Support Directional Shifting Vector: A Direction Based Machine Learning Classifier

Kowsher, Md.; Hossen, Imran; Tahabilder, Anik; Prottasha, Nusrat Jahan; Habib, K. M. Masum; Azmi, Zafril Rizal M.

doi:10.28991/esj-2021-01306

Cited by 16 publications

(7 citation statements)

References 18 publications

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“…It has forced teachers to learn new technologies and acquire related teaching and instructional skills. This has probably caused stress among teachers and students [17][18][19]. Globally, most schools have tried to provide students with interactive e-learning to replace faceto-face teaching.…”

Section: Features Of E-learning Platformsmentioning

confidence: 99%

Impediments of Using E-Learning Platforms for Teaching English: A Case Study in Jordan

Rababah¹,

Dalaeen²,

Ta'amneh³

et al. 2023

Int. J. Emerg. Technol. Learn.

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E-learning platforms are essential tools used widely for teaching and learning English, especially since the COVID-19 pandemic. They are also used to communicate and interact with students, assess progress, evaluate assignments, and provide feedback. However, teachers of English face potential barriers when they use such platforms. This study examines the use of e-learning platforms in teaching English as a foreign language in Jordan. The study employed a quantitative research method. The findings revealed that using e-learning platforms for educational purposes is beneficial regarding accessibility when attending courses. E-learning enabled the students to practise more and to be more engaged in the learning process, which improved their language skills. Effective e-learning platform strategies significantly broaden students' perceptions and increase the opportunity to exchange information with their classmates. Nonetheless, several impediments may hinder the application of e-learning platforms, including teacher-related, technical, and technological factors. The study recommends that teachers use interactive methods, including images, sounds, videos, and multimedia, to engage learners with various needs and abilities. The study also suggests building codified standards when designing e-learning to develop students' skills at all levels and training teachers on using modern technological strategies in e-learning.

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Section: Features Of E-learning Platformsmentioning

confidence: 99%

Impediments of Using E-Learning Platforms for Teaching English: A Case Study in Jordan

Rababah¹,

Dalaeen²,

Ta'amneh³

et al. 2023

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

show abstract

“…A few examples of the different areas include the optimisation of designing airfoils, turbine blades, vehicle crash tests, proteins, and drugs [28,36]. As the surrogate model is a substitute for the system under consideration, its selection is problem dependent and does not support a one-size-fits-all approach [32,15]. The review paper completed by Bhoesekar et al [8] details that the surrogate model selection process is quite challenging and that problem categorisation into either feasibility, prediction or optimisation is beneficial to the selection of a suitable surrogate model.…”

Section: Introductionmentioning

confidence: 99%

Surrogate Assisted Evolutionary Multi-objective Optimisation applied to a Pressure Swing Adsorption system

Stander¹,

Woolway²,

Zyl³

2022

Preprint

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Chemical plant design and optimisation have proven challenging due to the complexity of these real-world systems. The resulting complexity translates into high computational costs for these systems' mathematical formulations and simulation models. Research has illustrated the benefits of using machine learning surrogate models as substitutes for computationally expensive models during optimisation. This paper extends recent research into optimising chemical plant design and operation. The study further explores Surrogate Assisted Genetic Algorithms (SA-GA) in more complex variants of the original plant design and optimisation problems, such as the inclusion of parallel and feedback components. The novel extension to the original algorithm proposed in this study, Surrogate Assisted NSGA-II (SA-NSGA), was tested on a popular literature case, the Pressure Swing Adsorption (PSA) system. We further provide extensive experimentation, comparing various meta-heuristic optimisation techniques and numerous machine learning models as surrogates. The results for both sets of systems illustrate the benefits of using Genetic Algorithms as an optimisation framework for complex chemical plant system design and optimisation for both single and

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“…We used some NLP datasets for the proposed BERT model's performance analysis. We compared them with classical machine learning and hybrid deep learning models [9], including LSTM [10], CNN [11], CRF, and proved that the Bangla-BERT model outperformed them. When we compared the outcomes to the current state of the art in performance, Bangla-BERT came out on top [12].…”

mentioning

confidence: 99%

Bangla-BERT: Transformer-Based Efficient Model for Transfer Learning and Language Understanding

et al. 2022

Self Cite

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The advent of pre-trained language models has directed a new era of Natural Language Processing (NLP), enabling us to create powerful language models. Among these models, Transformer-based models like BERT have grown in popularity due to their cutting-edge effectiveness. However, these models heavily rely on resource-intensive languages, forcing other languages into multilingual models(mBERT). The two fundamental challenges with mBERT become significantly more challenging in a resource-constrained language like Bangla. It was trained on a limited and organized dataset and contained weights for all other languages. Besides, current research on other languages suggests that a language-specific BERT model will exceed multilingual ones. This paper introduces Bangla-BERT a , a monolingual BERT model for the Bangla language. Despite the limited data available for NLP tasks in Bangla, we perform pre-training on the largest Bangla language model dataset, BanglaLM, which we constructed using 40 GB of text data. Bangla-BERT achieves the highest results in all datasets and vastly improves the state-of-the-art performance in binary linguistic classification, multilabel extraction, and named entity recognition, outperforming multilingual BERT and other previous research. The pre-trained model is assessed against several non-contextual models such as Bangla fasttext and word2vec the downstream tasks. Finally, this model is evaluated by transfer learning based on hybrid deep learning models such as LSTM, CNN, and CRF in NER, and it is observed that Bangla-BERT outperforms state-of-the-art methods. The proposed Bangla-BERT model is assessed by using benchmark datasets, including Banfakenews, Sentiment Analysis on Bengali News Comments, and Cross-lingual Sentiment Analysis in Bengali. Finally, it is concluded that Bangla-BERT surpasses all prior state-of-the-art results by 3.52%, 2.2%, and 5.3%. a https://huggingface.co/Kowsher/bangla-bert INDEX TERMS Bangla NLP, BERT-Base, Large Corpus,Transformer I. INTRODUCTION P RE-TRAINED language models based on the transformer architecture have become an absolute standard for state-of-the-art performance on a wide variety of natural language processing applications [1].BERT, a renowned transformer-based technique, brought a great revolution that had huge impacts on the evolution of NLP [2]. Since its release as an academic research paper, this technologically pioneering NLP model has amazed the AI world. It's the firstever deeply bidirectional and fully unsupervised technique

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Support Directional Shifting Vector: A Direction Based Machine Learning Classifier

Cited by 16 publications

References 18 publications

Impediments of Using E-Learning Platforms for Teaching English: A Case Study in Jordan

Impediments of Using E-Learning Platforms for Teaching English: A Case Study in Jordan

Surrogate Assisted Evolutionary Multi-objective Optimisation applied to a Pressure Swing Adsorption system

Bangla-BERT: Transformer-Based Efficient Model for Transfer Learning and Language Understanding

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