in nature as their lexicological identity does not have any bearing in the act of specifying subject domains. Therefore, it becomes necessary for language users to anchor upon certain domain-specific lexical items to recognize a text that belongs to a specific text domain. The eventual findings of this study confirm that texts belonging to different subject domains in Bangla news text corpus clearly differ on the parameters of lexical load, lexical choice, lexical clustering, lexical collocation. In fact, based on these parameters, along with some statistical calculations, it is possible to classify mass media texts into different types to mark their relation with regard to the domains they should actually belong. The advantage of this analysis lies in the proper identification of the linguistic factors which will give language users a better insight into the method they employ in text comprehension, as well as construct a systemic frame for designing text identification strategy for language learners. The availability of huge amount of Bangla media text data is useful for achieving accurate conclusions with a certain amount of reliability and authenticity. This kind of corpus-based analysis is quite relevant for a resource-poor language like Bangla, as no attempt has ever been made to understand how the structure and texture of Bangla mass media texts vary due to certain linguistic and extra-linguistic constraints that are actively operational to specific text domains. Since mass media language is assumed to be the most 'recent representation' of the actual use of the language, this study is expected to show how the Bangla news texts reflect the thoughts of the society and how they leave a strong impact on the thought process of the speech community.

Keywords: Bangla, corpus, discourse, domains, lexical choice, mass media, register, variation

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Authors: C. B. Abhilash, Kavi Mahesh

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Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

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Authors: Mei-Yi Wu, Shang-Ming Huang

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The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

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Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: Busra Nur Ozguler Aktel

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This research aims to understand the factors that affect the ways in which tribes perceive and respond to violent conflicts in fragile states, given that tribes are essential stakeholders in many conflict-ridden fragile states, whether Afghanistan, Iraq, Syria, Libya, Somalia, Nigeria, or Yemen. It explores the primary questions of why some tribes align with extremist groups while others align with states during civil wars and why some tribes switch alignments. It argues that tribes form and switch alignments based on their perception of threats to their traditional tribal structure (internal dynamics) and clientelist relationships (external dynamics). Put differently; threat perceptions lead them to choose either the state or extremist groups that will more likely secure their traditional structure and patronage networks. This study focuses on Iraqi tribes as a case study. It builds a theory of tribal alignment formation based on ethnographic fieldwork in the Middle East, with a particular focus on Iraqi Sunni tribes living in the Kurdish region of Iraq and Jordan. As a result of the interviews with tribal leaders and members, local journalists, researchers, and politicians, it concludes that complex (re)alignments of tribes can determine the course and outcome of the conflicts, either mitigating or escalating violence. This study contributes to the larger body of conflict management and peacebuilding literature by introducing tribes as non-state actors and exploring their interactions with other actors in civil wars.

Keywords: civil wars, tribes, alignment formation, side-switching, Iraq

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Authors: Leila Anjomshoa, Firooz Sadighi

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This study investigated the effects of three types of pre-reading activities (vocabulary definitions, text summary and pre-passage questions) on EFL learners’ English reading comprehension. On the basis of the results of a placement test administered to two hundred and thirty English students at Kerman Azad University, 200 subjects (one hundred intermediate and one hundred advanced) were selected.Four texts, two of them at intermediate level and two of them at advanced level were chosen. The data gathered was subjected to the statistical procedures of ANOVA. A close examination of the results through Tukey’s HSD showed the fact that the experimental groups performed better than the control group, highlighting the effect of the treatment on them. Also, the experimental group C (text summary), performed remarkably better than the other three groups (both experimental & control). Group B subjects, vocabulary definitions, performed better than groups A and D. The pre-passage questions group’s (D) performance showed higher scores than the control condition.

Keywords: pre-reading activities, text summary, vocabulary definition, and pre-passage questions, reading comprehension

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Authors: Nurvadi Albekov

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Communicative situation is a basis, which designates potential models of ‘constructed forms’, a motivated basis of a text, for a text can be assumed as a product of the communicative situation. It is within the field of emergence the models of text, that can be potentially prognosticated in a certain communicative situation, are designated. Every text can be assumed as conceptual system structured on the base of certain communicative situation. However in the process of ‘structuring’ of a certain model of ‘conceptual system’ consciousness of a recipient is able act only within the border of the field of emergence for going out of this border indicates misunderstanding of the communicative situation. On the base of communicative situation we can witness the increment of meaning where the synergizing of the informative model of communication, formed by using of the invariant units of a language system, is a result of verbalization of the communicative situation. The potential of the models of a text, prognosticated within the field of emergence, also depends on the communicative situation. The conception ‘the field of emergence’ is interpreted as a unit of the language system, having poly-directed universal structure, implying the presence of the core, the center and the periphery, including different levels of means of a functioning system of language, both in terms of linguistic resources, and in terms of extra linguistic factors interaction of which results increment of a text. The conception ‘field of emergence’ is considered as the most promising in the analysis of texts: oral, written, printed and electronic. As a unit of the language system field of emergence has several properties that predict its use during the study of a text in different levels. This work is an attempt analysis of entropy in a text in the aspect of lingua-cultural code, prognosticated within the model of the field of emergence. The article describes the problem of entropy in the field of emergence, caused by influence of the extra-linguistic factors. The increasing of entropy is caused not only by the fact of intrusion of the language resources but by influence of the alien culture in a whole, and by appearance of non-typical for this very culture symbols in the field of emergence. The borrowing of alien lingua-cultural symbols into the lingua-culture of the author is a reason of increasing the entropy when constructing a text both in meaning and in structuring level. It is nothing but artificial formatting of lexical units that violate stylistic unity of a phrase. It is marked that one of the important characteristics descending the entropy in the field of emergence is a typical similarity of lexical and semantic resources of the different lingua-cultures in aspects of extra linguistic factors.

Keywords: communicative situation, field of emergence, lingua-culture, entropy

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Authors: Cherry Yieng Siang Ling, Joong Hee Lee, Myung Hwan Yun

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The quality of a product to be usable has become the basic requirement in consumer’s perspective while failing the requirement ends up the customer from not using the product. Identifying usability issues from analyzing quantitative and qualitative data collected from usability testing and evaluation activities aids in the process of product design, yet the lack of studies and researches regarding analysis methodologies in qualitative text data of usability field inhibits the potential of these data for more useful applications. While the possibility of analyzing qualitative text data found with the rapid development of data analysis studies such as natural language processing field in understanding human language in computer, and machine learning field in providing predictive model and clustering tool. Therefore, this research aims to study the application capability of text processing algorithm in analysis of qualitative text data collected from usability activities. This research utilized datasets collected from LG neckband headset usability experiment in which the datasets consist of headset survey text data, subject’s data and product physical data. In the analysis procedure, which integrated with the text-processing algorithm, the process includes training of comments onto vector space, labeling them with the subject and product physical feature data, and clustering to validate the result of comment vector clustering. The result shows 'volume and music control button' as the usability feature that matches best with the cluster of comment vectors where centroid comments of a cluster emphasized more on button positions, while centroid comments of the other cluster emphasized more on button interface issues. When volume and music control buttons are designed separately, the participant experienced less confusion, and thus, the comments mentioned only about the buttons' positions. While in the situation where the volume and music control buttons are designed as a single button, the participants experienced interface issues regarding the buttons such as operating methods of functions and confusion of functions' buttons. The relevance of the cluster centroid comments with the extracted feature explained the capability of text processing algorithms in analyzing qualitative text data from usability testing and evaluations.

Keywords: usability, qualitative data, text-processing algorithm, natural language processing

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Authors: Siti Ayu Ningsih

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This study aims to find the differences outcomes in learning reading comprehension with text and film as media on Indonesian Language for foreign speaker (BIPA) learning at intermediate level. By using quantitative and qualitative research methods, the respondent of this study is a single respondent from D'Royal Morocco Integrative Islamic School in grade nine from secondary level. Quantitative method used to calculate the learning outcomes that have been given the appropriate action cycle, whereas qualitative method used to translate the findings derived from quantitative methods to be described. The technique used in this study is the observation techniques and testing work. Based on the research, it is known that the use of the text media is more effective than the film for intermediate level of Indonesian Language for foreign speaker learner. This is because, when using film the learner does not have enough time to take note the difficult vocabulary and don't have enough time to look for the meaning of the vocabulary from the dictionary. While the use of media texts shows the better effectiveness because it does not require additional time to take note the difficult words. For the words that are difficult or strange, the learner can immediately find its meaning from the dictionary. The presence of the text is also very helpful for Indonesian Language for foreign speaker learner to find the answers according to the questions more easily. By matching the vocabulary of the question into the text references.

Keywords: Indonesian language for foreign speaker, learning outcome, media, reading comprehension

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Authors: Rosana Silvina Codaro, Patricia Amelia Tomei

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This study explores the relationship between job satisfaction and alignment between the individual´s current occupation and his talents, needs and values, namely his 'career anchors'. With this purpose in mind, a quantitative survey was performed for a non- graduate probabilistic sample of management business students of a private university in Rio de Janeiro. The results of the survey showed there is no significant association between satisfaction at work and alignment with the individual’s career anchor. The most frequent career anchor found for both genders was lifestyle, showing a trend towards finding a career that allows some balance between professional and personal life. The study also showed that self-employed individuals are more satisfied with their work than the individuals employed by a company are, and men are more satisfied at work than women are, Individuals aligned and not satisfied tend to be the ones who have fewer years of work experience and individuals not aligned and satisfied tend to be older.

Keywords: careers, career anchors, job satisfaction, Schein´s career anchor model

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Authors: Adriana M. Duquette, Derek P. Bornath

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Reaction Time (RT) and Movement Time (MT) are important components of everyday life that have an effect on the way in which we move about our environment. These measures become even more crucial when an event can be caused (or avoided) in a fraction of a second, such as the RT and MT required while driving. The purpose of this study was to develop a more simple method of testing RT and MT during simulated driving with or without text messaging, in a university-aged population (n = 170). In the control condition, a randomly-delayed red light stimulus flashed on a computer interface after the participant began pressing the ‘gas’ pedal on a foot switch mat. Simple RT was defined as the time between the presentation of the light stimulus and the initiation of lifting the foot from the switch mat ‘gas’ pedal; while MT was defined as the time after the initiation of lifting the foot, to the initiation of depressing the switch mat ‘brake’ pedal. In the texting condition, upon pressing the ‘gas’ pedal, a ‘text message’ appeared on the computer interface in a dialog box that the participant typed on their cell phone while waiting for the light stimulus to turn red. In both conditions, the sequence was repeated 10 times, and an average RT (seconds) and average MT (seconds) were recorded. Condition significantly (p = .000) impacted overall RTs, as the texting condition (0.47 s) took longer than the no-texting (control) condition (0.34 s). Longer MTs were also recorded during the texting condition (0.28 s) than in the control condition (0.23 s), p = .001. Overall increases in Response Time (RT + MT) of 189 ms during the texting condition would equate to an additional 4.2 meters (to react to the stimulus and begin braking) if the participant had been driving an automobile at 80 km per hour. In conclusion, increasing task complexity due to the dual-task demand of text messaging during simulated driving caused significant increases in RT (41%), MT (23%) and Response Time (34%), thus further strengthening the mounting evidence against text messaging while driving.

Keywords: simulated driving, text messaging, reaction time, movement time

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Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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Authors: Kimberli Breen

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Background Check-In, Check-Out is noted as the most widely implemented evidence-based intervention for youth at-promise within schools. Over twenty years of peer-reviewed research demonstrates the powerful effects of this Positive Behavioral Interventions and Supports (PBIS) practice when implemented with fidelity. However, literature to date has not explicitly connected this intervention with Positive Psychology. Aims This session will illustrate the powerful role Positive Psychology and core elements of PERMA play in the worldwide success of this intervention and how more explicitly aligning Positive Behavioral Interventions and Supports (PBIS) practices with Positive Psychology might remove common barriers to current implementation. Method Students receiving the Check-In, Check-Out intervention experience a warm, positive greeting from a caring adult (CICO Coach) before entering their first class of the day. Teachers then provide high frequency positive feedback to the students at the end of each time block, or segment, of the day. An “optimistic close” to the day is then provided by the same CICO Coach at the end of the school day via the “check-out” process, where students assess the day’s accomplishments and goal-set for the next day. Results CICO clearly aligns with the Positive Psychology core elements of PERMA (Positive Emotion, Engagement, Relationships, Meaning and Accomplishments) and could be further strengthened through explicit integration. Conclusion The already powerful impact and reach of the Check-In, Check-Out intervention can be further enhanced and expanded through greater alignment with Positive Psychology elements and practices. Initiating this important alignment with CICO also offers promise for further integration of Positive Psychology and Positive Behavioral Interventions and Supports.

Keywords: positive pscyhology, check-In check-out, schools, alignment

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Authors: Saurabh Farkya, Govinda Surampudi

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Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.

Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)

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Authors: R. A. Temah, L. A. Nkengla-Asi

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Planning for future disasters sets the stage for a variety of activities that may trigger multiple recurring operations and expose the community to opportunities to minimize risks. Local communities are increasingly embracing the necessity for planning based on local risks, but are also significantly challenged to effectively plan and response to disasters. This research examines basic risk-based disaster planning model and compares it with advanced risk-based planning that introduces the identification and alignment of varieties of local capabilities within and out of the local community that can be pivotal to facilitate the management of local risks and cascading effects prior to a disaster. A critical review shows that the identification and alignment of capabilities can potentially enhance risk-based disaster planning. A tailored holistic approach to risk based disaster planning is pivotal to enhance collective action and a reduction in disaster collective cost.

Keywords: capabilities, disaster planning, hazards, local community, risk-based

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Authors: Yoon-Cheol Park

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This research focuses on examining the information structures in the old Chinese character-Korean translation of the Vajrachedika-prajna-paramita sutra. The background of this research comes from the fact that there were no previous researches which looked into the information structures in the target text of the Vajrachedika-prajna-paramita sutra by now. The existing researches on the Buddhist scripture translation mainly put weight on message conveyance by literal and semantic translation methods. But the message conveyance from one language to another has a necessity to be delivered with equivalent information structure. Thus, this research is intended to investigate on the flow of old and new information in the target text of Buddhist scripture, compared with source text. The Vajrachedika-prajna-paramita sutra unlike other Buddhist scriptures is composed of conversational structures between Buddha and his disciple, Suboli. This implies that the information flow can be changed by utterance context and some propositions. So, this research tries to analyze the flow of old and new information within the source and target text. As a result of analysis, this research can discover the following facts; firstly, there are the differences of the information flow in the message conveyance between the old Chinese character and Korean by language features. The old Chinese character reveals that old-new information flow is developed, while Korean indicates new-old information flow because of word order. Secondly, the source text of the Vajrachedika-prajna-paramita sutra includes abstruse terminologies, jargon and abstract words. These make influence on the target text and cause the change of the information flow. But the repetitive expressions of these words provide the old information in the target text. Lastly, the Vajrachedika-prajna-paramita sutra offers the expository structure from conversations between Buddha and Suboli. It means that the information flow is developed in the way of explaining specific subjects and of paraphrasing unfamiliar phrases and expressions. From the results of analysis above, this research can verify that the information structures in the target text of the Vajrachedika-prajna-paramita sutra are changed by specific subjects and terminologies, developed with the new-old information flow by repetitive expressions or word order and reveal the information structures familiar to target culture. It also implies that the translation of the Vajrachedika-prajna-paramita sutra as a religious book needs the message conveyance to take into account the information structures of two languages.

Keywords: abstruse terminologies, the information structure, new and old information, old Chinese character-Korean translation

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Authors: Elahe Kamari

Abstract:

Research on translation process has been conducted for more than 20 years, investigating various issues and using different research methodologies. Most recently, researchers have started to use eye tracking to study translation processes. They believed that the observable, measurable data that can be gained from eye tracking are indicators of unobservable cognitive processes happening in the translators’ mind during translation tasks. The aim of this study was to investigate directionality in translation processes through using eye tracking. The following hypotheses were tested: 1) processing the target text requires more cognitive effort than processing the source text, in both directions of translation; 2) L2 translation tasks on the whole require more cognitive effort than L1 tasks; 3) cognitive resources allocated to the processing of the source text is higher in L1 translation than in L2 translation; 4) cognitive resources allocated to the processing of the target text is higher in L2 translation than in L1 translation; and 5) in both directions non-professional translators invest more cognitive effort in translation tasks than do professional translators. The performance of a group of 30 male professional translators was compared with that of a group of 30 male non-professional translators. All the participants translated two comparable texts one into their L1 (Persian) and the other into their L2 (English). The eye tracker measured gaze time, average fixation duration, total task length and pupil dilation. These variables are assumed to measure the cognitive effort allocated to the translation task. The data derived from eye tracking only confirmed the first hypothesis. This hypothesis was confirmed by all the relevant indicators: gaze time, average fixation duration and pupil dilation. The second hypothesis that L2 translation tasks requires allocation of more cognitive resources than L1 translation tasks has not been confirmed by all four indicators. The third hypothesis that source text processing requires more cognitive resources in L1 translation than in L2 translation and the fourth hypothesis that target text processing requires more cognitive effort in L2 translation than L1 translation were not confirmed. It seems that source text processing in L2 translation can be just as demanding as in L1 translation. The final hypothesis that non-professional translators allocate more cognitive resources for the same translation tasks than do the professionals was partially confirmed. One of the indicators, average fixation duration, indicated higher cognitive effort-related values for professionals.

Keywords: translation processes, eye tracking, cognitive resources, directionality

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