Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks by Hussein A. M. Hussein, Sharafiz B. Abdul Rahim, Faizal B. Mustapha, Prajindra S. Krishnan, Nawal Aswan B. Abdul Jalil

“…The subsequent data processing stage involved the application of an ANN algorithm for pattern recognition to analyze and classify the acquired data, identifying patterns associated with the replicated fault conditions. …”
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Deep Learning-Emerged Grid Cells-Based Bio-Inspired Navigation in Robotics by Arturs Simkuns, Rodions Saltanovs, Maksims Ivanovs, Roberts Kadikis

“…This paper first provides an overview of recent research on grid cell-based navigation in robotics, focusing on deep learning models and algorithms capable of handling uncertainty and dynamic environments. …”
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Facilitating Robot Learning in Virtual Environments: A Deep Reinforcement Learning Framework by Algirdas Laukaitis, Andrej Šareiko, Dalius Mažeika

“…This study introduces an open-source framework and a novel pattern-based method designed to facilitate the exploration of robot learning capabilities through reinforcement learning algorithms in specialized virtual testing environments built on Webots. …”
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Interpretation of myocardial perfusion SPECT with attenuation correction. Part 2 by A. A. Ansheles, V. В. Sergienko

“…The diffuse irregularity of perfusion radiopharmaceutical tracer accumulation in the application of the current reconstruction algorithms stood out in a separate pattern as a sign of microcirculatory disturbances. …”
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Development characteristics and intelligent identification method of natural fractures: A case study of the Upper Triassic Xujiahe Formation in the western Sichuan Depression, Sich... by LI Wei, WANG Min, XIAO Dianshi, JIN Hui, SHAO Haoming, CUI Junfeng, JIA Yidong, ZHANG Zeyuan, LI Ming

“…To evaluate the “sweet spot” enrichment area of the Xujiahe Formation gas reservoir, fracture development characteristics are identified and an effective fracture recognition method is established based on core observation, logging data, and intelligent algorithms. The research suggests that structural fractures, diagenetic fractures, and overpressure fractures all develop in the study area. …”
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Predictive Analytics in Finance Using the Arima Model. Application for Bucharest Stock Exchange Financial Companies Closing Prices by Spulbar Cristi, Ene Cezar Cătălin

“…Moreover, the selected model is part of the time series analysis under prediction algorithms, the purpose of the research being to predict the prices of the selected shares. …”
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GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data by Muhammad Iqbal, Arshad Iqbal, Humaira Ayub, Maqbool Khan, Naveed Ahmad, Yasir Javed, Mohammed Ali Alshara

“…The findings highlight the capacity of machine learning methods to reveal complex patterns in NGS data, therefore improving the proposed comprehension of the causes of congenital glaucoma. …”
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Impact Analysis of BIM on Power Substation Project Costs: Techno-Economic Data Evidence from China by Ding Liu, Lizhong Qi, Yi Sun, Jingguo Rong, Su Zhang, Guangze Yu

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Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network by Aythem Khairi Kareem, Mohammed M. AL-Ani, Ahmed Adil Nafea

“…Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. …”
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Correlation Between Depression-Associated Genes and Cancer Types: Predicting Cancer Based on Mutation Frequencies by Fernando Patricio Carranco-Avila, Clayanela Zambrano-Caicedo, Jonathan Javier Loor-Duque, Ariana Deyaneira Jimenez-Narvaez, Ivan Galo Reyes-Chacon, Paulina Vizcaino, Isidro Rafael Amaro Martin, Manuel Eugenio Morocho-Cayamcela

“…The analysis employed advanced methodologies, including HJ biplot K-means and DBSCAN clustering algorithms for pattern grouping in 2D. This process generated a dataset, enabling the training and testing of machine learning and deep learning classification models. …”
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Optimizing Personalized and Context-Aware Recommendations in Pervasive Computing Environments by A. C. Kaladevi, V. Vinoth Kumar, T. R. Mahesh, Suresh Guluwadi

“…Abstract The researchers in the current era provided many new recommendation methodologies. …”
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Artificial Intelligence for Smoking Detection: A Review of Machine Learning and Deep Learning Approaches by Mohammed Al-Hayali, Fawziya Ramo

“…Furthermore, this paper will provide data on the results of indoor and outdoor smoker detection using smart algorithms, contributing valuable insights for future research in this area.…”
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An Investigation of Suicidal Ideation from Social Media Using Machine Learning Approach by Soumyabrata Saha, Suparna Dasgupta, Adnan Anam, Rahul Saha, Sudarshan Nath, Surajit Dutta

“…The machine learning algorithms showed high accuracy, precision, recall, and F1-score in detecting suicide patterns on social media data whereas SVM has the highest performance with an accuracy of 0.886.       …”
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<b>The investigation of commonalities in human brain semantic representations across people and across languages</b><br> by Augusto Buchweitz

“…By using Machine Learning techniques to analyze neuroimaging data, researchers have been able to find stable patterns of brain activity across different people. …”
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A systematic review on sleep stage classification and sleep disorder detection using artificial intelligence by Tayab Uddin Wara, Ababil Hossain Fahad, Adri Shankar Das, Md Mehedi Hasan Shawon

“…Brain waves are the most commonly used body signals for studying sleep patterns and disorders. Almost 36 % of the research exclusively used brain activity signals, and 80 % combined them with other body parameters in sleep staging. …”
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Introduction to Computational Creativity by Anna Longo, ChatGPT

“…By deconstructing the cognitive processes involved in human creativity, researchers can design algorithms that simulate these processes. …”
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Minangkabau Language Stemming: A New Approach with Modified Enhanced Confix Stripping by Fadhli Almu'iini Ahda, Aji Prasetya Wibawa, Didik Dwi Prasetya, Danang Arbian Sulistyo, Andrew Nafalski

“…The employed method assesses the efficacy of stemming, which differs according to language. Complex affixation patterns in Indonesian and regional languages such as Minangkabau pose considerable difficulties for traditional algorithms. …”
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Hurst exponent based approach for influence maximization in social networks by Bhawna Saxena, Vikas Saxena

“…For assessing the self-similarity trend in a node’s activity pattern, Hurst exponent (H) has been computed. Based on the results achieved, proposed algorithm has been found to perform better than other state-of-art algorithms for initial adopter identification.…”
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Frequency Characteristics of Rhythm Non-Assimilation in Canine Ventricular Fibrillation by M. I. Guryanov

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A fear detection method based on palpebral fissure by Rawinan Praditsangthong, Bhattarasiri Slakkham, Pattarasinee Bhattarakosol

“…These changing faces can reflect the emotional states that are used to identify a normal or an abnormal behaviour. This research aims to study the patterns in human faces and identify the areas of interest (AOI), which is called Facial Landmark Detection (FLD). …”
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