Search results for: large language models (LLMS)

Authors: Ming Liu, Chong Wu, Bingquan Liu, Lei Chen

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Internet users have to face the massive amount of textual data every day. Organizing texts into categories can help users dig the useful information from large-scale text collection. Clustering, in fact, is one of the most promising tools for categorizing texts due to its unsupervised characteristic. Unfortunately, most of traditional clustering algorithms lose their high qualities on large-scale text collection. This situation mainly attributes to the high- dimensional vectors generated from texts. To effectively and efficiently cluster large-scale text collection, this paper proposes a vector reconstruction based clustering algorithm. Only the features that can represent the cluster are preserved in cluster’s representative vector. This algorithm alternately repeats two sub-processes until it converges. One process is partial tuning sub-process, where feature’s weight is fine-tuned by iterative process. To accelerate clustering velocity, an intersection based similarity measurement and its corresponding neuron adjustment function are proposed and implemented in this sub-process. The other process is overall tuning sub-process, where the features are reallocated among different clusters. In this sub-process, the features useless to represent the cluster are removed from cluster’s representative vector. Experimental results on the three text collections (including two small-scale and one large-scale text collections) demonstrate that our algorithm obtains high quality on both small-scale and large-scale text collections.

Keywords: vector reconstruction, large-scale text clustering, partial tuning sub-process, overall tuning sub-process

Procedia PDF Downloads 435

Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

Procedia PDF Downloads 105

Authors: Karen Guerrero

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Kindergarten-12th grade teachers engaged in teacher professional development (PD) on game-based learning techniques and strategies to support teaching STEMSS (STEM + Social Studies with an emphasis on geography across the curriculum) to language learners. Ten effective strategies have supported teaching content and language in tandem. To provide exiting teacher PD on summer and spring breaks, gamification has integrated these strategies to engage linguistically diverse student populations to provide informal language practice while students engage in the content. Teachers brought a STEMSS lesson to the PD, engaged in a wide variety of games (dice, cards, board, physical, digital, etc.), critiqued the games based on gaming elements, then developed, brainstormed, presented, piloted, and published their game-based STEMSS lessons to share with their colleagues. Pre and post-surveys and focus groups were conducted to demonstrate an increase in knowledge, skills, and self-efficacy in using gamification to teach content in the classroom. Provide an engaging strategy (gamification) to support teaching content and language to linguistically diverse students in the K-12 classroom. Game-based learning supports informal language practice while developing academic vocabulary utilized in the game elements/content focus, building both content knowledge through play and language development through practice. The study also investigated teacher's increase in knowledge, skills, and self-efficacy in using games to teach language learners. Mixed methods were used to investigate knowledge, skills, and self-efficacy prior to and after the gamification teacher training (pre/post) and to understand the content and application of developing and utilizing game-based learning to teach. This study will contribute to the body of knowledge in applying game-based learning theories to the K-12 classroom to support English learners in developing English skills and STEMSS content knowledge.

Keywords: gamification, teacher professional development, STEM, English learners, game-based learning

Procedia PDF Downloads 91

Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

Procedia PDF Downloads 138

Authors: Don August G. Delgado

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Foreign Language acquisition without enough motivation is tough because it is the force that drives students’ interest or enthusiasm to achieve learning. In addition, it also serves as the students’ beacon to achieve their goals, desires, dreams, and aspirations in life. Since it plays an integral factor in language learning acquisition, this study focuses on the integrative and instrumental motivation levels of all the first year students of Naresuan University International College. The identification of their motivation level and inclination in learning the English language will greatly help all NUIC lecturers and administrators to create a project or activities that they will truly enjoy and find worth doing. However, if the findings of this study will say otherwise, this study can also show to NUIC lecturers and administrators how they can help and transform NUIC freshmen on becoming motivated learners to enhance their English proficiency levels. All respondents in this study received an adopted and developed questionnaire from different researches in the same perspective. The questionnaire has 24 questions that were randomly arranged; 12 for integrative motivation and 12 for instrumental motivation. The questionnaire employed the five-point Likert scale. The tabulated data were analyzed according to its means and standard deviations using the Standard Deviation Calculator. In order to interpret the motivation level of the respondents, the Interpretation of Mean Scores was utilized. Thus, this study concludes that majority of the NUIC freshmen are neither integratively motivated nor instrumentally motivated students.

Keywords: motivation, integrative, foreign language acquisition, instrumental

Procedia PDF Downloads 228

Authors: Sanaa Abouras

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This research investigates the attitude of Egyptian Nubian University students towards the Arabic and the two Nubian languages, Nobiin, and Kenuzi-Dongola. The Nubian languages are called by Egyptian Nubians, Fadijja/Fadicca and Kenzi, respectively. Nubians are people who live in the Nubia area which lies between Egypt’s southern borders with the northern part of Sudan. Nubia is divided into two parts - one under the Egyptian regime, and the other under the Sudanese regime. The number of participants used in the study was forty - half male and half female. Twenty of these participants live in the Nubian region and are enrolled at the South Valley University in Aswan, Egypt. This number was compared with an additional twenty Egyptian-Nubian university students who live outside the Nubian region and attend various Egyptian universities located in Alexandria and Cairo. The hypothesis of this study is that Egyptian Nubian University students tend to have positive attitudes toward Arabic and also the Nubian languages. This research is a qualitative and partially quantitative one. Observations, questionnaires, and interviews were used to collect data in order to explore the following: (1) the language students prefer to speak at home and in public and if language preferences are gender-related, (2) the factors that influence the Egyptian Nubian university students' attitudes towards Arabic and Nubian languages, and (3) a look at the future of these ethnic Nubian languages. Results that answered the main question on the attitude of Egyptian Nubian University students toward Arabic and Nubian languages revealed that students who live inside and outside the Nubian region tend to have positive attitudes towards both the Arabic and the Nubian languages.

Keywords: language attitude, minority, Arabic language, Nubian Language

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Authors: Elena Krutskikh, Elena Khvatova

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In tertiary settings expanding students’ vocabulary and teaching discursive competence is seen as one of the chief goals of a professional development course. However, such a focus often is detrimental to students’ cognitive competences, such as analysis, synthesis, and creative processing of information, and deprives students of motivation for self-improvement and self-development of language skills. The presentation is going to argue that in an ESP course special attention should be paid to reading/listening which can promote understanding and using the language as a tool for solving significant real world problems, including professional ones. It is claimed that in the learning process it is necessary to maintain a balance between the content and the linguistic aspect of the educational process as language acquisition is inextricably linked with mental activity and the need to express oneself is a primary stimulus for using a language. A study conducted among undergraduates indicates that they place a premium on quality materials that motivate them and stimulate their further linguistic and professional development. Thus, more demands are placed on study materials that should contain new information for students and serve not only as a source of new vocabulary but also prepare them for real tasks related to professional activities.

Keywords: critical reading, english for professional development, english for specific purposes, high order thinking skills, lexical approach, vocabulary acquisition

Procedia PDF Downloads 167

Authors: Nodelman V.

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Despite serious difficulties in the assimilation of the conceptual system of Calculus, software in the educational process is used only occasionally, and even then, mainly for illustration purposes. The following are a few reasons: The non-trivial nature of the studied material, Lack of skills in working with software, Fear of losing time working with software, The variety of the software itself, the corresponding interface, syntax, and the methods of working with the software, The need to find suitable models, and familiarize yourself with working with them, Incomplete compatibility of the found models with the content and teaching methods of the studied material. This paper proposes an active use of the developed non-commercial software VusuMatica, which allows removing these restrictions through Broad support for the studied mathematical material (and not only Calculus). As a result - no need to select the right software, Emphasizing the unity of mathematics, its intrasubject and interdisciplinary relations, User-friendly interface, Absence of special syntax in defining mathematical objects, Ease of building models of the studied material and manipulating them, Unlimited flexibility of models thanks to the ability to redefine objects, which allows exploring objects characteristics, and considering examples and counterexamples of the concepts under study. The construction of models is based on an original approach to the analysis of the structure of the studied concepts. Thanks to the ease of construction, students are able not only to use ready-made models but also to create them on their own and explore the material studied with their help. The presentation includes examples of using VusuMatica in studying the concepts of limit and continuity of a function, its derivative, and integral.

Keywords: counterexamples, limitations and requirements, software, teaching and learning calculus, user-friendly interface and syntax

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Authors: Rezvan Khavari

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The Zagros fold-thrust belt in SW Iran is a part of the Alpine-Himalayan system which consists of a variety of structures with different sizes or geometries. The study area is Chamshir Dam, which is located on the Zohreh River, 20 km southeast of Gachsaran City (southwest Iran). The satellite images are valuable means available to geologists for locating geological or geomorphological features expressing regional fault or fracture systems, therefore, the satellite images were used for structural analysis of the Chamshir dam area. As well, using the DEM and geological maps, 3D Models of the area have been constructed. Then, based on these models, all the acquired fracture traces data were integrated in Geographic Information System (GIS) environment by using Arc GIS software. Based on field investigation and DEM model, main structures in the area consist of Cham Shir syncline and two fault sets, the main thrust faults with NW-SE direction and small normal faults in NE-SW direction. There are three joint sets in the study area, both of them (J1 and J3) are the main large fractures around the Chamshir dam. These fractures indeed consist with the normal faults in NE-SW direction. The third joint set in NW-SE is normal to the others. In general, according to topography, geomorphology and structural geology evidences, Chamshir dam has a potential for sliding in some parts of Gachsaran formation.

Keywords: DEM, chamshir dam, zohreh river, satellite images

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Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

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Authors: Anjalika Fernando, Banuka Athuraliya

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This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

Procedia PDF Downloads 104

Authors: Nargiz Ismayilova

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The issue of modernism and the concept of postmodernism has been the focus of world researchers for many years, and there are very few researchers who have come to a common denominator about this term. During the independence period, the expansion of the relations of Azerbaijani literature with the world has led to the spread of many currents and tendencies formed in the West to the literary environment in our country. In this context, the works created in our environment are distinguished by their extreme richness in terms of subject matter and diversity in terms of genre. As an interesting example of contemporary postmodern prose in Azerbaijan, Parviz Jabrayil's novel "In a Foreign Language" pays attention with its more different plotline. The disagreement exists among the critics about the novel. Some are looking for high artistry in work; others are satisfied with the elements of postmodernism in work. Delimitation of the border between modernism and postmodernism can serve to carry out a deep scientific study of the novel. The novel depicts the world in the author's consciousness against the background of water shortage (thirst) in the Old City (Icharishahar). The author deconstructs today's Ichari Shahar mould. Along with modernism, elements of postmodernism occupy a large place in the work. When we look at the general tendencies of postmodernist art, we see that science and individuality are questioned, criticizing the sharp boundaries of modernism and the negativity of these restrictions, and modernism offers alternatives to artistic production by identifying its negatives and shortcomings in the areas of artistic freedom. The novel is extremely interesting in this point of view.

Keywords: concept of postmodernism, modernism, delimitation, political postmodernism, modern postmodern prose, Azerbaijani literature, novel, comparison, world literature, analysis

Procedia PDF Downloads 137

Authors: Christian Angerer, Markus Lienkamp

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Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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Authors: Marielle Leijten, Catherine Meulemans, Sven De Maeyer, Luuk Van Waes

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For the diagnosis of Alzheimer's disease (AD), a large variety of neuropsychological tests are available. In some of these tests, linguistic processing - both oral and written - is an important factor. Language disturbances might serve as a strong indicator for an underlying neurodegenerative disorder like AD. However, the current diagnostic instruments for language assessment mainly focus on product measures, such as text length or number of errors, ignoring the importance of the process that leads to written or spoken language production. In this study, it is our aim to describe and test differences between cognitive and impaired elderly on the basis of a selection of writing process variables (inter- and intrapersonal characteristics). These process variables are mainly related to pause times, because the number, length, and location of pauses have proven to be an important indicator of the cognitive complexity of a process. Method: Participants that were enrolled in our research were chosen on the basis of a number of basic criteria necessary to collect reliable writing process data. Furthermore, we opted to match the thirteen cognitively impaired patients (8 MCI and 5 AD) with thirteen cognitively healthy elderly. At the start of the experiment, participants were each given a number of tests, such as the Mini-Mental State Examination test (MMSE), the Geriatric Depression Scale (GDS), the forward and backward digit span and the Edinburgh Handedness Inventory (EHI). Also, a questionnaire was used to collect socio-demographic information (age, gender, eduction) of the subjects as well as more details on their level of computer literacy. The tests and questionnaire were followed by two typing tasks and two picture description tasks. For the typing tasks participants had to copy (type) characters, words and sentences from a screen, whereas the picture description tasks each consisted of an image they had to describe in a few sentences. Both the typing and the picture description tasks were logged with Inputlog, a keystroke logging tool that allows us to log and time stamp keystroke activity to reconstruct and describe text production processes. The main rationale behind keystroke logging is that writing fluency and flow reveal traces of the underlying cognitive processes. This explains the analytical focus on pause (length, number, distribution, location, etc.) and revision (number, type, operation, embeddedness, location, etc.) characteristics. As in speech, pause times are seen as indexical of cognitive effort. Results. Preliminary analysis already showed some promising results concerning pause times before, within and after words. For all variables, mixed effects models were used that included participants as a random effect and MMSE scores, GDS scores and word categories (such as determiners and nouns) as a fixed effect. For pause times before and after words cognitively impaired patients paused longer than healthy elderly. These variables did not show an interaction effect between the group participants (cognitively impaired or healthy elderly) belonged to and word categories. However, pause times within words did show an interaction effect, which indicates pause times within certain word categories differ significantly between patients and healthy elderly.

Keywords: Alzheimer's disease, keystroke logging, matching, writing process

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Authors: Janine Just, Kerstin Meints

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The research aims to compare vocabulary size and grammatical development between US American English- and British English-speaking children at age 2;0. As there is evidence that precocious children with large vocabularies develop grammar skills earlier than their typically developing peers, it was investigated if this also holds true across varieties of English. Thus, if US American children start to produce words earlier than their British counterparts, this could mean that US children are also at an advantage in the early developmental stages of acquiring grammar. This research employs a British English adaptation of the MacArthur-Bates CDI Words and Sentences (Lincoln Toddler CDI) to compare vocabulary and also grammar scores with the updated US Toddler CDI norms. At first, the Lincoln TCDI was assessed for its concurrent validity with the Preschool Language Scale (PLS-5 UK). This showed high correlations for the vocabulary and grammar subscales between the tests. In addition, the frequency of the Toddler CDI’s words was also compared using American and British English corpora of adult spoken and written language. A paired-samples t-test found a significant difference in word frequency between the British and the American CDI demonstrating that the TCDI’s words were indeed of higher frequency in British English. We then compared language and grammar scores between US (N = 135) and British children (N = 96). A two-way between groups ANOVA examined if the two samples differed in terms of SES (i.e. maternal education) by investigating the impact of SES and country on vocabulary and sentence complexity. The two samples did not differ in terms of maternal education as the interaction effects between SES and country were not significant. In most cases, scores were not significantly different between US and British children, for example, for overall word production and most grammatical subscales (i.e. use of words, over- regularizations, complex sentences, word combinations). However, in-depth analysis showed that US children were significantly better than British children at using some noun categories (i.e. people, objects, places) and several categories marking early grammatical development (i.e. pronouns, prepositions, quantifiers, helping words). However, the effect sizes were small. Significant differences for grammar were found for irregular word forms and progressive tense suffixes. US children were more advanced in their use of these grammatical categories, but the effect sizes were small. In sum, while differences exist in terms of vocabulary and grammar ability, favouring US children, effect sizes were small. It can be concluded that most British children are ‘catching up’ with their US American peers at age 2;0. Implications of this research will be discussed.

Keywords: first language acquisition, grammar, parent report instrument, vocabulary

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Authors: H. Djebar, L. Khene, M. Boucenna, M. R. Djebar, M. N. Khebbeb, M. Djekoun

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Currently in toxicology, use of alternative models permits to understand the mechanisms of toxicity at different levels of cells. Objectives of our research concern the determination of NPs ZnO, TiO2, AlO2, and FeO2 effect on ciliate protist freshwater Paramecium sp and Helix aspersa. The result obtained show that NPs increased antioxidative enzyme activity like catalase, glutathione –S-transferase and level GSH. Also, cells treated with high concentrations of NPs showed a high level of MDA. In conclusion, observations from growth and enzymatic parameters suggest on one hand that treatment with NPs provokes an oxidative stress and on the other that snale and paramecium are excellent alternatives models for ecotoxicological studies.

Keywords: NPs, GST, catalase, GSH, MDA, toxicity, snale and paramecium

Procedia PDF Downloads 282

Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

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Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

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Authors: Raymond E. Raguindin

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Objective: This research studied the teaching improvement of daycare workers in imitation, joint attention, and language activities using the play-based early intervention training program in Cabanatuan City, Nueva Ecija. Methods: Focus group discussions were developed to explore the attitude, beliefs, and practices of daycare workers. Results: Findings of the study revealed that daycare workers have existing knowledge and experience in teaching children with autism. Their workshops on managing inappropriate behaviors of children with autism resulting in a general positive perception of accepting and teaching children with autism in daycare centers. Play based activities were modelled and participated in by daycare workers. These include demonstration, modelling, prompting and providing social reinforcers as reward. Five lectures and five training days were done to implement the training program. Daycare workers’ levels of skill in teaching imitation, joint attention and language were gathered before and after the participation in the training program. Findings suggest significant differences between pre-test and post test scores. They have shown significant improvement in facilitating imitation, joint attention, and language children with autism after the play-based early intervention training. They were able to initiate and sustain imitation, joint attention, and language activities with adequate knowledge and confidence. Conclusions: 1. Existing attitudes and beliefs greatly influenced the positive delivery mode of instruction. 2. Teacher-directed approach to improve attention, imitation, joint attention, and language of children with autism can be acquired by daycare workers. 3. Teaching skills and experience can be used as reference and basis for identifying future training needs.

Keywords: early intervention, imitation, joint attention, language

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Authors: Aysen Handan Girginer

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This study analyzes the possible causes of miscommunication between pilots and air traffic controllers by looking into a number of variables such as pronunciation, L1 interference, use of non-standard vocabulary. The purpose of this study is to enhance the knowledge of the aviation LSP instructors and to apply this knowledge to the design of new curriculum. A 16-item questionnaire was administered to 60 Turkish pilots who work for commercial airlines in Turkey. The questionnaire consists of 7 open-ended and 9 Likert-scale type questions. The analysis of data shows that there are certain pit holes that may cause communication problems for pilots that can be avoided through proper English language training. The findings of this study are expected to contribute to the development of new materials and to develop a language training model that is tailored to the needs of students of flight training department at the Faculty of Aeronautics and Astronautics. The results are beneficial not only to the instructors but also to the new pilots in training. Specific suggestions for aviation students’ training will be made during the presentation.

Keywords: curriculum design, materials development, LSP, pilot training

Procedia PDF Downloads 351

Authors: Alvaro Marin

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This paper explores the challenges in Cognitive Translation Studies (CTS) conceptual development to accommodate professionals’ perceptions in the language industry into CTS established theoretical apparatus, empirical research projects, and university pedagogical proposals. A comparative conceptual assessment framework is developed from a pluralist epistemological stance that promotes interdisciplinary explorations of the translation process. The framework is used to review key notions such as expertise or feedback, as understood by language industry stakeholders. This review is followed by an analysis of how these notions can enrich research constructs to be applied in empirical investigations of translators’ cognitive processes from an embedded, situated cognition perspective. Thus, it will be proposed to apply the conceptual assessment framework as an effort towards strengthening the interpretative research tools and bridging the gap between industry and academia. The conclusions of this analysis will serve as a basis to further discuss how professional practices, combined with our current knowledge about expertise development in cognitive science and Expertise Studies, can enhance the learning experience of university translation students and help them better understand the processes and requirements of professional cross-linguistic mediation.

Keywords: language industry, cognitive translation studies, translation cognitive theory, translation teaching

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Authors: Kate Benedicta Amenador, Dianjian Wang, Bright Nkrumah

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This extensive bibliometric study explores the dynamic influence of artificial intelligence in the field of English as a Foreign Language (EFL) between 2012 and 2024. The study, which examined 4,500 articles from Google Scholar, Modern Language Association Linguistics Abstracts, Web of Science, Scopus, Researchgate, and library genesis databases, indicates that AI integration in EFL is on the rise. This notable increase is ascribed to a variety of transformative events, including increased academic funding for higher education and the COVID-19 epidemic. The results of the study identify leading contributors, prominent authors, publishers and sources, with the United States, China and the United Kingdom emerging as key contributors. The co-occurrence analysis of key terms reveals five clusters highlighting patterns in AI-enhanced language instruction and learning, including evaluation strategies, educational technology, learning motivation, EFL teaching aspects, and learner feedback. The study also discusses the impact of various AIs in enhancing EFL writing skills with software such as Grammarly, Quilbot, and Chatgpt. The current study recognizes limitations in database selection and linguistic constraints. Nevertheless, the results provide useful insights for educators, researchers and policymakers, inspiring and guiding a cross-disciplinary collaboration and creative pedagogical techniques and approaches to teaching and learning in the future.

Keywords: artificial intelligence, bibliometrics study, VOSviewer visualization, English as a foreign language

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Authors: Ayman Mutahar Alrassas, Shaoran Ren, Renyuan Ren, Hung Vo Thanh, Mohammed Hail Hakimi, Zhenliang Guan

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The significant effect of CO₂ on global climate and the environment has gained more concern worldwide. Enhance oil recovery (EOR) associated with sequestration of CO₂ particularly into the depleted oil reservoir is considered the viable approach under financial limitations since it improves the oil recovery from the existing oil reservoir and boosts the relation between global-scale of CO₂ capture and geological sequestration. Consequently, practical measurements are required to attain large-scale CO₂ emission reduction. This paper presents an integrated modeling workflow to construct an accurate 3D reservoir geological model to estimate the storage capacity of CO₂ under geological uncertainty in an unconventional oil reservoir of the Paleogene Shahejie Formation (Es1) in the block Nv32, Shenvsi oilfield, China. In this regard, geophysical data, including well logs of twenty-two well locations and seismic data, were combined with geological and engineering data and used to construct a 3D reservoir geological modeling. The geological modeling focused on four tight reservoir units of the Shahejie Formation (Es1-x1, Es1-x2, Es1-x3, and Es1-x4). The validated 3D reservoir models were subsequently used to calculate the theoretical CO₂ storage capacity in the block Nv32, Shenvsi oilfield. Well logs were utilized to predict petrophysical properties such as porosity and permeability, and lithofacies and indicate that the Es1 reservoir units are mainly sandstone, shale, and limestone with a proportion of 38.09%, 32.42%, and 29.49, respectively. Well log-based petrophysical results also show that the Es1 reservoir units generally exhibit 2–36% porosity, 0.017 mD to 974.8 mD permeability, and moderate to good net to gross ratios. These estimated values of porosity, permeability, lithofacies, and net to gross were up-scaled and distributed laterally using Sequential Gaussian Simulation (SGS) and Simulation Sequential Indicator (SIS) methods to generate 3D reservoir geological models. The reservoir geological models show there are lateral heterogeneities of the reservoir properties and lithofacies, and the best reservoir rocks exist in the Es1-x4, Es1-x3, and Es1-x2 units, respectively. In addition, the reservoir volumetric of the Es1 units in block Nv32 was also estimated based on the petrophysical property models and fund to be between 0.554368

Keywords: CO₂ storage capacity, 3D geological model, geological uncertainty, unconventional oil reservoir, block Nv32

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Ekaterina Lukianchenko

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This article sums up a six-year experience of teaching English as a foreign language to over 900 university students at MGIMO (Moscow University of International Relations, Russia), all of them native speakers of Russian aged 16 to 23. By combining modern communicative approach to teaching with cognitive linguistics theories, one can deal more effectively with deeply rooted mistakes which particular students have of which conventional methods have failed to eliminate. If language items are understood as concepts and frames, and classroom activities as meaningful parts of language competence development, this might help to solve such problems as incorrect use of words, unsuitable register, and confused tenses - as well as logical or structural mistakes, and even certain psychological issues concerning essay writing. Along with classic teaching methods, such classroom practice includes plenty of interaction between students - playing special classroom games aimed at eliminating particular mistakes, working in pairs and groups, integrating all skills in one class. The main conclusions that the author of the experiment makes consist in an assumption that academic essay writing classes demand a balanced plan. This should not only include writing as such, but additionally feature elements of listening, reading, speaking activities specifically chosen according to the skills and language students will need to write the particular type of essay.

Keywords: academic essay writing, creative teaching, cognitive linguistics, competency-based approach, communicative language teaching, frame, concept

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Authors: Raninder Kaur Dhillon, Mayur Jethwa, Hardeep Singh Rai

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Information technology has made a pivotal progress across disparate disciplines, one of which is AEC (Architecture, Engineering and Construction) industry. CAD is a form of computer-aided building modulation that architects, engineers and contractors use to create and view two- and three-dimensional models. The AEC industry also uses building information modeling (BIM), a newer computerized modeling system that can create four-dimensional models; this software can greatly increase productivity in the AEC industry. BIM models generate open source IFC (Industry Foundation Classes) files which aim for interoperability for exchanging information throughout the project lifecycle among various disciplines. The methods developed in previous studies require either an IFC schema or MVD and software applications, such as an IFC model server or a Building Information Modeling (BIM) authoring tool, to extract a partial or complete IFC instance model. This paper proposes an efficient algorithm for extracting a partial and total model from an Industry Foundation Classes (IFC) instance model without an IFC schema or a complete IFC model view definition (MVD).

Keywords: BIM, CAD, IFC, MVD

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Authors: Gaye Senbag

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In English language teaching, feedback is considered as one of the main components of writing instruction. Teachers put a lot of time and effort in order to provide learners with written feedback for effective language learning. At Anadolu University School of Foreign Languages (AUSFL) students are given written feedback for their each piece of writing through online platforms such as Edmodo and Turnitin, and traditional methods. However, little is known regarding how learners value and respond to teacher-provided feedback. As the perceptions of the students remarkably affect their learning, this study examines how they perceive the effectiveness of feedback provided by the teacher. Aiming to analyse it, 30 intermediate level (B1+ CEFR level) students were given a questionnaire, which includes Likert scale questions. The results will be discussed in detail.

Keywords: feedback, perceptions, writing, English Language Teaching (ELT)

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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: Daniel Fulus Fom, Gau Patrick Damulak

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In this study, the Autoregressive Fractional Integrated Moving Average (ARFIMA) and Jordan Recurrent Neural Network (JRNN) models were employed to model the forecasting performance of the daily turbidity flow of White Clay Creek (WCC). The two methods were applied to the log difference series of the daily turbidity flow series of WCC. The measurements of error employed to investigate the forecasting performance of the ARFIMA and JRNN models are the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The outcome of the investigation revealed that the forecasting performance of the JRNN technique is better than the forecasting performance of the ARFIMA technique in the mean square error sense. The results of the ARFIMA and JRNN models were obtained by the simulation of the models using MATLAB version 8.03. The significance of using the log difference series rather than the difference series is that the log difference series stabilizes the turbidity flow series than the difference series on the ARFIMA and JRNN.

Keywords: auto regressive, mean absolute error, neural network, root square mean error

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Authors: Boubacar Niang, Denis Raulin

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This paper presents the design of a dedicated board for learning and programming with ATMEL AVR new generation micro controller’s family. This board designed as a "shield" for the Arduino Uno allows us to focus on the design and programming of basic micro controller functionalities in high level language with a considerable time saving because of dealing with additional components is not required.

Keywords: Arduino, microcontroller, programming, language

Procedia PDF Downloads 584

Authors: Muhammad Alhaji Maidugu

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The role played by Arabic and Islamic Studies in the history of Nigeria - particularly Northern part of the country - cannot be overemphasized. Before the British colonialism, Arabic language was the official language in some of the great empires in Nigeria such as the Kanem Borno Empire. Islam, on the other hand, is the state religion. Both the rulers and the ruled were deeply involved in the pursuit of Arabic and Islamic knowledge traveling as far as Egypt, Saudia Arabia for scholarship. Their homes are like a modern library where Islamic books are kept and used to teach the community the different fields of Arabic and Islamic Studies. Scholars of Arabic and Islamic Studies were highly regarded and well respected in the society as they were the decision makers, diplomats and advisers to the authorities. Unfortunately, the colonizers used their influence and force to replace this language with a foreign language. In fact, they tried to exterminate it. Arabic became less important in the country. Arabic and Islamic Students became less significant and anybody studying Arabic or Islamic Studies is looked down at with disdain, and the course is considered unprofessional. This paper aims at casting a glance in the position of Arabic and Islamic Studies in Yobe State, Nigeria and social, political, economical and moral challenges faced by the students at institutions of learning.

Keywords: challenges, students of Arabic and Islamic studies, tertiary, institutions, Yobe

Procedia PDF Downloads 359