Clinical Applications of Artificial Intelligence in Teleorthodontics: A Scoping Review by Alessandro Polizzi, Sara Serra, Rosalia Leonardi, Gaetano Isola

“…One study explored an alternative system, StrojCHECK™, based on a decision tree algorithm, showing improved compliance with personalized feedback. …”
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HIV epidemic appraisals for assisting in the design of effective prevention programmes: shifting the paradigm back to basics. by Sharmistha Mishra, Sema K Sgaier, Laura H Thompson, Stephen Moses, B M Ramesh, Michel Alary, David Wilson, James F Blanchard

“…<h4>Methods and findings</h4>We compared outputs of the traditional methods in five countries for which results were published, and applied the numeric and MOT model to India and six districts within India. We discovered three limitations of the current methods for epidemic appraisal: (1) their results failed to identify the key behaviours that drive the epidemic; (2) they were difficult to apply to local epidemics with heterogeneity across district-level administrative units; and (3) the MOT model was highly sensitive to input parameters, many of which required extraction from non-regional sources. …”
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Comparative techno-economic analysis of grid-connected solar PV-battery and PV-fuel cell systems for educational institutions sustainable academic laboratories by Takele Ferede Agajie, Fuseini Seidu Ibrahim, Isaac Amoussou, Elsabet Ferede Agajie, Eriisa Yiga Paddy, Yayehyirad Ayalew Awoke, Wirnkar Basil Nsanyuy, Mohit Bajaj

“…Total net present cost (TNPC) was used for economic analysis, and mathematical modeling was created in order to apply metaheuristic optimization for system sizing. Techno-economic decision criteria were implemented using MATLAB. Three algorithms were used: Teaching–Learning-Based Optimization (TLBO), Water Cycle Algorithm (WCA), and Improved Grey Wolf Optimization (I-GWO). …”
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An in-depth exploration of supervised and semi-supervised learning on face recognition by Purnawansyah, Wibawa Aji Prasetya, Widiyaningtyas Triyanna, Haviluddin, Darwis Herdianti, Azis Huzain

“…This study aims to assess the effectiveness of various algorithms in the realms of supervised and semi-supervised learning applied to three multiclass facial image datasets: JAFFE, Georgia tech, and Yale. …”
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The impact of environmental variables on reed stands of the intermittent Lake Cerknica, Slovenia: 40 years of change by Nik Ojdanič, Alenka Gaberščik, Igor Zelnik, Aleksandra Golob

“…Decision tree-based data mining using the M5P algorithm effectively identified significant changes in MSAVI2. …”
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Development and validation of a machine learning model for prediction of cephalic dystocia by Yumei Huang, Xuerong Ran, Xueyan Wang, Defang Wu, Zheng Yao, Jinguo Zhai

“…The least absolute shrinkage and selection operator (LASSO) algorithm was used to select predictive factors, followed by the development of logistic regression, decision tree, and random forest machine learning models. …”
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Smart forest monitoring: A novel Internet of Things framework with shortest path routing for sustainable environmental management by Alireza Etaati, Mostafa Bastam, Ehsan Ataie

“…IoT facilitates proactive decision‐making for forest monitoring, control, and protection through advanced data analysis techniques, including AI algorithms. …”
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Detection of Epilepsy Disorder Using Spectrogram Images Generated From Brain EEG Signals by Venkatesh Bhandage, Tejeswar Pokuri, Devansh Desai, Andrew Jeyabose

“…The proposed approach is 3-fold. First, we propose an algorithm to generate spectrogram images from the EEG signals, and then, we adapt an efficient Convolutional Neural Network (CNN) model to classify the spectrogram images. …”
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Adaptive AI-enhanced computation offloading with machine learning for QoE optimization and energy-efficient mobile edge systems by Dinesh Kumar Nishad, Vandna Rani Verma, Pushkar Rajput, Sandeep Gupta, Anurag Dwivedi, Dharti Raj Shah

“…This paper introduces a novel Adaptive AI-enhanced offloading (AAEO) framework that uniquely integrates three complementary AI approaches: deep reinforcement learning for real-time decision-making, evolutionary algorithms for global optimization, and federated learning for distributed knowledge sharing. …”
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Applications of Raspberry Pi for Precision Agriculture—A Systematic Review by Astina Joice, Talha Tufaique, Humeera Tazeen, C. Igathinathane, Zhao Zhang, Craig Whippo, John Hendrickson, David Archer

“…This review consolidates details on Raspberry Pi versions, sensors, devices, algorithm deployment, and PA applications. A systematic literature review of three academic databases (Scopus, Web of Science, IEEE <i>Xplore</i>) yielded 84 (as of 22 November 2024) articles based on four research questions and screening criteria (exclusion and inclusion). …”
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A Wind Power Density Forecasting Model Based on RF-DBO-VMD Feature Selection and BiGRU Optimized by the Attention Mechanism by Bixiong Luo, Peng Zuo, Lijun Zhu, Wei Hua

“…The proposed model consists of three main stages. First, critical physical features relevant to WPD are identified using random forest (RF), effectively eliminating data redundancy and enhancing prediction efficiency. …”
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Multi-Domain Controversial Text Detection Based on a Machine Learning and Deep Learning Stacked Ensemble by Jiadi Liu, Zhuodong Liu, Qiaoqi Li, Weihao Kong, Xiangyu Li

“…Furthermore, we systematically compare three hyperparameter optimization algorithms, including the sparrow search algorithm (SSA), particle swarm optimization (PSO), and Bayesian optimization (BO). …”
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Road Pothole Recognition and Size Measurement Based on the Fusion of Camera and LiDAR by Yongxiang Cai, Mingxing Deng, Xin Xu, Wei Wang, Xiaowei Xu

“…In intelligent driving systems, accurate detection and measurement of the three-dimensional (3D) dimensions of road potholes are essential for optimizing decision-making processes, including deceleration and obstacle avoidance. …”
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Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms by Ayesha Siddika, Momotaz Begum, Fahmid Al Farid, Jia Uddin, Hezerul Abdul Karim

“…This research addresses this need by combining advanced techniques (ensemble techniques) with seventeen machine learning algorithms for predicting software defects, categorised into three types: semi-supervised, self-supervised, and supervised. …”
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Machine learning-driven insights into phase prediction for high entropy alloys by Reliance Jain, Sandeep Jain, Sheetal Kumar Dewangan, Lokesh Kumar Boriwal, Sumanta Samal

“…Herein, a method of designing substitutional high entropy alloys with optimization of input features and predict their phase formation, using different ML algorithms are proposed. The ML models such as multi layer precreptron MLP, Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), KNN, XGB nad SVM Classifier algorithm were used for the identifying the phase of HEAs. …”
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Enhancing Daylight and Energy Efficiency in Hot Climate Regions with a Perforated Shading System Using a Hybrid Approach Considering Different Case Studies by Basma Gaber, Changhong Zhan, Xueying Han, Mohamed Omar, Guanghao Li

“…A hybrid approach integrating parametric modeling, machine learning, multi-criteria decision-making (MCDM), and genetic algorithm (GA) is used to optimize the design incorporating architects’ preferences. …”
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Transformer attention fusion for fine grained medical image classification by Danyal Badar, Junaid Abbas, Raed Alsini, Tahir Abbas, Wang ChengLiang, Ali Daud

“…It extracts features at three different resolutions (12 × 12, 24 × 24, 48 × 48), allowing it to detect subtle local features and global elements. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…For regression and classification, deep neural network (DNN) from deep learning algorithms and support vector machine (SVM), decision trees (DTs), k-nearest neighbor (KNN), random forest (RF), logistic regression (LR), and extreme gradient boosting (XGBoost) algorithms from machine learning algorithms were used. …”
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Cryptographic hardness assumptions identification based on discrete wavelet transform by Ke Yuan, Yu Du, Yizheng Liu, Rongjin Feng, Bowen Xu, Gaojuan Fan, Chunfu Jia

“…A hybrid feature selection algorithm is proposed to filter out irrelevant features, which combines wrapper and filter methods. …”
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Ensemble Machine Learning Classifiers Combining CT Radiomics and Clinical-Radiological Features for Preoperative Prediction of Pathological Invasiveness in Lung Adenocarcinoma Pres... by Yunhua Li BS, Jianbang Ding MS, Kun Wu MS, Wanyin Qi BS, Shanyue Lin BS, Gangwen Chen BS, Zhichao Zuo PhD

“…Methods We retrospectively analyzed 344 patients with pathologically confirmed lung adenocarcinoma presenting as PSNs across three medical centers. Following random allocation into training (n = 240) and validation (n = 104) sets (7:3 ratio), we extracted 1239 quantitative radiomic features from preoperative thin-section CT scans. …”
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