Feature Selection for Hypertension Risk Prediction Using XGBoost on Single Nucleotide Polymorphism Data by Lailil Muflikhah, Tirana Noor Fatyanosa, Nashi Widodo, Rizal Setya Perdana, Solimun, Hana Ratnawati

“…It is a chronic medical issue that, if left unaddressed, can lead to severe health complications, including kidney problems, heart disease, and stroke. This study aims to develop a feature selection model using the XGBoost algorithm to identify specific single nucleotide polymorphisms (SNPs) as biomarkers for detecting hypertension risk. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…The SIMDP-EDLIoT model is designed to monitor and detect various conditions and activities within indoor spaces for disabled people. …”
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RODA-OOD: Robust Domain Adaptation from Out-of-Distribution Data by Jaekyun Jeong, Mangyu Lee, Sunguk Yun, Keejun Han, Jungeun Kim

“…Domain adaptation aims to effectively learn from two domains with different distributions, solving labeling problems; however, traditional methods assume that the source and target data are in-distribution data that share the same labels. …”
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Artificial Intelligence Technologies in Criminal Procedural Proving by M. S. Spiridonov

“…The author pays attention to the problems of using artificial intelligence technologies in conducting expert assessments, requiring an improved methodology of forensic work. …”
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Predicting fertilizer treating of maize using digital image processing and deep learning approaches by Eshete Derb Emiru, Kassie Bishaw

“…An automated approach to identify and categorize fertility problems in maize plants is desperately needed to address this issue. …”
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Preliminary Study on Real-Time Phonocardiogram Signal Acquisition and Analysis Using Machine Learning and IoMT for Digital Stethoscope by M. Kalimuthu, C. Hemanth

“…Since most heart-related problems are reflected by the small variations in the heart’s sounds, quality research into heart rhythm will provide valuable health information that may identify and treat cardiac-related issues and disorders. …”
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Plantention: A general-purpose, lightweight and attention-based model for multi-crop leaf disease classification by Brindha Subburaj, Rohan M, Samhruth Ananthanarayanan, Daehan Won

“…Being a staple contributor to the Indian economy, these losses can cause large problems in other sectors as well. Most computerized methods involve some form of Deep Learning algorithms and models to automate the detection process. …”
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INTERLEAVING BURST ERROR ELEMENTS IN INFORMATION ARRAYS USING THE METHOD OF INDEX STRUCTURISATION by I. P. Kadiev, P. A. Kadiev, B. R. Kudaev

“…Thus, the task of combating the burst errors leading to the destruction of individual groups of characters can be reduced to solving a simpler problem of minor fold error correction.…”
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Frequency Characteristics of Rhythm Non-Assimilation in Canine Ventricular Fibrillation by M. I. Guryanov

“…Ventricular fibrillation is the main cause of sudden cardiac death in many countries, including Russia; therefore to study ventricular fibrillation is an urgent problem. Objective: to study rhythm non-assimilation in canine ventricular fibrillation. …”
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Topical Issues of Drug Safety, Possibilities of Improving of Pharmacovigilance by M. V. Zhuravleva, B. K. Romanov, G. I. Gorodetskaya, O. V. Muslimova, V. S. Krysanova, E. Yu. Demchenkova

“…The analysis of pharmacovigilance structure in the Russian Federation is carried  out, its main problems are designated. Presents methods to identify causal relationships between adverse reaction and drug, evaluation of its degree of validity (questionnaires, algorithms, and scale), as already recommended by the WHO, and the new modifi ed versions. …”
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Applying Machine Learning for Sustainable Farm Management: Integrating Crop Recommendations and Disease Identification by P. Ankit Krishna, Neelamadhab Padhy, Archana Patnaik

“…The goal is to give farmers precise advice for the best crop choices and the prompt detection of plant diseases by utilizing machine learning algorithms. …”
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CdZnTe- and TlBr-detectors response simulation for registration of the mixed beta- and gamma-radiation by A. I. Skrypnyk

“…The conducted studies allow us: — to see in a new light the measurement results on finite intervals of current Fourier spectrum and the current energy Fourier spectra of signals; give a numerical estimate of the non-invariance of the current energy Fourier spectrum of real tonal components. — to increase the effectiveness of digital spectral analysis in its many applications, in particular, for solving the problems of detection and identification of hidden periodicities in such subject areas as radar, vibroacoustic diagnostics, passive sonar, biomedicine, etc.…”
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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 conducted studies allow us: — to see in a new light the measurement results on finite intervals of current Fourier spectrum and the current energy Fourier spectra of signals; — give a numerical estimate of the non-invariance of the current energy Fourier spectrum of real tonal components; — to increase the effectiveness of digital spectral analysis in its many applications, in particular, for solving the problems of detection and identification of hidden periodicities in such subject areas as radar, vibroacoustic diagnostics, passive sonar, biomedicine, etc.…”
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Secrecy-Constrained UAV-Mounted RIS-Assisted ISAC Networks: Position Optimization and Power Beamforming by Weichao Yang, Yajing Wang, Dawei Wang, Yixin He, Li Li

“…To address this non-convex, multivariate, and coupled problem, we decompose it into three subproblems, which are solved iteratively using particle swarm optimization (PSO), semi-definite relaxation (SDR), majorization–minimization (MM), and alternating direction method of multipliers (ADMM) algorithms. …”
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A Review of Approaches for Rapid Data Clustering: Challenges, Opportunities, and Future Directions by Mahnoor, Imran Shafi, Mahnoor Chaudhry, Elizabeth Caro Montero, Eduardo Silva Alvarado, Isabel de la Torre Diez, Md Abdus Samad, Imran Ashraf

“…This paper examines unique strategies for rapid clustering, highlighting the problems and possibilities in this area. The paper includes a brief introduction to clustering, discussing various clustering algorithms, improvements in handling various data types, and appropriate evaluation metrics. …”
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CNN‐based off‐angle iris segmentation and recognition by Ehsaneddin Jalilian, Mahmut Karakaya, Andreas Uhl

“…Finally, the recognition performance of the selected approach is compared against some state‐of‐the‐art off‐angle iris recognition algorithms.…”
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Simultaneous Classification of Objects with Unknown Rejection (SCOUR) Using Infra-Red Sensor Imagery by Adam Cuellar, Daniel Brignac, Abhijit Mahalanobis, Wasfy Mikhael

“…Recognizing targets in infra-red images is an important problem for defense and security applications. A deployed network must not only recognize the known classes, but it must also reject any new or <i>unknown</i> objects without confusing them to be one of the known classes. …”
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Oversampling based on generative adversarial networks to overcome imbalance data in predicting fraud insurance claim by Ranu Agastya Nugraha, Hilman Ferdinandus Pardede, Agus Subekti

“…However, one of remaining problems for predicting health insurance frauds is the data imbalance. …”
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Key Vital Signs Monitor Based on MIMO Radar by Michael Gottinger, Nicola Notari, Samuel Dutler, Samuel Kranz, Robin Vetsch, Tindaro Pittorino, Christoph Würsch, Guido Piai

“…Key vital parameters that can be measured in the second step are respiration rate, asynchronous respiratory movement of chest and abdomen and limb movements. The developed algorithms were tested through experiments. The achieved mean absolute error (MAE) for the locations of the xiphoid and navel was less than 5 cm and the categorical accuracy of pose classification and limb movement detection was better than 90% and 98.6%, respectively. …”
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Digital Technology of Assesment the Power Capacity of Tractor Fleet of an Agricultural Enterprise by V. V. Alt, O. F. Savchenko, O. V. Elkin

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