AI Methods for New Psychoactive Substance (NPS) Design and Analysis by Enrico Greco

“…Special emphasis is placed on mass spectrometry (MS)-based techniques, where AI algorithms (e.g., for spectral prediction and pattern recognition) are revolutionizing the detection and characterization of unknown NPSs. …”
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Rural Landscape Characters and Spatial Correlation Mechanism in the Tiaoxi River – Canal Basin in Zhejiang Province by Lin ZHANG, You ZUO, Binyi LIU

“…Future research will construct a spatio-temporal dynamic dataset of canal heritage landscapes, which aims to enhance the fine-grained character extraction and type classification accuracy of machine learning algorithm models for rural landscapes. …”
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Rekayasa Perangkat Lunak Aplikasi Presensi Mobile Menggunakan Metode Deep Learning by Ragil Setiawan, Nurcahya Pradana Taufik Prakisya, Rosihan Ariyuana

“…Seeing the ongoing development of facial pattern recognition algorithms such as Viola Jones, Backpropagation, this research uses the MobileFaceNet  mobile CNN model which is currently popular to be implemented in the mobile-based facial recognition presence application at the Information and Computer Engineering Education (PTIK) FKIP UNS. …”
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Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…Specifically, ANN models excel at detecting subtle, complex patterns that reflect battery health and performance, crucial for accurate SOC estimation. …”
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Speculation resource provisioning in high-performance computing by Leena Sri, Balaji Narayanan

“…In this paper, we propose an automated resource provisioning algorithm, Speculation resource provisioning , prompting load balancing through speculative approach in resource provisioning. …”
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EBOC: Ensemble-Based Ordinal Classification in Transportation by Pelin Yıldırım, Ulaş K. Birant, Derya Birant

“…Learning the latent patterns of historical data in an efficient way to model the behaviour of a system is a major need for making right decisions. …”
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Classification of patients with lithium-treated bipolar disorder based on gene expression: Dirichlet Bayesian network model by Nader Salari, Sahar Souri Pilangorgi, Afshin Almasi, Soodeh Shahsavari, Andrew J. Fournier

“…Essential variables were selected using partial least squares regression to analyze and classify the data. The plaid algorithm was employed to identify identical patterns and biclusters within the gene expression data. …”
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A Unified Approach to Image Recognition and Cryptography via Flexible Weak Inverse Property Quasigroups by Mohammad Mazyad Hazzazi, Muhammad Nadeem, Muhammad Kamran, Muhammad Arshad, Samuel Asefa Fufa

“…It also addresses the implementation of polynomial functions PTt in image and pattern detection, with emphasis on feature extraction and edge detection. …”
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Adaptation of k-means to automated forecasting of poorly structured time series of economic dynamics by Dunskaia Lada, Popova Elena

“…Data mining methods used in machine learning or deep learning allow to take into account complex patterns and nonlinear dependencies in the data. …”
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Tree networks of real-world data: Analysis of efficiency and spatiotemporal scales by Davide Cipollini, Lambert Schomaker

“…Using an algorithm that creates and searches trees of real-world patterns, our work stands at the intersection of statistical physics, machine learning, and network theory. …”
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A Crime Data Analysis of Prediction Based on Classification Approaches by Fatima Shaker Hussain, Abbas Fadhil Aljuboori

“…Various machine learning algorithms on the dataset of Boston city crime are Decision Tree, Naïve Bayes and Logistic Regression classifiers have been used here to predict the type of crime that happens in the area. …”
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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…The main objective of the proposed optimal weighting-based CNN-LSTM-SVM (OCLS) hybrid classifier is to simultaneously leverage the unique advantages of CNN in feature extraction from input signals, LSTM in modeling the sequential patterns of signals, SVM in classifying regular patterns, and especially the proposed weighting algorithm to optimally integrate the outputs of these components. …”
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Wavelet filterbank‐based EEG rhythm‐specific spatial features for covert speech classification by Sukanya Biswas, Rohit Sinha

“…With the motivation of deriving more discriminative features, each channel data has been decomposed into distinct bands focussing on the five basic EEG rhythms using the discrete wavelet transform (DWT)‐based signal decomposition algorithm. Following that, for each band, the multi‐class common spatial pattern (CSP) features are computed using joint approximate diagonalisation. …”
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BIMLP Model Based on Deep Learning for Predicting Electrical Load Demand by Somayeh Talebzadeh, Reza Radfar, Abbas Toloei Ashlaghi

“…However, the complexities of demand patterns, weather variability, and socioeconomic factors make it challenging to forecast demand with high accuracy. …”
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ML-based Plant Stress Detection from IoT-sensed Reduced Electromes by Marcos De Oliveira Jr, Gregory Sedrez, Gerson Geraldo H. Cavalheiro

“…The recognition of patterns in the electrical activities of plants (electromes, in time series format) has gained prominence in recent years. …”
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Research progress in predicting the conversion from mild cognitive impairment to Alzheimer’s disease via multimodal MRI and artificial intelligence by Min Ai, Yu Liu, Dan Liu, Chengxi Yan, Xia Wang, Xun Chen

“…Artificial intelligence (AI) methods based on deep learning and machine learning, with their powerful data processing and pattern recognition capabilities, have shown great potential in mining the features of multimodal MRI data and constructing prediction models for MCI conversion. …”
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A novel multi-agent dynamic portfolio optimization learning system based on hierarchical deep reinforcement learning by Ruoyu Sun, Yue Xi, Angelos Stefanidis, Zhengyong Jiang, Jionglong Su

“…In each back-test experiment, the proposed learning system is compared to sixteen traditional strategies and ten strategies based on machine learning algorithms in the performance of profitability and risk control ability. …”
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A Transformer-Based Approach for Efficient Geometric Feature Extraction from Vector Shape Data by Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang, Junkui Xu

“…Traditional methods rely on different machine learning algorithms tailored to specific types of line and polygon elements, limiting their general applicability. …”
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Toward Hand Gesture Recognition Using a Channel-Wise Cumulative Spike Train Image-Driven Model by Yang Yu, Zeyu Zhou, Yang Xu, Chen Chen, Weichao Guo, Xinjun Sheng

“…Recognizing hand gestures from neural control signals is essential for natural human–machine interaction, which is extensively applied to prosthesis control and rehabilitation. …”
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Anoikis in hepatocellular carcinoma: genetic alterations and immune microenvironment insights from single-cell and computational analysis by Bing Zhou, Jialing Zhang, Mingfeng Guo

“…Cox regression and 101 machine learning algorithms were employed to identify prognostic genes and construct a risk model, which was validated using TCGA, ICGC, and GEO datasets. …”
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