Mengqi Zhang¹, Jiazhao Chai², Jianxiang Cao³, Jialing Ji³, Tong Yi^4,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3743-3762, 2024, DOI:10.32604/cmc.2024.048486

Abstract In recent years, deep learning methods have developed rapidly and found application in many fields, including natural language processing. In the field of aspect-level sentiment analysis, deep learning methods can also greatly improve the performance of models. However, previous studies did not take into account the relationship between user feature extraction and contextual terms. To address this issue, we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method. To be specific, we design user comment feature extraction (UCFE) to distill salient features from users’ historical comments and transform them into representative user feature vectors.… More >

Zhaoliang Wu¹, Yuewei Wu^1,2, Xiaoli Feng¹, Jiajun Zou³, Fulian Yin^1,2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3391-3412, 2024, DOI:10.32604/cmc.2024.047076

Abstract Aspect-Based Sentiment Analysis (ABSA) is a fundamental area of research in Natural Language Processing (NLP). Within ABSA, Aspect Sentiment Quad Prediction (ASQP) aims to accurately identify sentiment quadruplets in target sentences, including aspect terms, aspect categories, corresponding opinion terms, and sentiment polarity. However, most existing research has focused on English datasets. Consequently, while ASQP has seen significant progress in English, the Chinese ASQP task has remained relatively stagnant. Drawing inspiration from methods applied to English ASQP, we propose Chinese generation templates and employ prompt-based instruction learning to enhance the model’s understanding of the task, ultimately improving ASQP performance in the… More >

Asmaa Habib Alanzi, N. Ameer Ahammad^*

Frontiers in Heat and Mass Transfer, Vol.21, pp. 179-197, 2023, DOI:10.32604/fhmt.2023.042009

Abstract The conversion of solar radiation to thermal energy has recently attracted a lot of interest as the requirement for renewable heat and power grows. Due to their enhanced ability to promote heat transmission, nanofluids can significantly contribute to enhancing the efficiency of solar-thermal systems. This article focus solar energy aspect on the effects of the thermal radiation in the flow of a hyperbolic tangent nanofluid containing magnesium oxide (MgO) and silver (Ag) are the nanoparticle with the base fluid as kerosene through a wedge and stagnation. The system of hybrid nanofluid transport equations are transformed into ordinary differential systems using… More >

Bishrul Haq¹, Sher Muhammad Daudpota¹, Ali Shariq Imran², Zenun Kastrati^3,*, Waheed Noor⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 115-137, 2023, DOI:10.32604/cmc.2023.040638

Abstract The Internet has become one of the significant sources for sharing information and expressing users’ opinions about products and their interests with the associated aspects. It is essential to learn about product reviews; however, to react to such reviews, extracting aspects of the entity to which these reviews belong is equally important. Aspect-based Sentiment Analysis (ABSA) refers to aspects extracted from an opinionated text. The literature proposes different approaches for ABSA; however, most research is focused on supervised approaches, which require labeled datasets with manual sentiment polarity labeling and aspect tagging. This study proposes a semi-supervised approach with minimal human… More >

Waqas Ahmad¹, Hikmat Ullah Khan^1,2,*, Fawaz Khaled Alarfaj^3,*, Saqib Iqbal⁴, Abdullah Mohammad Alomair³, Naif Almusallam³

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3101-3124, 2023, DOI:10.32604/iasc.2023.040614

Abstract Aspect-based sentiment analysis aims to detect and classify the sentiment polarities as negative, positive, or neutral while associating them with their identified aspects from the corresponding context. In this regard, prior methodologies widely utilize either word embedding or tree-based representations. Meanwhile, the separate use of those deep features such as word embedding and tree-based dependencies has become a significant cause of information loss. Generally, word embedding preserves the syntactic and semantic relations between a couple of terms lying in a sentence. Besides, the tree-based structure conserves the grammatical and logical dependencies of context. In addition, the sentence-oriented word position describes… More >

M. Arun, J. Akhil, K. Noufal, Robin Baby, Darshitha Babu, M. Jose Prakash^*

Frontiers in Heat and Mass Transfer, Vol.8, pp. 1-9, 2017, DOI:10.5098/hmt.8.23

Abstract The supercritical turbulent flow of cryogenic methane flowing in a rocket engine cooing channel is numerically analysed by imposing constant heat flux at the bottom surface of the channel. The calculation scheme is validated by comparing the results obtained with experimental results reported in literature. The heat transfer coefficient is influenced by the strong variation in thermophysical properties of methane at super critical pressure. An increasing trend in the average value of Nusselt number is observed with aspect ratio. The efficacy of both Modified Jackson and Hall and Bishop empirical correlations in predicting Nusselt number is tested for cryogenic methane… More >

Kaprawi Sahim^* , Dewi Puspitasari^†

Frontiers in Heat and Mass Transfer, Vol.8, pp. 1-6, 2017, DOI:10.5098/hmt.8.16

Abstract One row of heated elliptical cylinder with aspect ratio 0.6 and 0.8 are studied to know the forced heat transfer performance. The transversal distance between the cylinders are changed and the heat transfer is observed. Numerical observation of the study is done by using finite volume method to solve the momentum equations in two dimension domains. The pressure term instead of velocity is obtained by measurement in a subsonic wind tunnel and then it is injected into the momentum equation. The results of the hydrodynamic calculation are then injected into the energy equation which is solved by the over relaxation… More >

Ammar Abdulkadhim^a,*, Azher Mouhsen Abed^a , Khaled Al-Farhany^b

Frontiers in Heat and Mass Transfer, Vol.11, pp. 1-7, 2018, DOI:10.5098/hmt.11.12

Abstract The conjugate natural convection heat transfer in a partially heated porous enclosure had been studied numerically. The governing dimensionless equations are solved using finite element method. Classical Darcy model have been used and the considering dimensionless parameters are modified Rayleigh number (10 ≤ Ra ≤ 10³), finite wall thickness (0.02 ≤ D ≤ 0.5), thermal conductivity ratio (0.1 ≤ K_r ≤ 10), and the aspect ratio (0.5 ≤ A≤ 10). The results are presented in terms of streamlines, isotherms and local and average Nusselt number. The results indicate that heat transfer can be enhanced by increasing the modified Rayleigh number,… More >

M. Arun^a,*, M. Jose Prakash^b

Frontiers in Heat and Mass Transfer, Vol.11, pp. 1-10, 2018, DOI:10.5098/hmt.11.9

Abstract Prediction of heat transfer deterioration in rocket engine coolant channels with supercritical flow is essential while designing high pressure rocket engines. Three-dimensional conjugate heat transfer of cryogenic methane in rectangular engine cooling channels at supercritical pressures with asymmetric heating imposed on the bottom channel surface is numerically investigated, focusing on the effects of key parameters such as aspect ratio, heat flux and coolant pressure. Due to the similarity of the coolant channel with that of an actual rocket engine, the results obtained herein are beneficial for the design and optimization of rocket engine cooling systems. Heat flux is varied from… More >

Shabir Hussain¹, Muhammad Ayoub², Yang Yu¹, Junaid Abdul Wahid¹, Akmal Khan³, Dietmar P. F. Moller⁴, Hou Weiyan^1,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5355-5377, 2023, DOI:10.32604/cmc.2023.036779

Abstract As the COVID-19 pandemic swept the globe, social media platforms became an essential source of information and communication for many. International students, particularly, turned to Twitter to express their struggles and hardships during this difficult time. To better understand the sentiments and experiences of these international students, we developed the Situational Aspect-Based Annotation and Classification (SABAC) text mining framework. This framework uses a three-layer approach, combining baseline Deep Learning (DL) models with Machine Learning (ML) models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset. Using the proposed aspect2class annotation algorithm, we… More >