Optimization of Meat and Poultry Farm Inventory Stock Using Data Analytics for Green Supply Chain Network by Rajnish Kler, Roshan Gangurde, Samariddin Elmirzaev, Md Shamim Hossain, Nhut V. T. Vo, Tien V. T. Nguyen, P. Naveen Kumar

“…Effective inventory optimization algorithms have been shown to be able to evaluate a significant portion of previous sales data and anticipate inventory future demand by taking seasonality and lead times into account. …”
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Adrenal Insufficiency: A Forgotten Diagnosis in HIV/AIDS Patients in Developing Countries by David D. Nassoro, Mkhoi L. Mkhoi, Issa Sabi, Alfred J. Meremo, Paul S. Lawala, Issakwisa Habakkuk Mwakyula

“…Development of simple screening algorithms may help clinicians reach the diagnosis when approaching these patients. …”
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Review of models for estimating 3D human pose using deep learning by Sani Salisu, Kamaluddeen Usman Danyaro, Maged Nasser, Israa M. Hayder, Hussain A. Younis

“…We assess the most widely used datasets and evaluation metrics, providing a comparison of leading algorithms in terms of precision and computational efficiency in tabular form. …”
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Design, Multiperspective Investigations, and Performance Analysis of Multirotor Unmanned Aerial Vehicle for Precision Farming by Darshan Kumar Jayaram, Vijayanandh Raja, Beena Stanislaus Arputharaj, Hussein A. Z. AL-bonsrulah

“…In this experiment, AI algorithms were used to lemon leaves. Three AI systems were tested on different datasets to forecast plant stress by analyzing leaves due to technical constraints. …”
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Predictive modelling of hexagonal boron nitride nanosheets yield through machine and deep learning: An ultrasonic exfoliation parametric evaluation by Jerrin Joy Varughese, Sreekanth M․S․

“…A suite of machine learning regression models including Adaptive Boosting (AdaBoost) Regressor, Random Forest (RF) Regressor, Linear Regressor (LR), and Classification and Regression Tree (CART) Regressor, was employed alongside a deep neural network (DNN) architecture optimized using various algorithms such as Adaptive Moment Estimation (Adam), Root Mean Square Propagation (RMS Prop), Stochastic Gradient Descent (SGD), and Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS). …”
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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…To demonstrate the system's effectiveness, a curriculum was crafted for a specialized field of study - Artificial Intelligence (AI), with a specific focus on the practical application of Machine Learning algorithms. This curriculum incorporates theoretical and practical application components, complemented by a suite of assessment tools and assignments tailored to the proposed subject. …”
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An Extraction Method of Weak Low-Frequency Magnetic Communication Signals Based on Multisensor by Chao Huang, Xin Xu, Dunge Liu, Wanhua Zhu, Xiaojuan Zhang, Guangyou Fang

“…In this paper, we analyze the numerical characteristics of the low-frequency magnetic field and propose the algorithms of the fast optimization of blind source separation (FOBSS) and the frequency-domain correlation extraction (FDCE). …”
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An improved soft voting-based machine learning technique to detect breast cancer utilizing effective feature selection and SMOTE-ENN class balancing by Indu Chhillar, Ajmer Singh

“…However, if the dataset contains duplicate or irrelevant features, machine learning-based algorithms are unable to give the intended results. …”
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Very Short-Term Blackout Prediction for Grid-Tied PV Systems Operating in Low Reliability Weak Electric Grids of Developing Countries by Benson H. Mbuya, Aleksandar Dimovski, Marco Merlo, Thomas Kivevele

“…A very short-term power outage prediction model framework based on a hybrid random forest (RF) algorithm was developed using open-source Python machine learning libraries and using a dataset generated from the pilot project’s experimental microgrid. …”
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Quantum secure patient login credential system using blockchain for electronic health record sharing framework by M. Natarajan, A. Bharathi, C. Sai Varun, Shitharth Selvarajan

“…Similarly, the Tune Swarm Optimization (TSO) algorithm is utilized to optimize performance metrics. …”
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A critical assessment of ionic liquid-based aqueous biphasic systems for biomolecules extraction and CO2 absorption by Viggy Wee Gee Tan, Yazan Abuhasheesh, Doris Ying Ying Tang, Yongyu Zhang, Zengling Ma, Lin Chen, Rambabu Krishnamoorthy, Pau Loke Show

“…The incorporation of machine learning (ML) algorithms to predict the toxicity and CO2 capture properties, as well as the scaling up of IL-ABSs, is also explored.…”
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Hardware Efficient Speech Enhancement With Noise Aware Multi-Target Deep Learning by Salinna Abdullah, Majid Zamani, Andreas Demosthenous

“…When processing NOISEX-92 noises, the system achieved an average short-time objective intelligibility (STOI) and perceptual evaluation of speech quality (PESQ) scores of 0.81 and 1.62, respectively, outperforming SE algorithms trained with only a single learning target. …”
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Continuously tracking of moving object by a combination of ultra-high frequency radio-frequency identification and laser range finder by Yulu Fu, Ran Liu, Hua Zhang, Gaoli Liang, Shafiq ur Rehman, Lixiang Liu

“…Two-dimensional laser range finders can provide the distance to the objects but require complicated recognition algorithms to acquire the identity of object. This article proposes an innovative method to track the locations of dynamic objects by combining radio-frequency identification and laser ranging information. …”
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A scalable framework for secure and reliable wireless-based fog cloud communication by Kymbat Khairosheva, Abdul Razaque, Gulnara Bektemyssova, Joon Yoo

“…For that, the proposed SFRRDC supports a user authentication mining (UAM) algorithm to secure the confidentiality of the users. …”
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A Novel Compression Technique for Multi-Camera Nodes through Directional Correlation by Saima Shaheen, M. Younus Javed, Muid Mufti, Shehzad Khalid, Aasia Khanum, Shoab A. Khan, M. Usman Akram

“…In order to eliminate surplus data, standard video compression algorithms exploit spatial and temporal correlation present in video sequence. …”
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Machine learning-based prediction of antipsychotic efficacy from brain gray matter structure in drug-naive first-episode schizophrenia by Xiaodong Guo, Enpeng Zhou, Xianghe Wang, Bingjie Huang, Tianqi Gao, Chengcheng Pu, Xin Yu

“…At 1-year follow-up, patients were categorized into the rehabilitation and non-rehabilitation groups. Machine learning algorithms were applied to predict treatment outcomes based on GM volume, cortical thickness, and gyrification index, and the model performance was evaluated. …”
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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal. by Susana Lavado, Eduardo Costa, Niclas F Sturm, Johannes S Tafferner, Octávio Rodrigues, Pedro Pita Barros, Leid Zejnilovic

“…Logistic regression models with variables selected through low-variance filtering and recursive feature elimination outperformed various others trained with complex machine learning algorithms based on precision@k metric, outperforming also random selection and expert rule-based models in identifying students with poor oral health. …”
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A novel knowledge distillation framework for enhancing small object detection in blurry environments with unmanned aerial vehicle-assisted images by Sayed Jobaer, Xue-song Tang, Yihong Zhang, Gaojian Li, Foysal Ahmed

“…Using image deblurring before object detection is an option, but it demands significant computing power and relies heavily on the accuracy of the deblurring algorithms. Another common issue is the suitable dataset for the specific problem. …”
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Optimum Energy Flow Management of a Grid-Tied Photovoltaic-Wind-Battery System considering Cost, Reliability, and CO2 Emission by Meryeme Azaroual, Mohammed Ouassaid, Mohamed Maaroufi

“…A hybrid algorithm (HGAFMINCON) is developed to demonstrate the superiority of the algorithm over FMINCON and GA shown in terms of cost savings and income.…”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

“…We employed radial basis function (RBF) and multilayer perceptron (MLP) algorithms for ANN modeling. The optimal MLP configuration, utilizing the Levenberg–Marquardt (Trainlm) algorithm, consisted of three hidden layers with 20, 17, and 9 neurons, respectively, while the optimal RBF network contained 43 neurons. …”
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