A review of deep-learning-based models for afaan oromo fake news detection on social media networks by Kedir Lemma Arega, Kula Kekeba Tune, Asrat Mulatu Beyene, Wegderes Tariku, Nurhussen Menza Bune

“…It compares machine learning and deep learning algorithms, proposes future studies using picture data, and encourages more effective methodologies. …”
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Digitalization of Spectral Measurements in the Fourier Basis – Development Trends and Problems by O. V. Ponomareva, A. V. Ponomarev, N. V. Smirnova

“…An analysis of digital methods for measuring spectra showed that methods based on Discrete Fourier Transform (DFT) retain their leading role and are effective in almost all subject areas. However, there are also problems of digitalization of measurements of the spectra of signals based on the DFT, which are associated, first of all, with the manifestation of a number of negative effects that are absent with analog methods for measuring spectra based on the Fourier transform. …”
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Unraveling consistently altered brain activations of language deficits in schizophrenia: evidence from ALE meta-analysis by Yuwen He, Ya Hou, Yuan Zhou, Ruolei Gu, Fei Gao, Zhen Yuan

“…Further evidence in comparison analysis also uncovered greater alteration in right MFG related to comprehension than production, while greater alterations in left IFG and others related to production than comprehension in schizophrenia. …”
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PARAMETRIC SYNTHESIS OF MODELS FOR MULTICRITERIAL ESTIMATION OF TECHNOLOGICAL SYSTEMS by Vladimir Beskorovainyi

“…The experimental study of the method confirms the increase in the efficiency of the procedures of parametric synthesis of models built on its basis in comparison with the method of group accounting of arguments on the basis of genetic algorithms. Practical application of the results obtained in the support systems for making multicriteria design and management decisions will improve their accuracy and, on this basis, increase the functional and cost efficiency of modern TS.…”
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Advancing cybersecurity and privacy with artificial intelligence: current trends and future research directions by Krishnashree Achuthan, Sasangan Ramanathan, Sethuraman Srinivas, Raghu Raman

“…More research in trustworthy AI, standardizing AI-driven methods, legislations for robust privacy protection amongst others is emphasized. The study also highlights key current and future areas of focus, including quantum machine learning, explainable AI, integrating humanized AI and deepfakes.…”
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Developing a Critical Imagination for How Researchers can use Artificially Intelligent Tools Reflexively and Responsibly During Qualitative Literature Reviews by Kristen Foley, Caitlan McLean, Reece De Zylva, Gregorius Asa, Jordana Maio, Samantha Batchelor, Gideon Dzando, Ahmad Dimassi

“…Beyond only literature retrieval, some AI tools describe their use-value as being able to appraise and synthesise contrasting evidence within and across papers; work like ‘Spotify’ to cultivate a personalised ecosystem of research articles that evolves via algorithmic learning; and suggest new directions for research based on existing evidence about a topic and an assessment of knowledge gaps. …”
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Using machine learning to identify key predictors of maternal success in sheep for improved lamb survival by Ebru Emsen, Bahadir Baran Odevci, Muzeyyen Kutluca Korkmaz

“…Breed-specific maternal differences were also observed, with crossbred prolific ewes exhibiting stronger maternal instincts. …”
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Tackling Heterogeneous Light Detection and Ranging-Camera Alignment Challenges in Dynamic Environments: A Review for Object Detection by Yujing Wang, Abdul Hadi Abd Rahman, Fadilla ’Atyka Nor Rashid, Mohamad Khairulamirin Md Razali

“…Existing review articles on object detection predominantly focus on the statistical analysis of fusion algorithms, often overlooking the complexities of aligning data from these distinct modalities, especially dynamic environment data alignment. …”
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New Predictive Models for the Computation of Reinforced Concrete Columns Shear Strength by Anthos I. Ioannou, David Galbraith, Nikolaos Bakas, George Markou, John Bellos

“…Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. Three ML models, LREGR, POLYREG-HYT, and XGBoost-HYT-CV, were used to develop different predictive models that were able to compute the shear strength of RC columns. …”
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Scientific Substantiation of the Creation and Prospects for the Development of an Epidemiological Surveillance System for Infection Caused by the Epstein-Barr Virus by T. V. Solomay, E. G. Simonova, T. A. Semenenko

“…Also, improving the control of EBVinfection is impossible without continuing scientific research; professional training of medical workers on the clinic, diagnosis, epidemiology and prevention of EBV-infection; development of modern visual methods and means of informing the population about the clinic and prevention of EBV-infection.…”
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G-OnRamp: Generating genome browsers to facilitate undergraduate-driven collaborative genome annotation. by Luke Sargent, Yating Liu, Wilson Leung, Nathan T Mortimer, David Lopatto, Jeremy Goecks, Sarah C R Elgin

“…Despite advances in computational gene prediction algorithms, most eukaryotic genomes still benefit from manual gene annotation. …”
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The Analytical System for Determining the Attitude of Students to the University by Violeta Tretynyk, Mariia Pinda

“…Therefore, there is a need to develop new solutions that will not only be available for use, but also provide high accuracy and efficiency in processing text reviews. …”
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The future of immunohistochemistry: advancing precision medicine through artificial intelligence-driven spatial proteomics and multiplexed diagnostic technologies by Ruby Dhar, Arun Kumar, Subhradip Karmakar

“…The integration of AI algorithms automates the quantification of biomarkers, minimizes subjectivity in interpretations, and speeds up turnaround times in high-volume labs. …”
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DEVELOPMENT OF METHODOLOGY FOR DESIGNING TESTABLE COMPONENT STRUCTURE OF DISCIPLINARY COMPETENCE by Vladimir I. Freyman

“…The research findings can help promoting learning efficiency increase, a choice of adequate control devices, accuracy of assessment, and also efficient use of personnel, temporal and material resources of higher education institutions. …”
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Software-Defined Platform for Global Navigation Satellite System Antenna Array Development and Testing by Diogo Gomes, Diogo Baptista, Hugo Dinis, Paulo M. Mendes, Sérgio Lopes

“…The average delay introduced by each channel of the system is around 381 ns with a maximum deviation of 1.05 ns. The delay was also measured for the implementation using 4 beams, which achieves a slightly bigger average delay of 384.6 ns while keeping the variation to 5 to 6 ns. …”
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A Hybrid Approach of DenseNet121 with Attention and Bi-LSTM for Yoga Pose Estimation by Aarthy K., Alice Nithya

“…This approach not only ensures accurate pose identification but also enhances practicing quality and helps prevent errors, making it a valuable asset in diverse domains.…”
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Preliminary study: Data analytics for predicting medication adherence in Malaysian arthritis patients by Firdaus Aziz, Shubathira Sooriamoorthy, Bryan Liew, Sharifah M. Syed Ahmad, Wei Wen Chong, Sorayya Malek, Adliah Mhd Ali

“…Results Results from machine learning algorithms showed varied performance. Support vector machine, gradient boosting, and random forest models performed best with AUC values of 0.907, 0.775, and 0.632 utilizing all variables. …”
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Perioperative management of patients with rheumatic disorders: problems and solutions by A. A. Klimenko, A. A. Kondrashov

“…Currently management of patients with rheumatic disorders (RD) involves not only application of all of the known spectrum of mediations in accordance with current guidelines and algorithms but also timely use of high-tech medical care, for example, endoprosthesis of the large joints, spinal surgery, dental care, endovascular surgery, aimed at decreasing the level of disability and improving patients’ quality of life. …”
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Development of a Success Prediction Model for Crowdfunding Based on Machine Learning Reflecting ESG Information by Jiyoung Park, Hyung Jong Na, Hyungjoon Kim

“…To achieve the research objectives, this study employed advanced machine learning algorithms, including XGBoost, LightGBM, AdaBoost, CatBoost, and NGBoost, to analyze data from a prominent reward-based crowdfunding platform in Korea, ‘Wadiz.…”
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A fusion model to predict the survival of colorectal cancer based on histopathological image and gene mutation by Binsheng He, Lixia Wang, Wenjing Zhou, Haiyan Liu, Yingxuan Wang, Kebo Lv, Kunhui He

“…Predicting the survival of CRC patients not only enhances understanding of their life expectancies but also aids clinicians in making informed decisions regarding suitable adjuvant treatments. …”
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