In the current digital environment, cyberbullying remains a significant threat to online safety and well-being. This study explores the technological advancements and strategies utilized in the project, providing comp...
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The wide spectrum of security challenges, spanning from physical tampering to transport layer vulnerabilities, necessitates a holistic and interdisciplinary strategy. By leveraging existing research while filling up t...
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The paper’s primary goal is to analyse and define guidelines and methodology for the ergonomic design of PET bottles. In designing any product, in addition to production requirements (design for manufacturing), ergon...
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This paper deals with distributed control of variable efficiency heterogeneous battery storage systems connected in a microgrid. The nonlinear efficiency of battery charging is taken from converters’ datasheet and id...
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Large Language Models (LLMs) have made significant strides in various tasks, yet their effectiveness in predicting disease progression remains relatively unexplored. To fill this gap, we use LLMs and employ advanced g...
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Kinesiology and its related disciplines (kinanthropometry, biomechanics, kinesiological rehabilitation, sports games) symbiotically attract new computer technologies, implementing them in the form of effective tools f...
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A face detection model can be used to detect the presence of a face in real time detection with great accuracy. However, the face detection model can only perform well under a very optimum condition and situation whic...
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Farmers and producers may suffer significant financial losses due to plant diseases. Effective control of plant diseases requires early identification and categorization of the illnesses. However, traditional plant di...
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Aspect-based sentiment analysis(ABSA)is a fine-grained *** fundamental subtasks are aspect termextraction(ATE)and aspect polarity classification(APC),and these subtasks are dependent and closely ***,most existing work...
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Aspect-based sentiment analysis(ABSA)is a fine-grained *** fundamental subtasks are aspect termextraction(ATE)and aspect polarity classification(APC),and these subtasks are dependent and closely ***,most existing works on Arabic ABSA content separately address them,assume that aspect terms are preidentified,or use a pipeline *** solutions design different models for each task,and the output from the ATE model is used as the input to the APC model,which may result in error propagation among different steps because APC is affected by ATE *** methods are impractical for real-world scenarios where the ATE task is the base task for APC,and its result impacts the accuracy of ***,in this study,we focused on a multi-task learning model for Arabic ATE and APC in which the model is jointly trained on two subtasks simultaneously in a *** paper integrates themulti-task model,namely Local Cotext Foucse-Aspect Term Extraction and Polarity classification(LCF-ATEPC)and Arabic Bidirectional Encoder Representation from Transformers(AraBERT)as a shred layer for Arabic contextual text *** LCF-ATEPC model is based on a multi-head selfattention and local context focus mechanism(LCF)to capture the interactive information between an aspect and its ***,data augmentation techniques are proposed based on state-of-the-art augmentation techniques(word embedding substitution with constraints and contextual embedding(AraBERT))to increase the diversity of the training *** paper examined the effect of data augmentation on the multi-task model for Arabic *** experiments were conducted on the original and combined datasets(merging the original and augmented datasets).Experimental results demonstrate that the proposed Multi-task model outperformed existing APC *** results were obtained by AraBERT and LCF-ATEPC with fusion layer(AR-LCF-ATEPC-Fusion)and the proposed data augmentation
The paper proposes a data-based approach in control of building temperature for the case of a single floor of an office building. Several obtained datasets are exploited to identify a mathematical model of building th...
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