Using artificial intelligence for enhancement of solar cell efficiency in the of Iraq by Ibtihal R. N. ALRubeei, Safa N. Idi, Ihab L. Hussein Alsammak, Haider Th. AlRikabi, Hussain A. Mutar, Abdul Hadi M. Alaidi

“…Research findings confirm that AI-based site selection procedures can boost solar energy cell performance throughout south Iraq. The model uses Random Forest machine learning to integrate diverse data types which enables site suitability prediction together with optimized outcomes in energy production and economic affordability. …”
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IFed: A novel federated learning framework for local differential privacy in Power Internet of Things by Hui Cao, Shubo Liu, Renfang Zhao, Xingxing Xiong

“…However, the large computing resource consumption to train the machine learning model is not affordable for most Power Internet of Thing terminal. …”
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Using artificial intelligence for enhancement of solar cell efficiency in the of Iraq by Ibtihal R. N. ALRubeei, Safa N. Idi, Ihab L. Hussein Alsammak, Haider Th. AlRikabi, Hussain A. Mutar, Abdul Hadi M. Alaidi

“…Research findings confirm that AI-based site selection procedures can boost solar energy cell performance throughout south Iraq. The model uses Random Forest machine learning to integrate diverse data types which enables site suitability prediction together with optimized outcomes in energy production and economic affordability. …”
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Smart IoT-driven precision agriculture: Land mapping, crop prediction, and irrigation system. by Gourab Saha, Fariha Shahrin, Farhan Hasin Khan, Mashook Mohammad Meshkat, Akm Abdul Malek Azad

“…Multiple soil-parameter measuring sensors are used to identify suitable crop and fertilizer requirements for that land using IoT and machine learning. The ML model-based crop prediction showed 97.35% accuracy utilizing random forest algorithm. …”
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Soft Computing Solutions for Reducing the Carbon Footprint of Fly Ash Based Concrete. Advances in Civil Engineering by Awoyera, Paul O., Adetola, Joshua, Nayeemuddin, Mohammed, Mewada, Hiren, George Fadugba, Olaolu

“…The construction industry significantly contributes to environmental degradation,with many structures exhibiting high carbon footprints throughout their construction processes and lifespans.Activities such as cement hydration and other commoncon-struction practices substantially influence environmental conditions overtime,necessitating a critical evaluation of material and design choices.This study reported the environmental impact of fly ash(FA),which is largely used to enhance concrete strength.A prediction of two end point indicators,that is,global warming potential(GWP)and CO2 emission using soft computing methods are presented,which are particularly effective for handling complex,non linear relationships in environmental data.To achieve this, two machine learning approaches,the random forest(RF)and decision tree(DT)models,are employed to assess the environ- mental impact of structural materials and designs.Two data sets were obtained from reputable databases,including ResearchGate, Science Direct, Semantic Scholar,and Mendeley Data.The models are trained to explore the potential for optimizing structural designs and material selection stominimize environmental impacts.Feature importance is analyzed using Shapley values,providing insights into the most influential factors affecting GWP and CO2 emission Model performance is evaluated using R2 and root mean square error(RMSE) metrics. …”
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SegTrackDetect: A window-based framework for tiny object detection via semantic segmentation and tracking by Aleksandra Kos, Karol Majek, Dominik Belter

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Preliminary clinical performance of a Cas13a-based lateral flow assay for detecting Neisseria gonorrhoeae in urine specimens by Lao-Tzu Allan-Blitz, Gordon Adams, Gabriela Sanders, Palak Shah, Krithik Ramesh, Jana Jarolimova, Kevin L. Ard, John A. Branda, Jeffrey D. Klausner, Pardis C. Sabeti, Jacob E. Lemieux

“…We also trained a smartphone-based machine-learning model on 1,008 images to classify lateral flow results. …”
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Fine-tuned PhoBERT for sentiment analysis of Vietnamese phone reviews by Tan Minh Ngo, Ba Hung Ngo, Stuchilin Vladimir Valerievich

“…We experimented with various models including naive Bayes, Support Vector Machine, and PhoBERT, utilizing multiple data preprocessing techniques. …”
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Fine-tuned PhoBERT for sentiment analysis of Vietnamese phone reviews by Tan Minh Ngo, Ba Hung Ngo, Stuchilin Vladimir Valerievich

“…We experimented with various models including naive Bayes, Support Vector Machine, and PhoBERT, utilizing multiple data preprocessing techniques. …”
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Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs by Kaifeng Geng, Chunming Ye, Zhen hua Dai, Li Liu

“…The proposed model can make enterprises avoid high price period reasonably, transfer power load, and reduce the energy consumption cost effectively. …”
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A transformer-based framework for enterprise sales forecasting by Yupeng Sun, Tian Li

“…The experimental results demonstrated that our proposed method surpasses conventional machine learning models, achieving reduced mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE), as well as higher R2 values of nearly 0.95. …”
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In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study by Chitra Joshi, Chitrakant Banchorr, Omkaresh Kulkarni, Kirti Wanjale

“…It also had a big impact on the time it took to train and run models because of its optimized in-memory processing. …”
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Survey of Quantum Generative Adversarial Networks (QGAN) to Generate Images by Mohammadsaleh Pajuhanfard, Rasoul Kiani, Victor S. Sheng

“…Quantum Generative Adversarial Networks (QGANs) represent a useful development in quantum machine learning, using the particular properties of quantum mechanics to solve the challenges of data analysis and modeling. …”
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Identification of significant bio-markers from high-dimensional cancerous data employing a modified multi-objective meta-heuristic algorithm by Prajna Paramita Debata, Puspanjali Mohapatra

“…Here, the suggested algorithm has been compared with multi-objective chaotic Genetic Algorithm (MOCGA), multi-objective chaotic particle swarm optimization (MOCPSO), multi-objective Jaya (MOJaya), multi-objective PSO (MOPSO), and non-dominated sorting GA (NSGA-II) models. …”
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The prognostic predictive value of indirect bilirubin-inflammation score in patients with nasopharyngeal carcinoma by JI Huojin, LI Jun, LUO Yonglin, QIN Weiling, YE Yinxin, CAI Yonglin

“…Results By comparing 14 types of machine learning algorithms, the optimal model, oblique random survival forest, was selected to construct IBI score. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method centered on the initial meter gas production index and integrated multiple machine-learning algorithms. The results showed that: 1） The Beggs & Bill model and Gray model exhibited poor applicability for predicting the bottom-hole flowing pressure of deep CBM wells, while the single-phase gas model demonstrated reduced overall error as water production declined. …”
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High-Throughput Adaptive Co-Channel Interference Cancellation for Edge Devices Using Depthwise Separable Convolutions, Quantization, and Pruning by Mostafa Naseri, Eli De Poorter, Ingrid Moerman, H. Vincent Poor, Adnan Shahid

“…Overall, our findings underscore the feasibility of using optimized machine-learning models for interference cancellation in devices with limited resources.…”
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基于神经网络和遗传算法的多齿轮并联传动优化设计 by 杜子学, 赵大毅

“…Based on neural network and genetic algorithm,the optimal designed mathematical model of multi-gear parallel drive and transmission for a certain giant overload operation machine is established.In this optimized gear design,some vague string diagrams of input-output relationship as well as the neural networks fitting methods of discrete data are given,and then the optimizing calculation by applying genetic algorithm is conducted.The result shows that through the utilization of this method,not only the working efficiency could be promoted,but the result could also be reasonable and credible.…”
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Battery System Fault Detection: A Data-Driven Aggregation and Augmentation Strategy by Zhiming Zhang, Dan Zhang, Dejun Li, Yi Liu, Jiong Yang

“…Leveraging these enhanced datasets, this study develop an optimized Light Gradient Boosting Machine model specifically tailored for fault detection tasks. …”
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Symbolic Framework for Evaluation of NOMA Modulation Impairments Based on Irregular Constellation Diagrams by Nenad Stefanovic, Vladimir Mladenovic, Borisa Jovanovic, Ron Dabora, Asutosh Kar

“…The advantages of the proposed approach include intuitive symbolic modeling in a dynamic framework for NOMA signals; efficient, more accurate, and less time-consuming design flow; and generation of synthetic training data for machine-learning models that could be used for system optimization in real-world use cases.…”
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