Search results for: adaptation of text

Authors: Tadesse Anberbir, Bankole Felix, Tomio Takara

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In the development of a text-to-speech synthesizer, automatic derivation of correct pronunciation from the grapheme form of a text is a central problem. Particularly deriving phonological features which are not shown in orthography is challenging. In the Amharic language, geminates and epenthetic vowels are very crucial for proper pronunciation, but neither is shown in orthography. In this paper, to proposed and integrated a morphological analyzer into an Amharic Text-to-Speech system, mainly to predict geminates and epenthetic vowel positions and prepared a duration modeling method. Amharic Text-to-Speech system (AmhTTS) is a parametric and rule-based system that adopts a cepstral method and uses a source filter model for speech production and a Log Magnitude Approximation (LMA) filter as the vocal tract filter. The naturalness of the system after employing the duration modeling was evaluated by sentence listening test, and we achieved an average Mean Opinion Score (MOS) 3.4 (68%), which is moderate. By modeling the duration of geminates and controlling the locations of epenthetic vowel, we are able to synthesize good quality speech. Our system is mainly suitable to be customized for other Ethiopian languages with limited resources.

Keywords: amharic, gemination, Speech synthesis, morphology, epenthesis

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Authors: Trisha Malhotra

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Sentiment analysis is a recent field of study that computationally assesses the emotional nature of a body of text. To assess its test-validity, sentiment analysis was carried out on the emotional corpus of text from a personal 15-day mood diary. Self-reported mood scores varied more or less accurately with daily mood evaluation score given by the software. On further assessment, it was found that while sentiment analysis was good at assessing ‘global’ mood, it was not able to ‘locally’ identify and differentially score synonyms of various emotional words. It is further critiqued for treating the intensity of an emotion as universal across cultures. Finally, the software is shown not to account for emotional complexity in sentences by treating emotions as strictly positive or negative. Hence, it is posited that a better output could be two (positive and negative) affect scores for the same body of text.

Keywords: analysis, data, diary, emotions, mood, sentiment

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Authors: Andrey V. Timofeev, Viktor M. Denisov

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A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture

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Authors: Ibrahim Hassan

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Motion typography is one of the most important types of visual communication based on display. Through the digital display media, we can control the text properties (size, direction, thickness, color, etc.). The use of motion typography in visual communication made it have several images. We need to adjust the terminology and clarify the different differences between them, so relying on the word motion typography -considered a general term- is not enough to separate the different communicative functions of the moving text. In this paper, we discuss the different effects of motion typography on Arabic writing and how we can achieve harmony between the movement and the letterform, and we will, during our experiments, present a new type of text movement.

Keywords: Arabic typography, motion typography, kinetic typography, fluid typography, temporal typography

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Authors: Farshideh Einsele, Hassan Foroosh

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In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using wellknown geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: camera-based OCR, feature extraction, document, image processing, grocery products

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Authors: Zarine Avetisyan

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Both in language and literature there exists the theory of recurrence of text and talk chunks which brings us to the notion of precedence. It must be stated that precedence as a pragma-linguistic phenomenon is yet underknown and it is the main objective of the present research to revisit and reveal it thoroughly. In line with the main research objective, analysis of political text and talk provides abundant relevant data for the illustration of the phenomenon of precedence. The analysis focuses on certain pragmatic universals (e.g. intention) and categories (e.g. speech techniques) which lead to the disclosure of the present object of study.

Keywords: intention, precedence, political discourse, pragmatic universals

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Authors: Tadesse Anberbir, Felix Bankole, Tomio Takara, Girma Mamo

Abstract:

In the development of a text-to-speech synthesizer, automatic derivation of correct pronunciation from the grapheme form of a text is a central problem. Particularly deriving phonological features which are not shown in orthography is challenging. In the Amharic language, geminates and epenthetic vowels are very crucial for proper pronunciation but neither is shown in orthography. In this paper, we proposed and integrated a morphological analyzer into an Amharic Text-to-Speech system, mainly to predict geminates and epenthetic vowel positions, and prepared a duration modeling method. Amharic Text-to-Speech system (AmhTTS) is a parametric and rule-based system that adopts a cepstral method and uses a source filter model for speech production and a Log Magnitude Approximation (LMA) filter as the vocal tract filter. The naturalness of the system after employing the duration modeling was evaluated by sentence listening test and we achieved an average Mean Opinion Score (MOS) 3.4 (68%) which is moderate. By modeling the duration of geminates and controlling the locations of epenthetic vowel, we are able to synthesize good quality speech. Our system is mainly suitable to be customized for other Ethiopian languages with limited resources.

Keywords: Amharic, gemination, speech synthesis, morphology, epenthesis

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Authors: Archit Yajnik

Abstract:

Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.

Keywords: hidden markov model, natural language processing, POS tagging, viterbi algorithm

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

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We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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Authors: Afia Shahid

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The writing of Samuel Beckett is associated with meaning in the meaninglessness and the production of what he calls ‘literature of unword’. The casual escape from the world of words in the form of silences and pauses, in his play Waiting for Godot, urges to ask question of their existence and ultimately leads to investigate the theory behind their use in the play. This paper proposes that these absences (silence and pause) in Beckett’s play force to think ‘beyond’ language. This paper asks how silence and pause in Beckett’s text speak for the emergence of poststructuralist text. It aims to identify the significant features of the philosophy of deconstruction in the play of Beckett to demystify the hostile complicity between literature and philosophy. With the interpretive paradigm of poststructuralism this research focuses on the text as a research data. It attempts to delineate the relationship between poststructuralist theoretical concerns and text of Beckett. Keeping in view the theoretical concerns of Poststructuralist theorist Jacques Derrida, the main concern of the discussion is directed towards the notion of ‘beyond’ language into the absences that are aimed at silencing the existing discourse with the ‘radical irony’ of this anti-formal art that contains its own denial and thus represents the idea of ceaseless questioning and radical contradiction in art and any text. This article asks how text of Beckett vibrates with loud silence and has disrupted language to demonstrate the emptiness of words and thus exploring the limitless void of absences. Beckett’s text resonates with silence and pause that is neither negation nor affirmation rather a poststructuralist’s suspension of reality that is ever changing with the undecidablity of all meanings. Within the theoretical notion of Derrida’s Différance this study interprets silence and pause in Beckett’s art. The silence and pause behave like Derrida’s Différance and have questioned their own existence in the text to deconstruct any definiteness and finality of reality to extend an undecidable threshold of poststructuralists that aims to evade the ‘labyrinth of language’.

Keywords: Différance, language, pause, poststructuralism, silence, text

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Authors: Alexandra-Monica Toma

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Internet memes are an element of computer mediated communication and an important part of online culture that combines text and image in order to generate meaning. This term coined by Richard Dawkings refers to more than a mere way to briefly communicate ideas or emotions, thus naming a complex and an intensely perpetuated phenomenon in the virtual environment. This paper approaches memes as a cultural artefact and a virtual trope that mirrors societal concerns and issues, and analyses the pragmatics of their use. Memes have to be analysed in series, usually relating to some image macros, which is proof of the interplay between imitation and creativity in the memes’ writing process. We believe that their potential to become viral relates to three key elements: adaptation to context, reference to a successful meme series, and humour (jokes, irony, sarcasm), with various pragmatic functions. The study also uses the concept of multimodality and stresses how the memes’ text interacts with the image, discussing three types of relations: symmetry, amplification, and contradiction. Moreover, the paper proves that memes could be employed as speech acts with illocutionary force, when the interaction between text and image is enriched through the connection to a specific situation. The features mentioned above are analysed in a corpus that consists of memes related to the COVID-19 pandemic. This corpus shows them to be highly adaptable to context, which helps build the feeling of connection and belonging in an otherwise tremendously fragmented world. Some of them are created based on well-known image macros, and their humour results from an intricate dialogue between texts and contexts. Memes created in relation to the COVID-19 pandemic can be considered speech acts and are often used as such, as proven in the paper. Consequently, this paper tackles the key features of memes, makes a thorough analysis of the memes sociocultural, linguistic, and situational context, and emphasizes their intertextuality, with special accent on their illocutionary potential.

Keywords: context, memes, multimodality, speech acts

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Authors: Olivia R. Rendon

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More than half of the world population lives in cities, in the UK, for example, 82% of the population was urban by 2013. Cities concentrate valuable and numerous infrastructure and sectors of the national economies. Cities are particularly vulnerable to climate change which will lead to higher damage costs in the future. There is thus a need to develop and invest in adaptation measures for cities to reduce the impact of flooding and other extreme weather events. Recent flood episodes present a significant and growing challenge to the UK and the estimated cost of urban flood damage is 270 million a year for England and Wales. This study aims to carry out cost-benefit analysis (CBA) of a nature-based approach for flood risk management in cities, focusing on the city of Leeds and the wider Aire catchment as a case study. Leeds was chosen as a case study due to its being one of the most flood vulnerable cities in the UK. In Leeds, over 4,500 properties are currently vulnerable to flooding and approximately £450 million of direct damage is estimated for a potential major flood from the River Aire. Leeds is also the second largest Metropolitan District in England with a projected population of 770,000 for 2014. So far the city council has mainly focused its flood risk management efforts on hard infrastructure solutions for the city centre. However, the wider Leeds district is at significant flood risk which could benefit from greener adaptation measures. This study presents estimates of a nature-based adaptation approach for flood risk management in Leeds. This land use management estimate is based on generating costings utilising primary and secondary data. This research contributes findings on the costs of different adaptation measures to flood risk management in a UK city, including the trade-offs and challenges of utilising nature-based solutions. Results also explore the potential implementation of the adaptation measures in the case study and the challenges of data collection and analysis for adaptation in flood risk management.

Keywords: green infrastructure, ecosystem services, woodland, adaptation, flood risk

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Authors: Erekle Magradze, Davit Soselia, Levan Shughliashvili, Irakli Koberidze, Shota Tsiskaridze, Victor Kakhniashvili, Tamar Chaghiashvili

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Since the beginning of active publishing activity in Georgia, voluminous printed material has been accumulated, the digitization of which is an important task. Digitized materials will be available to the audience, and it will be possible to find text in them and conduct various factual research. Digitizing scanned documents means scanning documents, extracting text from the scanned documents, and processing the text into a corresponding language model to detect inaccuracies and grammatical errors. Implementing these stages requires a unified, scalable, and automated platform, where the digital service developed for each stage will perform the task assigned to it; at the same time, it will be possible to develop these services dynamically so that there is no interruption in the work of the platform.

Keywords: NLP, OCR, BERT, Kubernetes, transformers

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Authors: Toktam Khatibi

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Self-supervised learning (SSL) includes machine learning models that are trained on one aspect and/or one part of the input to learn other aspects and/or part of it. SSL models are divided into two different categories, including pre-text task-based models and contrastive learning ones. Pre-text tasks are some auxiliary tasks learning pseudo-labels, and the trained models are further fine-tuned for downstream tasks. However, one important disadvantage of SSL using pre-text task solving is defining an appropriate pre-text task for each image dataset with a variety of image modalities. Therefore, it is required to design an appropriate pretext task automatically for each dataset and each downstream task. To the best of our knowledge, the automatic designing of pretext tasks for image analysis has not been considered yet. In this paper, we present a framework based on In-context learning that describes each task based on its input and output data using a pre-trained image transformer. Our proposed method combines the input image and its learned description for optimizing the pre-text task design and its hyper-parameters using Meta-learning models. The representations learned from the pre-text tasks are fine-tuned for solving the downstream tasks. We demonstrate that our proposed framework outperforms the compared ones on unseen tasks and image modalities in addition to its superior performance for previously known tasks and datasets.

Keywords: in-context learning (ICL), meta learning, self-supervised learning (SSL), vision-language domain, transformers

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Authors: E. E. Marschalko, K. Kalcza-Janosi, I. Kotta, B. Bibok

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Cultural moderation aspects have been highlighted in the literature on self-determination behavior in some cultures, including in the Hungarian population. There is a lack of validated instruments in Hungarian for the assessment of self-determination related behaviors. In order to fill in this gap, the aim of this study was the translation, cultural adaptation and validation of Self Determination Scale (Sheldon, 1995) for the Hungarian population. A total of 4335 adults participated in the study. The mean age of the participants was 27.97 (SD=9.60). The sample consisted mostly from females, less than 20% were males. Exploratory and confirmatory factor analyses were performed for adequacy checking. Cronbach’s alpha was used to examine the reliability of the factors. Our results revealed that the Hungarian version of SDS has good psychometric properties and it is a reliable tool for psychologist who would like to study or assess self-determination in their clients. The final, adapted and validated SDS items are presented in this paper.

Keywords: self-determination scale, Hungarian, adaptation, validation, reliability

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Authors: Taylor La Carriere

Abstract:

“What I had madly possessed was not she, but my own creation, another, fanciful Lolita perhaps, more real than Lolita; overlapping, encasing he and having no will, no consciousness indeed, no life of her own,” Vladimir Nabokov writes in his seminal work, Lolita. Throughout Nabokov’s novel, the eponymous character is rendered nonexistent through unreliable narrator Humbert Humbert’s impenetrable narrative, infused with lyrical rationalization. Instead, Lolita is “safely solipsised,” as Humbert muses, solidifying the potential for the erasure of Lolita’s agency and identity. In this literary work, Lolita’s voice is reduced to a nearly invisible presence, only seen through the eyes of her captor. However, in Stanley Kubrick’s film adaptation of Lolita (1962), the “nymphet,” as Nabokov coins, reemerges with a voice of her own, fueled by a lyric impulse, that displaces Humbert’s first-person narration. The lyric, as defined by Catherine Ing, is the voice of the invisible; it is also characterized by performance, the concentrated utterance of individual emotion, and the appearance of spontaneity. The novel’s lyricism is largely in the service of Humbert’s “seductive” voice, while the film reorients it more to Lolita’s subjectivity. Through a close analysis of Kubrick’s cinematic techniques, this paper examines the emergence and translation of Lolita’s voice in contrast with Humbert’s attempts to silence her in Nabokov’s Lolita, hypothesizing that Kubrick translates Lolita’s presence into a visual and aural voice with lyrical attributes, exemplified through the establishment of an altered power dynamic, Sue Lyon’s transformative performance as the titular character, Nelson Riddle and Bob Harris’ musical score, and the omission of Humbert’s first-person point-of-view. In doing so, the film reclaims Lolita’s agency by taking instances of Lolita’s voice in the novel as depicted in the last half of the work and expanding upon them in a way only cinematic depictions could allow. The results of this study suggest that Lolita’s voice in Kubrick’s adaptation functions without disrupting the lyricism present in Nabokov’s source text, materializing through the actions, expressions, and performance of Sue Lyon in the film. This voice, fueled by a lyric impulse of its own, refutes the silence bestowed upon the titular character and enables its ultimate reclamation upon the silver screen.

Keywords: cinema, adaptation, Lolita, lyric voice

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Authors: Tokihiko Akita, Seiichi Mita

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A millimeter-wave radar is the most robust against adverse environments, making it an essential environment recognition sensor for automated driving. However, the reflection signal is sparse and unstable, so it is difficult to obtain the high recognition accuracy. Deep learning provides high accuracy even for them in recognition, but requires large scale datasets with ground truth. Specially, it takes a lot of cost to annotate for a millimeter-wave radar. For the solution, utilizing a simulator that can generate an annotated huge dataset is effective. Simulation of the radar is more difficult to match with real world data than camera image, and recognition by deep learning with higher-order features using the simulator causes further deviation. We have challenged to improve the accuracy of traffic participant classification by fusing simulator and real-world data with domain adaptation technique. Experimental results with the domain adaptation network created by us show that classification accuracy can be improved even with a few real-world data.

Keywords: millimeter-wave radar, object classification, deep learning, simulation, domain adaptation

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Authors: Cynthia E. Nwobodo, A. E. Agwu

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The study was carried out in Benue State, Nigeria. Multi-stage sampling technique was used to select 120 respondents from two agricultural zones in the State. Data was collected using interview schedule. Descriptive statistics was used in data analysis. Findings showed that youth farmers in the area had positive attitude to climate change adaptation and mitigation as shown by their response to a set of positive and negative statement including: the youth are very important stakeholders in climate change issues (M= 2.91), youths should be encouraged to be climate change conscious (2.90), everybody should be involved in planting trees not just the government (M= 2.89), I will be glad to participate in climate change seminars (M= 2.89) among others. Findings on information seeking behavior indicate that majority (80.8 %) of the respondents sought climate change information from radio at an average of 19.78 times per month, 53.3 % sought from friends and neighbours at an average of 12.55 times per month and 42.5 % sought from family members at an average of 12.55 times per month among others. It was recommended that Youth farmers should be made important stakeholders in climate change policies and programmes since they have a very positive attitude to climate change adaptation and mitigation.

Keywords: adaptation, mitigation, attitude, climate change, youth farmers

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Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing

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Authors: Iftikhar A. Tayubi, Aabdulrahman Alsubhi, Abdullah Althrwi

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The deoxyribonucleic acid text provides a single source of high-quality Cryptography about Deoxyribonucleic acid sequence for structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to encrypt and decrypt Deoxy Ribonucleic Acid sequence text. It includes complex, securing by using Algorithm to encrypt and decrypt Deoxy Ribonucleic Acid sequence. The utility of this Deoxy Ribonucleic Acid Sequence Text is that, it can provide a user-friendly interface for users to Encrypt and Decrypt store the information about Deoxy Ribonucleic Acid sequence. These interfaces created in this project will satisfy the demands of the scientific community by providing fully encrypt of Deoxy Ribonucleic Acid sequence during this website. We have adopted a methodology by using C# and Active Server Page.NET for programming which is smart and secure. Deoxy Ribonucleic Acid sequence text is a wonderful piece of equipment for encrypting large quantities of data, efficiently. The users can thus navigate from one encoding and store orange text, depending on the field for user’s interest. Algorithm classification allows a user to Protect the deoxy ribonucleic acid sequence from change, whether an alteration or error occurred during the Deoxy Ribonucleic Acid sequence data transfer. It will check the integrity of the Deoxy Ribonucleic Acid sequence data during the access.

Keywords: algorithm, ASP.NET, DNA, encrypt, decrypt

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Authors: Narges Farokhshad, Milad Molazadeh, Saman Jamalabbasi, Hamed Babaei Giglou, Saeed Bibak

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The Persian language is an inflectional subject-object-verb language. This fact makes Persian a more uncertain language. However, using techniques such as Zero-Width Non-Joiner (ZWNJ) recognition, punctuation restoration, and Persian Ezafe construction will lead us to a more understandable and precise language. In most of the works in Persian, these techniques are addressed individually. Despite that, we believe that for text refinement in Persian, all of these tasks are necessary. In this work, we proposed a ViraPart framework that uses embedded ParsBERT in its core for text clarifications. First, used the BERT variant for Persian followed by a classifier layer for classification procedures. Next, we combined models outputs to output cleartext. In the end, the proposed model for ZWNJ recognition, punctuation restoration, and Persian Ezafe construction performs the averaged F1 macro scores of 96.90%, 92.13%, and 98.50%, respectively. Experimental results show that our proposed approach is very effective in text refinement for the Persian language.

Keywords: Persian Ezafe, punctuation, ZWNJ, NLP, ParsBERT, transformers

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Authors: Simiso Fisokuhle Nyandeni

Abstract:

Climate change has turned out to be a pandemic that has drawn the attention of many countries’ households around the globe, especially those whose livelihood and economic status depend on agricultural productivity. Hence, the agricultural sector is regarded as the sector that is most dependent on climate conditions for its productivity/harvest, yet in recent years this sector has been experiencing drought. However, adaptation seems to be a tool that every farmer looks upon as a solution to their challenges as their productivity keeps on being vulnerable to climate effects. Thus, exposure/access to the market seems to be a major challenge that faces especially small-scale farmers. We, therefore, examine the small-scale farmers’ constraints or challenges towards getting access to the market for them to get proper sales of their farming products. As a result, the adaptation capacity of every farm household varies on the financial status.

Keywords: climate change, small-scale farming, agriculture sector, adaptation

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Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari

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Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Keywords: steganography, watermarking, time complexity measurements, private keys

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Authors: Fadoua Ouamani, Narjès Bellamine Ben Saoud, Henda Hajjami Ben Ghézala

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In the last few years and over the last decades, there was a growing interest in the development of Computer Supported Collaborative Learning (CSCL) environments. However, the existing systems ignore the variety of learners and their socio-cultural differences, especially in the case of distant and networked learning. In fact, within such collaborative learning environments, learners from different socio-cultural backgrounds may interact together. These learners evolve within various cultures and social contexts and acquire different socio-cultural values and behaviors. Thus, they should be assisted while communicating and collaborating especially in an intercultural group. Besides, the communication and collaboration tools provided to each learner must depend on and be adapted to her/his socio-cultural profile. The main goal of this paper is to present the proposed socio-cultural adaptation approach based on and guided by ontologies to adapt CSCL environments to the socio-cultural profiles of its users (learners or others).

Keywords: CSCL, socio-cultural profile, adaptation, ontology

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Authors: Abdul Rahman M. Chamseddine, Mahmoud El-ashiri

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In the field of language teaching, communication skills are essential for the learner to achieve, however, these skills, in general, might not support the comprehension of some texts of literary or artistic nature like poetry. Understanding sentences and expressions is not enough to understand a poem; other skills are needed in order to understand the special structure of a text which literary meaning is inapprehensible even when the lingual meaning is well comprehended. And then there is the need for many other components that surpass one text to other similar texts that can be understood through solid traditions, which do not form an obstacle in the face of change and progress. This is not exclusive to texts that are classified as a literary but it is also the same with some daily short phrases and indicatively charged expressions that can be classified as literary or bear a taste of literary nature.. it can be found in Newpapers’ titles, TV news reports, and maybe football commentaries… the need to understand this special lingual use – described as literary – is highly important to understand this discourse that can be generally classified as very far from literature. This work will try to explore the role of the literary text in the language class and the way it is being covered or dealt with throughout all levels of acquiring proficiency. It will also attempt to survery the position of the literary text in some of the most important books for teaching Arabic around the world. The same way grammar is needed to understand the language, another (literary) grammar is also needed for understanding literature.

Keywords: language teaching, Arabic, literature, pedagogy, language proficiency

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Authors: Joe Dorbor Wuokolo

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Thousands of smallholder farmers in Todee District, Montserrado county, are currently vulnerable to the negative impact of climate change. The district, which is the agricultural hot spot for the county, is faced with unfavorable changes in the daily temperature due to climate change. Farmers in the district have observed a dramatic change in the ratio of rainfall to sunshine, which has caused a chilling effect on their crop yields. However, there is a lack of documentation regarding how farmers perceive and respond to these changes and challenges. A study was conducted in the region to examine the perceptions of smallholder farmers regarding the negative impact of climate change, the adaptation strategies practice, and the barriers that hinder the process of advancing adaptation strategy. On purpose, a sample of 41 respondents from five towns was selected, including five town chiefs, five youth leaders, five women leaders, and sixteen community members. Women and youth leaders were specifically chosen to provide gender balance and enhance the quality of the investigation. Additionally, to validate the barriers farmers face during adaptation to climate change, this study interviewed eight experts from local and international organizations and government ministries and agencies involved in climate change and agricultural programs on what they perceived as the major barrier in both local and national level that impede farmers adaptation to climate change impact. SPSS was used to code the data, and descriptive statistics were used to analyze the data. The weighted average index (WAI) was used to rank adaptation strategies and the perceived importance of adaptation practices among farmers. On a scale from 0 to 3, 0 indicates the least important technique, and 3 indicates the most effective technique. In addition, the Problem Confrontation Index (PCI) was used to rank the barriers that prevented farmers from implementing adaptation measures. According to the findings, approximately 60% of all respondents considered the use of irrigation systems to be the most effective adaptation strategy, with drought-resistant varieties making up 30% of the total. Additionally, 80% of respondents placed a high value on drought-resistant varieties, while 63% percent placed it on irrigation practices. In addition, 78% of farmers ranked and indicated that unpredictability of the weather is the most significant barrier to their adaptation strategies, followed by the high cost of farm inputs and lack of access to financing facilities. 80% of respondents believe that the long-term changes in precipitation (rainfall) and temperature (hotness) are accelerating. This suggests that decision-makers should adopt policies and increase the capacity of smallholder farmers to adapt to the negative impact of climate change in order to ensure sustainable food production.

Keywords: adaptation strategies, climate change, farmers’ perception, smallholder farmers

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Benjamin Kuester, Bjoern Eilert, Malte Stonis, Ludger Overmeyer

Abstract:

Increasing quality requirements make reliable and effective quality management indispensable. This includes the complaint handling in which the 8D method is widely used. The 8D report as a written documentation of the 8D method is one of the key quality documents as it internally secures the quality standards and acts as a communication medium to the customer. In practice, however, the 8D report is mostly faulty and of poor quality. There is no quality control of 8D reports today. This paper describes the use of natural language processing for the automated evaluation of 8D reports. Based on semantic analysis and text-mining algorithms the presented system is able to uncover content and formal quality deficiencies and thus increases the quality of the complaint processing in the long term.

Keywords: 8D report, complaint management, evaluation system, text-mining

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Authors: Alaa Osman, Sara Elgazzar, Breksal Elmiligy

Abstract:

The Supply Chain Operation Reference (SCOR) model is considered one of the most widely implemented supply chain performance measurement systems (SCPMSs). Several studies have been proposed on the SCOR model adaptation in developed countries context; while there is a limited availability of previous work on the SCPMSs application generally and the SCOR model specifically in developing nations. This paper presents a research agenda on the SCOR model adaptation in the developing countries. It aims at investigating the challenges of adapting the SCOR model to manage and measure supply chain performance in developing countries. The research will exemplify the system in the Egyptian automotive sector to gain a comprehensive understanding of how the application of the SCOR model can affect the performance of automotive companies in Egypt, with a necessary understanding of challenges and obstacles faced the adaptation of the model in the Egyptian supply chain context. An empirical study was conducted on the Egyptian automotive sector in three companies considering three different classes: BMW, Hyundai and Brilliance. First, in-depth interviews were carried out to gain an insight into the implementation and the relevance of the concepts of supply chain management and performance measurement in the Egyptian automotive industry. Then, a formal survey was designed based on the SCOR model five main processes (plan, source, make, deliver and return) and best practices to investigate the challenges and obstacles faced the adaptation of the SCOR model in the Egyptian automotive supply chain. Finally, based on the survey results, the appropriate best practices for each process were identified in order to overcome the SCOR model adaptation challenges. The results showed that the implementation of the SCOR model faced different challenges and unavailability of the required enablers. The survey highlighted the low integration of end-to-end supply chain, lacks commitment for the innovative ideas and technologies, financial constraints and lack of practical training and support as the main challenges faced the adaptation of the SCOR model in the Egyptian automotive supply chain. The research provides an original contribution to knowledge by proposing a procedure to identify challenges encountered during the process of SCOR model adoption which can pave a way for further research in the area of SCPMSs adaptation, particularly in the developing countries. The research can help managers and organizations to identify obstacles and difficulties of the SCOR model adaptation, subsequently this can facilitate measuring the improved performance or changes in the organizational performance.

Keywords: automotive sector, developing countries, SCOR model, supply chain performance

Procedia PDF Downloads 349

Authors: Pankaj Kumar

Abstract:

Rapid global changes resulted in unfavorable hydrological, ecological, and environmental changes and cumulatively affected natural resources. As a result, the local communities become vulnerable to water stress, poor hygiene, the spread of diseases, food security, etc.. However, the central point for this vulnerability revolves around water resources and the way people interrelate with the hydrological system. Also, most of the efforts to minimize the adverse effect of global changes are centered on the mitigation side. Hence, countries with poor adaptive capacities and poor governance suffer most in case of disasters. However, several transdisciplinary numerical tools are well designed and are capable of answering “what-if questions” through scenario analysis using a system approach. This study has predicted the future water environment in Marikina River in the National Capital Region, Metro Manila of Philippines, using Water Evaluation and Planning (WEAP), an integrated water resource management tool. Obtained results can answer possible adaptation measures along with their associated uncertainties. It also highlighted various challenges for the policy planners to design adaptation countermeasures as well as to track the progress of achieving SDG 6.0.

Keywords: water quality, Philippines, climate change adaptation, hydrological simulation, wastewater management, weap

Procedia PDF Downloads 75