Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues by Gianmarco Lazzini, Mario D’Acunto

“…In particular, in the last years several studies have demonstrated how the diagnostic performances of RS can be significantly improved by employing machine learning (ML) algorithms for the interpretation of Raman-based data. …”
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The Performance of an ML-Based Weigh-in-Motion System in the Context of a Network Arch Bridge Structural Specificity by Dawid Piotrowski, Marcin Jasiński, Artur Nowoświat, Piotr Łaziński, Stefan Pradelok

“…In civil and bridge engineering, they can facilitate the identification of specific patterns through the analysis of data acquired from structural health monitoring (SHM) systems. To evaluate the prediction capabilities of ML, this study examines the performance of several ML algorithms in estimating the total weight and location of vehicles on a bridge using strain sensing. …”
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Comparative Analysis of Deep Learning Models for Intrusion Detection in IoT Networks by Abdullah Waqas, Sultan Daud Khan, Zaib Ullah, Mohib Ullah, Habib Ullah

“…This study addresses the problem of detecting intrusions in IoT environments by evaluating the performance of deep learning (DL) models under different data and algorithmic conditions. …”
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Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration by Ousama M.T. Ajami, Rodney H.G. Tan, Mithulan Nadarajah, Farah Adilah Jamaludin, Adlan Bagus Pradana

“…To optimize the control parameters with the best objectives, all possible sets of objectives with four different optimization algorithms are studied. The three control models considered for the HESS incorporate Virtual Synchronous Generator (VSG) or Virtual Inertia (VI) control with independent or simultaneous optimization of control parameters. …”
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Comprehensive analysis of total knee arthroplasty kinematics and functional recovery: Exploring full-body gait deviations in patients with knee osteoarthritis. by Xavier Gasparutto, Alice Bonnefoy-Mazure, Michael Attias, Katia Turcot, Stéphane Armand, Hermès H Miozzari

“…The knee was excluded from classification to focus on full-body kinematics. Differences between groups, with controls, as well as before and after surgery were evaluated for patients reported outcome measures, kinematic features, and spatio-temporal parameters. …”
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Incidence, Pathogenesis, Risk Factors, and Treatment of Cystoid Macula Oedema Following Cataract Surgery: A Systematic Review by Lorenzo Ferro Desideri, Kirupakaran Arun, Enrico Bernardi, Nicola Sagurski, Rodrigo Anguita

“…Further research is needed to establish optimal treatment algorithms and improve outcomes for patients with post-operative CMO…”
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Machine learning approaches for identifying and predicting voltage conditions in power system networks using network topology behavior input formulation by Tolulope David Makanju, Oluwole John Famoriji, Ali N. Hasan, Thokozani Shongwe

“…This paper developed a predictive model for determining the condition of voltage in a power system based on the network topology behavior as input formulation. Different machine learning algorithms random forest, support vector machine and gradient boosting were used to evaluate the input formulation approach for voltage condition prediction in power system networks. …”
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IMPACT OF SEASONALITY OF GENERATION AND LOAD ON THE OPTIMAL CAPACITY OF THE ENERGY STORAGE SYSTEM OF THE PROSUMER’S MICROGRID by O.В. Кулапін, A.В. Івахнов, С.O. Федорчук, К.В. Махотіло, Д.О. Данильченко, О.В. Булгаков

“…Development of a method for determining the optimal capacity of an energy storage system to maximize profit from interaction prosumer’s microgrid with the power grid. Two radically different controller algorithms of microgrid operation are considered: the first is focused on the maximum use of solar generation, and the second is on the balanced use of all elements of the prosumer’s microgrid system, including storage and energy consumption. …”
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Prognostic and Diagnostic Value of Spontaneous Tumor-Related Antibodies by Sebastian Kobold, Tim Luetkens, Yanran Cao, Carsten Bokemeyer, Djordje Atanackovic

“…The combined analysis of autoantibodies targeting different antigens, however, may reach high sensitivity and specificity. …”
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Locating and quantifying CH₄ sources within a wastewater treatment plant based on mobile measurements by J. Yang, Z. Xu, Z. Xia, Z. Xia, X. Pei, Y. Yang, B. Qiu, B. Qiu, S. Zhao, S. Zhao, Y. Zhang, Y. Zhang, Z. Wang, Z. Wang

“…Locating and quantifying WWTP emission sources using a measurement-based GHG emission quantification method is crucial for evaluating and improving traditional emission inventories. …”
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Safety of creatine supplementation: a scientometrics analysis on the impact of the ‘Creatine For Health’ initiative and introduction to CREAS by Diego A. Bonilla, Drew E. Gonzalez, Gustavo Humeres, Jisun Chun, Kelly Hines, Adriana Gil, Richard B. Kreider

“…We employed supervised machine learning for sentiment analysis to detect and classify subjective content, using the SentiStrength algorithm within the Academic Research version of Mozdeh software. …”
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THE APPROVAL OF COMPLEX TREATMENT EFFECTIVENESS OF GENERALIZED PERIODONTITIS FOR THE PATIENTS AFTER TRANSMITTED CORONAVIRUS DISEASE AND REMAIN ON REHABILITATION by T.I. Matviykiv, M.M. Rozhko

“…The comparison of the effectiveness of treatment protocols for the patients diagnosed with generalized periodontitis and those hospitalized for pulmonary complications of coronavirus did not reveal a significant difference in the obtained clinical data on the choice of treatment. …”
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A comparative study of bone density in elderly people measured with AI and QCT by Min Guo, Min Guo, Yu Zhang, Yu Zhang, XinXin Gu, XinXin Gu, Xuhui Liu, Xuhui Liu, Fei Peng, Fei Peng, Zongjun Zhang, Zongjun Zhang, Mei Jing, Mei Jing, Yingxia Fu, Yingxia Fu

“…The linear regression fit between the R2 values of QCT and Bone Density AI for measuring lumbar spine BMD with different equipment ranged from 0.88 to 0.96, indicating a high degree of consistency between the two measurement methods across devices.ConclusionThis multicenter study pioneers a dual-validation framework to establish the clinical validity of deep learning-based BMD prediction algorithms using routine thoracic/abdominal CT scans. …”
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A Novel Dataset for Experimentation With Intrusion Detection Systems in SCADA Networks Using IEC 60870-5-104 Standard by M. Agus Syamsul Arifin, Deris Stiawan, Bhakti Yudho Suprapto, Susanto, Tasmi Salim, Mohd Yazid Idris, Mohamed Shenify, Rahmat Budiarto

“…Snort and Suricata verified the integrity of the dataset. We then evaluated six Intrusion Detection System (IDS) models using different machine learning algorithms, i.e.: Artificial Neural Network, Categorical Naïve Bayes, Decision Tree, K-Nearest Neighbors, Gradient Boosting, and Random Forest. …”
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ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…In this study, the proposed technique is referred to as the ML-based Self-Optimization Handover Technique (ML-SOHOT). The technique is evaluated and validated using different major HO metrics, including Handover Probability (HOP), Handover Failure (HOF), and Handover Ping-Pong (HOPP) across various mobility patterns in B5G, specifically considering an urban environment. …”
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Feasibility, Advantages, and Limitations of Machine Learning for Identifying Spilled Oil in Offshore Conditions by Seong-Il Kang, Cheol Huh, Choong-Ki Kim, Meang-Ik Cho, Hyuek-Jin Choi

“…The main objective was to compare models generated from various combinations of features and data. Under five different algorithms, the resulting models were evaluated in terms of their feasibility, advantages, and limitations (FAL). …”
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Metrology of Multicarrier-Based Delay-Doppler Channel Sounding for Sub-THz Frequencies by Jonas Gedschold, Diego Dupleich, Sebastian Semper, Michael Dobereiner, Alexander Ebert, Giovanni Del Galdo, Reiner S. Thoma

“…Therefore, we propose and discuss an over-the-air artifact allowing a joint verification of delay and Doppler parameters in a multipath scenario. The evaluations of exemplary sub-THz measurements with a multicarrier-based sounder highlight the strong interplay between sounder hardware and estimation algorithms, especially when coping with the mutual interference of parameters from multiple propagation paths. …”
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Characteristic genes and immune landscape of interstitial cystitis. by Junhao Wang, Yan Zhou, Jie Hu, Jianpeng Han, Jianyong Feng, Kuo Guo, Wenbin Chen, Yanrui Yun, Yongzhang Li

“…Receiver operator characteristic curve (ROC) was used to evaluate diagnostic efficacy of key genes.<h4>Results</h4>CCL18, MMP10 and WIF1 were identified as characteristic gene via machine learning algorithms. …”
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Corn Plant In-Row Distance Analysis Based on Unmanned Aerial Vehicle Imagery and Row-Unit Dynamics by Marko M. Kostić, Željana Grbović, Rana Waqar, Bojana Ivošević, Marko Panić, Antonio Scarfone, Aristotelis C. Tagarakis

“…This study investigates the effectiveness of utilizing different plant recognition algorithms applied to UAV-derived images for evaluating seeder performance based on detected plant spacings. …”
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A hybrid mutational Northern Goshawk and elite opposition learning artificial rabbits optimizer for PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…Abstract For the purpose of simulating, controlling, evaluating, managing and optimizing PEMFCs it is necessary to develop accurate mathematical models. …”
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