Integrating Bioengineering and Machine Learning: A Multi-Algorithm Approach to Enhance Agricultural Sustainability and Resource Efficiency by Senthil G.A., Prabha R., Asha R.M., Suganthi S.U., Sridevi S.

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Machine learning-based study of hardness in polypropylene/carbon nanotube and low-density polyethylene/carbon nanotube composites by Harshit Sharma, Gaurav Arora, Raj Kumar, Suman Debnath, Suchart Siengchin

“…(Random Forest, Support Vector Regression, K-Nearest Neighbors, Linear Regression, and Neural Network). …”
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IDENTIFICATION OF SIGNALS IN Multi-Static CROSS-CORRELATION PASSIVE RadarS by A. A. Dmitrenko, S. Y. Sedushev

“…The algorithm of stochastic signals processing in cross-correlation passive radars is synthesized. …”
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Acoustic Methods in Identifying Symptoms of Emotional States by Zuzanna PIĄTEK, Maciej KŁACZYŃSKI

“…After the parametrization process, data clustering was performed to allows for the grouping of feature vectors for speakers into greater collections which imitate specific emotional states. …”
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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

“…In this article, we compare a range of techniques, from traditional methods such as Part-of-Speech (POS) tagging and feature extraction methods like CountVectorizer with Term Frequency-Inverse Document Frequency (TF-IDF) and N-grams, to modern embeddings such as FastText and Embeddings from Language Models (ELMo), as well as deep learning architectures like transformers and Large Language Models (LLMs). …”
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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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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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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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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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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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Advanced sentiment analysis in online shopping: Implementing LSTM models analyzing E-commerce user sentiments by Lu Liyuan

“…This article elaborately contrasts long short-term memory (LSTM)-based models with traditional machine learning models, like support vector machines (SVM), random forest, and Naive Bayes classifiers. …”
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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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Effective dimensional reduction of complex systems based on tensor networks by Wout Merbis, Madelon Geurts, Clélia de Mulatier, Philippe Corboz

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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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