Design and Prototype of a Solar Array Malfunction Identification System. by Wabuyi, Richard

“…SAMIS integrates cutting-edge monitoring technologies and data analysis algorithms to detect, diagnose, and report issues within solar arrays. …”
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Design and Prototype of a Local Relay Fault Detection System for Three Phase Power Lines. by Lutaama, Samuel

“…The methodology covers system architecture, fault detection algorithms, and the prototype development process, which integrates sensors and a user interface for monitoring. …”
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Ekyeyo Mobile Application by Nkuba, Blair, Kansiime, Daniel

“…The app incorporates advanced search algorithms, tailored job recommendations, and streamlined candidate screening to improve job-matching accuracy. …”
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Building occupancy type classification and uncertainty estimation using machine learning and open data by Tom Narock, J. Michael Johnson, Justin Singh-Mohudpur, Arash Modaresi Rad

“…We demonstrate how existing open-source datasets can be spatially integrated and subsequently used as training for machine learning (ML) models to predict building occupancy type, a major component needed for disaster preparedness and decision -making. Multiple ML algorithms are compared. We address strategies to handle significant class imbalance and introduce Bayesian neural networks to handle prediction uncertainty. …”
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Quantum Circuit for Imputation of Missing Data by Claudio Sanavio, Simone Tibaldi, Edoardo Tignone, Elisa Ercolessi

“…We train and test the performance of the algorithms on a series of datasets finding good convergence of the results. …”
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On Oscillations and Noise in Multicomponent Adsorption: The Nature of Multiple Stationary States by Olga M. Jakšić, Zoran Jakšić, Milena B. Rašljić, Ljiljana Z. Kolar-Anić

“…We address perturbations around the steady state analytically, first in a classical way, then by introducing Langevin forces and analyzing the reaction flux and cross-correlations, then by applying the stochastic chemical master equation approach, and finally, numerically, by using stochastic simulation algorithms. Our results show that stationary states in this model are stable nodes. …”
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Computer Vision with Error Estimation for Reduced Order Modeling of Macroscopic Mechanical Tests by Franck Nguyen, Selim M. Barhli, Daniel Pino Muñoz, David Ryckelynck

“…This article details simple algorithmic choices that allowed a realistic mechanical modeling via computer vision.…”
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3D convolutional deep learning for nonlinear estimation of body composition from whole body morphology by Isaac Y. Tian, Jason Liu, Michael C. Wong, Nisa N. Kelly, Yong E. Liu, Andrea K. Garber, Steven B. Heymsfield, Brian Curless, John A. Shepherd

“…Abstract Body composition prediction from 3D optical imagery has previously been studied with linear algorithms. In this study, we present a novel application of deep 3D convolutional graph networks and nonlinear Gaussian process regression for human body shape parameterization and body composition estimation. …”
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Tracking solid electrolyte interphase dynamics using operando fibre-optic infra-red spectroscopy and multivariate curve regression by Cédric Leau, Yu Wang, Charlotte Gervillié-Mouravieff, Steven T Boles, Xiang-Hua Zhang, Simon Coudray, Catherine Boussard-Plédel, Jean-Marie Tarascon

“…This work employs chalcogenide fibres embedded in negative electrode materials for operando Infra-red Fibre-optic Evanescent Wave Spectroscopy (IR-FEWS), combined with Multivariate Curve Resolution by Alternating Least Squares (MCR-ALS) algorithms for spectra analysis. By establishing molecular fingerprints that can be used to identify reaction products, IR-FEWS combined with MCR-ALS enables improved understanding of SEI evolution during cell formation with notable differences stemming from electrolyte or anode material. …”
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Biomimic models for in vitro glycemic index: Scope of sensor integration and artificial intelligence by Mohammed Salman C K, Muskan Beura, Archana Singh, Anil Dahuja, Vinayak B. Kamble, Rajendra P. Shukla, Sijo Joseph Thandapilly, Veda Krishnan

“…Non-enzymatic sensors offer superior stability and repeatability in complex matrices, enabling real-time glucose quantification across multiple timepoints without enzyme degradation constraints. Machine learning algorithms, both supervised and unsupervised, enhance predictive accuracy by elucidating complex relationships within digestion data. …”
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Integration of clinical, pathological, radiological, and transcriptomic data improves prediction for first-line immunotherapy outcome in metastatic non-small cell lung cancer by Nicolas Captier, Marvin Lerousseau, Fanny Orlhac, Narinée Hovhannisyan-Baghdasarian, Marie Luporsi, Erwin Woff, Sarah Lagha, Paulette Salamoun Feghali, Christine Lonjou, Clément Beaulaton, Andrei Zinovyev, Hélène Salmon, Thomas Walter, Irène Buvat, Nicolas Girard, Emmanuel Barillot

“…In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information. …”
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Smart HVAC Control in IoT: Energy Consumption Minimization with User Comfort Constraints by Jordi Serra, David Pubill, Angelos Antonopoulos, Christos Verikoukis

“…In particular, the user may decide remotely the temperature of comfort, while the temperature and energy consumption information is sent through Internet and displayed at the end user’s device. The proposed algorithms have been implemented in a real testbed, highlighting the potential gains that can be achieved in terms of both energy and cost.…”
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Bus Priority Signal Control Considering Delays of Passengers and Pedestrians of Adjacent Intersections by Jiali Li, Yugang Liu, Hongtai Yang, Bin Chen

“…Secondly, models with the goal of maximizing the reduced total delays are established. Thirdly, three algorithms are used to solve the problem to obtain the optimal signal timing adjustment scheme at upstream intersections. …”
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Intelligent Sensor for Measurement Systems with Sinusoidal Excitation Response by U. A. Mikitsevich, A. I. Svistun, A. V. Samarina, K. U. Pantsialeyeu, A. L. Zharin

“…The aim of the work was to develop the optimal architecture and algorithms for the operation of intelligent sensors intended for use in measuring systems operating according to the sinusoidal excitation – response scheme.This paper describes the approach proposed by the authors to the construction of intelligent sensors based on modern microcontrollers, the distinctive feature of which is the continuous generation of sinusoidal excitation and reading responses in the background, as well as setting the readiness flags for data processing in the main process of the microprocessor, which ensures uninterrupted execution of background processes, the main of which is the generation of a sinusoidal excitatory action.This approach has been tested in the development of charge-sensitive surface mapping systems, such as the Kelvin probe based on a vibrating capacitor, and the surface photo voltage probe for the case of semiconductors.…”
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Artificial intelligence in kidney transplantation: a 30-year bibliometric analysis of research trends, innovations, and future directions by Ying Jia He, Pin Lin Liu, Tao Wei, Tao Liu, Yi Fei Li, Jing Yang, Wen Xing Fan

“…Key research themes include AI-driven advancements in donor matching, deep learning for post-transplant monitoring, and machine learning algorithms for personalized immunosuppressive therapies. …”
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A Survey of Deep Learning Techniques for Arabic Aspect-Based Sentiment Analysis by Dalal Alqusair, Mounira Taileb, and Hassanin Al-Barhamtoshy

“…In addition to ascertaining potential future directions that would encourage researchers to contribute to Arabic ABSA studies and generate more effective algorithms.…”
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Low-threshold dual-polarization electro-optic nonlinear activation functions by Tao Jin, Jian Lin, Pengjun Wang, Qiang Fu, Yuhan Sun, Yi Zou, Shixun Dai, Weiwei Chen, Jun Li, Tingge Dai, Jianyi Yang

“…This scheme relies on a structure composed of an optical power splitter and a thermo-optic modulator based on Mach–Zehnder interferometer, which are optimized by using direct binary search and particle swarm optimization algorithms. When a fixed proportion of the input optical signal is transformed into the electrical signal and the remaining input optical signal is modulated by using the thermo-optic effect, the rectified linear unit activation function with a low-threshold power of 0.2 mW for transverse-electric polarization and the Gaussian activation function with a low-threshold power of 0.1 mW for transverse-magnetic polarization can be measured separately. …”
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Automating airborne pollen classification: Identifying and interpreting hard samples for classifiers by Manuel Milling, Simon D.N. Rampp, Andreas Triantafyllopoulos, Maria P. Plaza, Jens O. Brunner, Claudia Traidl-Hoffmann, Björn W. Schuller, Athanasios Damialis

“…To shed some light on this issue, we conducted a sample-level difficulty analysis based on the likelihood for one of the largest automatically-generated datasets of pollen grains on microscopy images and investigated the reason for which certain airborne samples and specific pollen taxa pose particular problems to deep learning algorithms. It is here concluded that the main challenges lie in A) the (partly) co-occurring of multiple pollen grains in a single image, B) the occlusion of specific markers through the 2D capturing of microscopy images, and C) for some taxa, a general lack of salient, unique features. …”
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Deep learning based gasket fault detection: a CNN approach by S. Arumai Shiney, R. Seetharaman, V. J. Sharmila, S. Prathiba

“…The suggested method uses deep learning approaches to recognize and evaluate radiator images, with a focus on identifying misaligned or incorrectly installed gaskets. Deep learning algorithms are specific for feature extraction and classification together with a convolutional neural network (CNN) module that allows for seamless connection. …”
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Impact of facial tattoos and paintings on face recognition systems by Mathias Ibsen, Christian Rathgeb, Thomas Fink, Pawel Drozdowski, Christoph Busch

“…The authors’ work is an initial case study and indicates a need to design algorithms which are robust to the visual changes caused by facial tattoos and paintings.…”
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