Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review by Dhekre Saber Saleh, Mohd Shahizan Othman

“…By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. …”
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Optimizing microgrid performance a multi-objective strategy for integrated energy management with hybrid sources and demand response by Mohsen Moosavi, Javad Olamaei, Hossein Mohmmadnezhad Shourkaei

“…When compared to leading optimization algorithms, the proposed approach showed better performance. …”
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TS-PAID: A Two-Stage PUF-Based Lightweight Authentication Protocol for Internet of Drones by Shehzad Ashraf Chaudhry, Azeem Irshad, Bander A. Alzahrani, Ahmad Alhindi, Mohd Shariq, Ashok Kumar Das

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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

“…The data we use is provided by the National Alzheimer’s Coordinating Center (NACC) and contain many clinical and demographic predictors by which we characterize and model the cognitive status of the subjects. …”
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The invariance of current energy fourier spectrum of discrete real signals on finite intervals by V. A. Ponomarev, O. V. Ponomareva

“…The paper deals with the problems of measuring Fourier spectrum of signals in the base of discrete exponential functions. Methods and algorithms of sliding measurements of energy Fourier spectrum of signals on finite intervals were described. …”
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Hankel Tensor Subspace Representation for Remotely Sensed Image Fusion by Fei Ma, Qiang Qu, Feixia Yang, Guangxian Xu

“…As an illposed inverse problem, however, current multisensor data fusion faces many challenges. Exactly, traditional matrix-factorization-based algorithms often result in the loss of cubic structure knowledge in hyperspectral data, while deep neural networks are susceptible to noise accumulation and lack of large-scale labeled data. …”
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Advanced Multiplier Architecture Optimization for Accelerated Arithmetic Operations and its Integration in Wireless Sensor Network Applications by Nirmal Kumar R., Valarmathi R. S., Kalamani M.

“…Wireless sensor networks (WSNs) are becoming more valuable in environmental monitoring and industrial automation. Many WSN applications need high-performance adders and multipliers for efficient computation. …”
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Intrusion Detection System Framework for SDN-Based IoT Networks Using Deep Learning Approaches With XAI-Based Feature Selection Techniques and Domain-Constrained Features by Manlaibaatar Tserenkhuu, Md Delwar Hossain, Yuzo Taenaka, Youki Kadobayashi

“…The proliferation of Internet of Things (IoT) applications impact many aspects of life, including smart homes, smart offices, and smart cities, among others. …”
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Performance Estimation of Low Power and Area-Efficient Parallel Pipelined FFT by Surya P, Arunachalaperumal C, Dhilipkumar S

“…It is also used in image and video processing and is critical for algorithms that manipulate pixels, scale, and compress data when many multiplications need to be performed quickly. …”
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Enhancing Unmanned Aerial Vehicle Object Detection via Tensor Decompositions and Positive–Negative Momentum Optimizers by Ruslan Abdulkadirov, Pavel Lyakhov, Denis Butusov, Nikolay Nagornov, Dmitry Reznikov, Anatoly Bobrov, Diana Kalita

“…The current development of machine learning has advanced many fields in applied sciences and industry, including remote sensing. …”
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Data augmentation of time-series data in human movement biomechanics: A scoping review. by Christina Halmich, Lucas Höschler, Christoph Schranz, Christian Borgelt

“…However, the field faces challenges such as limited large-scale data sets, high data acquisition costs, and restricted participant access that hinder the development of robust algorithms. Additional issues include variability in sensor placement, soft tissue artifacts, and low diversity in movement patterns. …”
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Identification of factors associated with acute malnutrition in children under 5 years and forecasting future prevalence: assessing the potential of statistical and machine learnin... by Christopher Coffey, Meike Reusken, Frans Cruijssen, Bertrand Melenberg, Cascha van Wanrooij

“…Among the forecasting methods tested, random forest machine learning proves to be the most effective and was found to accurately forecast the direction of GAM prevalence in test data for many of the districts in Somalia.…”
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Diagnostics of leaks with unknown amplitudes against the background of interference caused by accidental consumption in the hydraulic system for the forest complex by Sazonova Svetlana, Zolnikov Konstantin, Skvortsova Tatyana, Kravchenko Andrey, Zarevich Anton

“…The formation of algorithms for leak detection is considered. It is shown that the solution to the problem of specific leak detection may vary depending on the type of hydraulic system and the technologies used. …”
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Phenological Restriction of the Oryza (v3) Model by Gutemberg Resende Honorio Filho, Alexandre Bryan Heinemann, David Henriques da Matta, Luís Fernando Stone, Santiago Vianna Cuadra, Silvio Steinmetz

“…Crop simulation models, such as ORYZA (v3), use equations that depend on two main parameters calibrated by the user: sensitivity to photoperiod and minimum optimal photoperiod. …”
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Laser-Induced Thermal Treatment of Superficial Human Tumors: An Advanced Heating Strategy and Non-Arrhenius Law for Living Tissues by Leonid A. Dombrovsky, Leonid A. Dombrovsky, Leonid A. Dombrovsky

“…The known finite-difference or finite element algorithms can be preferable in solving transient heat transfer problems. …”
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False data injection attack dataset for classification, identification, and detection for IIoT in Industry 5.0Zenodo by A K M Ahasan Habib, Mohammad Kamrul Hasan, Rosilah Hassan, Shayla Islam, Huda Saleh Abbas

“…The dataset offers an accurate characterization of IoT environments by covering many different kinds of network configurations and scenarios. …”
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Systematic Review: Malware Detection and Classification in Cybersecurity by Sebastian Berrios, Dante Leiva, Bastian Olivares, Héctor Allende-Cid, Pamela Hermosilla

“…Finally, this study identifies the main challenges and outlines opportunities of future research to improve malware detection and classification frameworks.…”
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BIM-Based Trajectory Planning for Unmanned Aerial Vehicle-Enabled Box Girder Bridge Inspection by Jiangpeng Shu, Zhe Xia, Yifan Gao

“…The approach reflects the geometry properties of box girders as inspection characteristics and is designed with algorithms to determine a mathematical relationship between the box girders’ coordinates and inspection sequences. …”
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Lung cancer brain metastases – the role of neurosurgery by V. A. Aleshin, V. B. Karakhan, A. Kh. Bekyashev, D. M. Belov

“…These factors increase the risk of metastatic lesions of the brain.Interest to the problem of neurosurgical treatment of patients suffering lung cancer is determined by frequency of lesion, varicosity of morphological variants of the disease, requiring various algorithms of treatment and diagnosis.The main role of neurosurgical intervention in cerebral metastases of lung cancer consist in creation of the paled of carrying out combined therapy. …”
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Fusing LiDAR and Photogrammetry for Accurate 3D Data: A Hybrid Approach by Rytis Maskeliūnas, Sarmad Maqsood, Mantas Vaškevičius, Julius Gelšvartas

“…The fusion of LiDAR and photogrammetry point clouds is a necessary advancement in 3D-modeling, enabling more comprehensive and accurate representations of physical environments. The main contribution of this paper is the development of an innovative fusion system that combines classical algorithms, such as Structure from Motion (SfM), with advanced machine learning techniques, like Coherent Point Drift (CPD) and Feature-Metric Registration (FMR), to improve point cloud alignment and fusion. …”
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