The potential of short-wave infrared hyperspectral imaging and deep learning for dietary assessment: a prototype on predicting closed sandwiches fillings by Esther Kok, Aneesh Chauhan, Michele Tufano, Edith Feskens, Guido Camps

“…We explored the applicability of hyperspectral imaging and machine learning for dietary assessment of home-prepared meals, by building a proof-of-concept, which automatically detects food ingredients inside closed sandwiches.MethodsIndividual spectra were selected from 24 hyperspectral images of assembled closed sandwiches, measured in a spectral range of 1116.14 nm to 1670.62 nm over 108 bands, pre-processed with Standard Normal Variate filtering, derivatives, and subsampling, and fed into multiple algorithms, among which PLS-DA, multiple classifiers, and a simple neural network.ResultsThe resulting best performing models had an accuracy score of ~80% for predicting type of bread, ~60% for butter, and ~ 28% for filling type. …”
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Matlab/Simulink simulation model of photo-diesel power supply system with intelligent control by B. V. Lukutin, D. I. Muravyev

“…As a result of experiments with changing input conditions, i.e. annual changes in insolation and temperature at different latitudes, the authors justify technical, economic, and environmental criteria for the effectiveness of decision-making and recommendations for the design and operation of PDPS power plants. Intelligent algorithms for effective control of PV-diesel power systems based on DC are developed and suggested.…”
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Microscopic Defect Detection on Aircraft Engine Blades via Improved YOLOv8 by Yujie Jiang, Ping Li, Bing Lin, Yingying Wang, Tian Li, Hui Xue, Weidong Liu, Zaihu Han, Dan Wang, Junlei Tang

“…Our approach significantly surpasses the performance of contemporary target detection algorithms, thereby offering a robust solution for microscopic defect detection in aeroengines. …”
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Applying Hybrid Deep Learning Models to Assess Upper Limb Rehabilitation by Sheng Miao, Zitong Liu, Dezhen Wang, Xiang Shen, Nana Shen

“…In order to solve these problems, this study presents a new method that utilizes deep learning algorithms to recognize rehabilitation movements and thus evaluate rehabilitation effects. …”
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A hybrid framework for colorectal cancer detection and U-Net segmentation using polynetDWTCADx by Akella S Narasimha Raju, K Venkatesh, Makineedi Rajababu, Ranjith Kumar Gatla, Marwa M. Eid, Enas Ali, Nataliia Titova, Ahmed B. Abou Sharaf

“…We can also employ the semantic segmentation algorithms of the U-Net architecture to accurately identify and segment cancerous colorectal regions. …”
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Stem and Leaf Segmentation and Phenotypic Parameter Extraction of Tomato Seedlings Based on 3D Point by Xuemei Liang, Wenbo Yu, Li Qin, Jianfeng Wang, Peng Jia, Qi Liu, Xiaoyu Lei, Minglai Yang

“…The RANSAC, region-growing, and greedy projection triangulation algorithms were employed to extract phenotypic parameters such as plant height, stem thickness, leaf area, and leaf inclination angle. …”
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Benchmark dataset on feeding intensity of the pearl gentian grouper(Epinephelus fuscoguttatus♀×E. lanceolatus♂) by Haijing Qin, Yunchen Tian, Jianing Quan, Xueqi Cong, Qingfei Li, Jinzhu Sui

“…In order to solve these problems, this study constructs a benchmark dataset of the feeding intensity of pearl gentian groupers in a factory circulating water environment, which is divided into feeding fish groups and fish aggregation areas by training Unet semantic segmentation network and compares standard clustering algorithms through clustering evaluation indexes to maximally select the optimal clustering method and the number of clusters that are suitable for this paper's dataset. …”
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Integrated Solution Combining Low-Frequency Forced Oscillation Technique and Continuous Equivital Sensor Monitoring for Assessment of Non-Invasive Ambulatory Respiratory Mechanics by Ghada Ben Othman, Amani R. Ynineb, Erhan Yumuk, Hamed Farbakhsh, Cristina Muresan, Isabela Roxana Birs, Alexandra De Raeve, Cosmin Copot, Clara M. Ionescu, Dana Copot

“…The best-fitting fractional-order models for impedance data were identified using genetic algorithms. This study also explores the correlation between impedance model parameters and EQV data, discussing the potential of AI tools for forecasting respiratory properties. …”
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A Lightweight Human Activity Recognition Method for Ultra-wideband Radar Based on Spatiotemporal Features of Point Clouds by Yongkun SONG, Tianxing YAN, Ke ZHANG, Xian LIU, Yongpeng DAI, Tian JIN

“…To address the issues of high computational complexity and extensive network parameters in existing action recognition algorithms, this study proposes an efficient and lightweight human activity recognition method using UWB radar based on spatiotemporal point clouds. …”
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A Denoising Based Autoassociative Model for Robust Sensor Monitoring in Nuclear Power Plants by Ahmad Shaheryar, Xu-Cheng Yin, Hong-Wei Hao, Hazrat Ali, Khalid Iqbal

“…Apart from these regularization heuristics, traditional error gradient based supervised learning algorithms for multilayered AANN models are highly susceptible of being trapped in local optimum. …”
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Atmospheric Turbulence Intensity Image Acquisition Method Based on Convolutional Neural Network by Yuan Mu, Liangping Zhou, Shiyong Shao, Zhiqiang Wang, Pei Tang, Zhiyuan Hu, Liwen Ye

“…An algorithmic model of a neural network with channel attention and spatial attention (CASANet) is proposed to estimate the value of atmospheric coherence length, which in turn provides a quantitative description of atmospheric turbulence intensity. …”
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Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis by Zhi-xiang Zhang, Yi-lin Cao, Chao Chen, Lin-yuan Wen, Yi-ding Ma, Bo-zhou Wang, Ying-zhe Liu

“…The modeling was performed based on a dataset consisting of 885 various compounds using linear and nonlinear algorithms. The tree-based models established demonstrated acceptable predictive abilities, yielding a low mean absolute error (MAE) of 31°C. …”
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Solving the fully fuzzy multi-choice linear programming model by Zahra Arami, Maryam Arabameri, Hassan Mishmast Nehi

“…In general, the resulting algorithms are simple and very inexpensive to implement, and they are more efficient than those of previous studies.Originality/Value: In this article, all parameters and coefficients of the problem are triangular fuzzy numbers, and the right side of the problem's constraints are the fuzzy multi-choice parameters. …”
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Application of edge computing technology in smart grid data security by Zhuo Cheng, Jiangxin Li, Jianjun Zhang, Chen Wang, Hui Wang, Juyin Wu

“…The experimental results indicate that: The total running time required for executing proxy authorization and verification, proxy key generation, signature and decryption algorithms in this scheme is 5.617 ms, with a ciphertext length of 80 Bytes. …”
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Predicting the hub interactome of COVID-19 and oral squamous cell carcinoma: uncovering ALDH-mediated Wnt/β-catenin pathway activation via salivary inflammatory proteins by Pradeep Kumar Yadalam, Deepavalli Arumuganainar, Prabhu Manickam Natarajan, Carlos M. Ardila

“…Hub proteins were identified using Cytoscape and Cytohubba, and machine learning algorithms including naïve Bayes, neural networks, gradient boosting, and random forest were used to predict hub genes. …”
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Optimizing Parkinson’s Disease Prediction: A Comparative Analysis of Data Aggregation Methods Using Multiple Voice Recordings via an Automated Artificial Intelligence Pipeline by Zhengxiao Yang, Hao Zhou, Sudesh Srivastav, Jeffrey G. Shaffer, Kuukua E. Abraham, Samuel M. Naandam, Samuel Kakraba

“…We developed a customized AI pipeline that incorporates twelve machine learning algorithms along with the four aggregation methods to detect Parkinson’s disease (PD) using multiple voice recordings from individuals available in the UCI Machine Learning Repository, which includes 756 voice recordings from 188 PD patients and 64 healthy individuals. …”
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Bearing Response Prediction in Hydrothermal Aged Carbon Fiber Reinforced Epoxy Composite Joints Using Machine Learning Techniques by Mohit Kumar, Govind Vashishtha, Babita Dhiman, Sumika Chauhan

“…In this research, an innovative support vector regression approach is present that leverages machine learning algorithms to forecast the bearing response of CFREC joints after undergoing hydrothermal aging. …”
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Interpretable machine learning modeling of temperature rise in a medium voltage switchgear using multiphysics CFD analysis by Mahmood Matin, Amir Dehghanian, Amir Hossein Zeinaddini, Hossein Darijani

“…Artificial intelligence (AI) algorithms have gained attention in various engineering fields to address similar issues. …”
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Technical architecture and strategies for intelligent construction of coal preparation plant by WANG Meijun, TAN Zhanglu, LÜ Hanbing, GUI Yudian

“…Departing from the fundamental purpose and motivation of digital transformation of coal preparation plant, we 1) discuss the technical objectives and major tasks of intelligent construction of coal preparation plant based on the underlying logic of intelligent construction of coal preparation plant; 2) propose the overall technical architecture of CNSASSM for the intelligent construction of coal preparation plant based on layered architecture, with five core competence requirements: "thorough perception, deep interconnection, autonomous learning, intelligent application, and global coordination"; 3) point out the technical pathway for intelligent construction of coal preparation plant and the major tasks to be completed at each phase based on capability maturity, including the integration of standard coal preparation data at the primary phase, the research and development of business optimization algorithms at the intermediate phase, and the empowerment of artificial intelligence model on coal preparation at the advanced phase; 4) generalize a 96-word guideline of technical strategies for intelligent construction of coal preparation plant based on patterns of complex system development, so as to provide reference for the technical realization of intelligent construction of coal preparation plant from the perspective of top-level design.…”
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Estilometría TIP: enhanced text analysis tool with customisable metrics for Spanish texts by Francisco J. Carreras-Riudavets, Zenón J. Hernández-Figueroa

“…Lexicon TIP draws on a comprehensive database of more than 320,000 lemmas and 8 million inflected forms, accounting for variations in number, gender, superlatives, diminutives, augmentatives, derogatory terms, and verb conjugations. Two key algorithms enhance this functionality: prefix detection, which accurately identifies prefixed words (e.g. …”
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