Comparative Analysis of Traditional and Modern NLP Techniques on the CoLA Dataset: From POS Tagging to Large Language Models by Abdessamad Benlahbib, Achraf Boumhidi, Anass Fahfouh, Hamza Alami

“…The task of classifying linguistic acceptability, exemplified by the CoLA (Corpus of Linguistic Acceptability) dataset, poses unique challenges for natural language processing (NLP) models. These challenges include distinguishing between subtle grammatical errors, understanding complex syntactic structures, and detecting semantic inconsistencies, all of which make the task difficult even for human annotators. …”
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An NN Framework for Target Number Detection in FMCW Radar Systems via Hankelization: A Low-Dimensional Data Representation Perspective by Jung-Hwan Kim, Gyung-Eun Kim, Woong-Hee Lee

“…By integrating the mathematical processes of Hankelization and singular value extraction, we can perform input data manipulation for effective target number detection, resulting in constructing an efficient NN framework. …”
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Star Identification Algorithm Based on Dynamic Distance Ratio Matching by Ya Dai, Chenguang Shi, Liyan Ben, Hua Zhu, Rui Zhang, Shufan Wu, Sixiang Shan, Yu Xu, Wang Zhou

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Seepage area of the cold seep exhibits strong homogeneous selection on prokaryotic community assembly and supports high depth variability of both archaeal and bacterial communities by Xueling Xiong, Furun Li, Haokun Yang, Chunshan Li, Haiming Chen, Dan He, Qinglong L. Wu, Sijun Huang, Lijuan Ren

“…In this study, we comprehensively investigated the microbial depth variability and its underlying assembly process in the seepage and non-seepage areas of Haima Cold Seep. …”
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Remaining useful life prediction of Lithium-ion batteries based on data preprocessing and CNN-LSSVR algorithm by Ti Dong, Yiming Sun, Jia Liu, Qiang Gao, Chunrong Zhao, Wenjiong Cao

“…Targeting the thorny issues of limited battery historical cycle data and the impact of uncertainty in the data collection process in practical applications, this study proposes a Remaining useful life (RUL) prediction method for lithium-ion batteries based on the data preprocessing and the joint convolutional neural network (CNN)-least squares support vector regression (LSSVR) algorithm. …”
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Dataset collection for automatic generation of commit messages by Ivan A. Kosyanenko, Roman G. Bolbakov

“…In this study, a comprehensive approach was used, including data collection from popular GitHub repositories, preliminary data processing and filtering, as well as statistical analysis and natural language processing method (text vectorization). …”
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Short text automatic scoring system based on BERT-BiLSTM model by XIA Linzhong, YE Jianfeng, LUO De’an, GUAN Mingxiang, LIU Jun, CAO Xuemei

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Wheat policy, wheat yield and production in Ethiopia by Zewdie Habte Shikur

“…The purpose of this study was to evaluate the effects of wheat policy, and wheat processing industrial policy on wheat yield and production using Vector Error Correction (VEC) and Tobit models. …”
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Construction of advanced persistent threat attack detection model based on provenance graph and attention mechanism by Yuancheng LI, Hao LUO, Xinyu WANG, Jiexuan YUAN

“…In response to the difficulty of existing attack detection methods in dealing with advanced persistent threat (APT) with longer durations, complex and covert attack methods, a model for APT attack detection based on attention mechanisms and provenance graphs was proposed.Firstly, provenance graphs that described system behavior based on system audit logs were constructed.Then, an optimization algorithm was designed to reduce the scale of provenance graphs without sacrificing key semantics.Afterward, a deep neural network (DNN) was utilized to convert the original attack sequence into a semantically enhanced feature vector sequence.Finally, an APT attack detection model named DAGCN was designed.An attention mechanism was applied to the traceback graph sequence.By allocating different weights to different positions in the input sequence and performing weight calculations, sequence feature information of sustained attacks could be extracted over a longer period of time, which effectively identified malicious nodes and reconstructs the attack process.The proposed model outperforms existing models in terms of recognition accuracy and other metrics.Experimental results on public APT attack datasets show that, compared with existing APT attack detection models, the accuracy of the proposed model in APT attack detection reaches 93.18%.…”
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Quantum key distribution through quantum machine learning: a research review by Krupa Purohit, Ajay Kumar Vyas

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Sentiment Analysis of Tweets Using Supervised Machine Learning Techniques Based on Term Frequency by Deepti Aggarwal, Vikram Bali, Abhishek Agarwal, Kshitiz Poswal, Madhav Gupta, Abhishek Gupta

“…Sentiment analysis of the text uses Natural language processing, a machine learning technique to tell the orientation of opinion of a piece of text. …”
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Advanced sentiment analysis in online shopping: Implementing LSTM models analyzing E-commerce user sentiments by Lu Liyuan

“…The authors have used a large dataset of customer reviews from famous e-commerce websites, pre-processed for noise reduction and standardization of the input. …”
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Identification of Rice Varieties Using Machine Learning Algorithms by Murat Koklu, İlkay Çınar

“…The images were pre-processed using MATLAB software and prepared for feature extraction. …”
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Speech emotion recognition using long-term average spectrum by Huerta-Hernández Luis David, Meléndez-Acosta Nayeli Joaquinita, Troncoso-Romero David Ernesto, Ramírez-Pacheco Julio César, León-Borges Jose Antonio

“…Automatic speech emotion recognition has become an important research subject in the area of speech signal processing. The performance of classification algorithms depends on the features extracted from speech. …”
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Deep Learning Approach for Predicting Psychodiagnosis by Zouaoui Samia, Khamari Chahinez

“…Currently, there is a great need for effectively processing mental healthcare with the integration of artificial intelligence such as machine learning and deep learning. …”
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Automated Detection of Aberrant Episodes in Epileptic Conditions: Leveraging EEG and Machine Learning Algorithms by Uddipan Hazarika, Bidyut Bikash Borah, Soumik Roy, Manob Jyoti Saikia

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Assessing the Role of EEG Biosignal Preprocessing to Enhance Multiscale Fuzzy Entropy in Alzheimer’s Disease Detection by Pasquale Arpaia, Maria Cacciapuoti, Andrea Cataldo, Sabatina Criscuolo, Egidio De Benedetto, Antonio Masciullo, Marisa Pesola, Raissa Schiavoni

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Replicating Current Procedural Terminology code assignment of rhinology operative notes using machine learning by Christopher P. Cheng, Ryan Sicard, Dragan Vujovic, Vikram Vasan, Chris Choi, David K. Lerner, Alfred‐Marc Iloreta

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AUTOMATIC SCORING OF KNOWLEDGE GAINED AND SHARED THROUGH DISCUSSION FORUMS: BASED ON THE COMMUNITY OF INQUIRY MODEL by P.A.L. Nadeesha, T.A. Weerasinghe, W.R.N.S Abeyweera

“…The methodology integrated Random Forest (RF) classification with TF-IDF feature extraction and Support Vector Machine (SVM) classification with Word2Vec embedding. …”
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Advanced Color Edge Detection Using Clifford Algebra in Satellite Images by Uzair Aslam Bhatti, Zhou Ming-Quan, Qingsong Huo, Sajid Ali, Aamir Hussain, Yan Yuhuan, Zhaoyuan Yu, Linwang Yuan, Saqib Ali Nawaz

“…Quaternion-based Fourier transform is used to process red, green and blue (RGB) images separately in the vector field. …”
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