A Lightweight Citrus Object Detection Method in Complex Environments by Qiurong Lv, Fuchun Sun, Yuechao Bian, Haorong Wu, Xiaoxiao Li, Xin Li, Jie Zhou

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Performance of Sentiment Classification on Tweets of Clothing Brands by Muhammad Shafiq Jalani, Hu Ng, Timothy Tzen Vun Yap, Vik Tor Goh

“…Hyperparameter tuning was implemented by GridSearchCV to find the best parameters of classification models in order to optimize the best results.  …”
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Serum microRNAs as peripheral markers of primary aldosteronism by Nikita Makhnov, Nikita Makhnov, Nikita Makhnov, Fredrik Axling, Elham Barazeghi, Peter Stålberg, Tobias Åkerström, Tobias Åkerström, Per Hellman, Per Hellman

“…The differentiating parameters were moderately good for comparison of bPA vs. uPA.ConclusionWithin our patient cohort, and using ML, the study identified distinctly different miRNA profiles between HT and PA, as well as between bPA and uPA. …”
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Hyperspectral imaging as a non-destructive technique for estimating the nutritional value of food by Juan-Jesús Marín-Méndez, Paula Luri Esplandiú, Miriam Alonso-Santamaría, Berta Remirez-Moreno, Leyre Urtasun Del Castillo, Jaione Echavarri Dublán, Eva Almiron-Roig, María-José Sáiz-Abajo

“…This study shows that it is possible to predict the energy and nutrient values of processed complex foods, using hyperspectral imaging systems combined with supervised machine learning methods.…”
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Reliable models for calculating the condensation heat transfer inside smooth helical tubes of different flow directions utilizing smart computational techniques by Chou-Yi Hsu, Nikunj Rachchh, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Ahmad Alkhayyat, Prabhat Kumar Sahu, Abhinav Kumar, Satvik Vats, F. Ranjbar

“…The current study aims at developing reliable models for the condensation HTC within smooth helical tubes at all flow directions. Two machine learning (ML) techniques, namely Support Vector Machine (SVM) and Gaussian Process Method (GPM) were implemented to accomplish this target. …”
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Using ML techniques to predict extubation outcomes for patients with central nervous system injuries in the Yun-Gui Plateau by Zi-han Chen, Hao-tian Wu, Zhou Yao, Qian Liu, Hong-mei Zhang, Xiao-chen Li, Li-qing Yao, Xue Yang

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Comparative analysis of correlation and causality inference in water quality problems with emphasis on TDS Karkheh River in Iran by Reza Shakeri, Hossein Amini, Farshid Fakheri, Man Yue Lam, Banafsheh Zahraie

“…Utilizing a comprehensive dataset spanning 50 years (1968–2018), this research integrates Machine Learning (ML) techniques to examine correlations and infer causality among multiple parameters, including flow rate (Q), Sodium (Na+), Magnesium (Mg2+), Calcium (Ca2+), Chloride (Cl−), Sulfate (SO4 2−), Bicarbonates (HCO3 −), and pH. …”
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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…This study aimed to develop an interpretable machine learning (ML) model using routine laboratory parameters to predict blood culture positivity. …”
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Designing for efficiency: an exploration of optimized joint configurations in tyne cultivator design by Elavarasan S, Manimaran G

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Long-Range Wide Area Network Intrusion Detection at the Edge by Gonçalo Esteves, Filipe Fidalgo, Nuno Cruz, José Simão

“…This paper proposes the implementation of machine learning algorithms, specifically the K-Nearest Neighbours (KNN) algorithm, within an Intrusion Detection System (IDS) for LoRaWAN networks. …”
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Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers by Hengjun Wan, Huaju Tian, Cheng Wu, Yue Zhao, Daiying Zhang, Yujie Zheng, Yuan Li, Xiaoxia Duan

“…Herein, we constructed a multidimensional postoperative delirium risk‐prediction model incorporating multiple demographic parameters and blood biomarkers to enhance prediction accuracy. …”
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Application of a methodological framework for the development and multicenter validation of reliable artificial intelligence in embryo evaluation by D. Gilboa, Akhil Garg, M. Shapiro, M. Meseguer, Y. Amar, N. Lustgarten, N. Desai, T. Shavit, V. Silva, A. Papatheodorou, A. Chatziparasidou, S. Angras, J. H. Lee, L. Thiel, C. L. Curchoe, Y. Tauber, D. S. Seidman

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Predicting Insemination Outcome in Holstein Dairy Cattle using Deep Learning by Mohammad Alishahi, Mahdi Ravakhah

“…Introduction: Development of a predictive model using machine learning can help livestock farmers to increase their understanding of the performance potential of their livestock. …”
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Output current harmonic analysis and suppression method for PMSM drive system with modular multilevel converter by Yang Zhang, Sicheng Li, Bing Luo, Chaokui Luo, Zhi Yu

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The Number of Microbubbles Generated During Cardiopulmonary Bypass Can Be Estimated Using Machine Learning From Suction Flow Rate, Venous Reservoir Level, Perfusion Flow Rate, Hema... by Satoshi Miyamoto, Zu Soh, Shigeyuki Okahara, Akira Furui, Taiichi Takasaki, Keijiro Katayama, Shinya Takahashi, Toshio Tsuji

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Modern trends in diagnostics and prediction of results of anti-vascular endothelial growth factor therapy of pigment epithelial detachment in neovascular agerelated macular degener... by E. V. Kozina, S. N. Sakhnov, V. V. Myasnikova, E. V. Bykova, L. E. Aksenova

“…Modern technologies of spectral optical coherence tomography make it possible to evaluate detailed quantitative parameters of pigment epithelium detachment, such as height, width, maximum linear diameter, area, volume and refl ectivity within the detachment.Groups of Russian and foreign authors identify various biomarkers recorded on optical coherence tomography images. …”
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Multi‑omics identification of a novel signature for serous ovarian carcinoma in the context of 3P medicine and based on twelve programmed cell death patterns: a multi-cohort machin... by Lele Ye, Chunhao Long, Binbing Xu, Xuyang Yao, Jiaye Yu, Yunhui Luo, Yuan Xu, Zhuofeng Jiang, Zekai Nian, Yawen Zheng, Yaoyao Cai, Xiangyang Xue, Gangqiang Guo

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Development of Machine Learning Prediction Models to Predict ICU Admission and the Length of Stay in ICU for COVID‑19 Patients Using a Clinical Dataset Including Chest Computed Tom... by Seyed Salman Zakariaee, Negar Naderi, Hadi Kazemi-Arpanahi

“…The most important and related predictors selected by the Boruta feature selection method were used to develop ML prediction models. The parameters obtained from the confusion matrix were used to evaluate the performance of the prediction models. …”
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Measuring of roundness after turning of composite material with natural fibers by D. Mital, J. Zajac, F. Botko, M. Hatala, Z. Mitalova, S. Radchenko, V. Ivanov

“…Technologists begin to use convention technologies – drilling, milling and turning, as tendency of application of WPC increased. Knowledges about machining of WPC are not elaborate as deep as machining of metals or plastics. …”
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Determinación de los parámetros geométricos originales de ruedas dentadas cilíndricas de dientes rectos y helicoidales mediante programa de computación. // Determination of origina... by J. Randulfe Ceballos, M. Sánchez Castro, F. Hdez Sardiñas, M. Gómez Florido

“…</p><p><br />Key words:Helical gears, calculations, geometric parameters, automation.</p>…”
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