PM2.5 IoT Sensor Calibration and Implementation Issues Including Machine Learning by Wacharapong Srisang, Krisanadej Jaroensutasinee, Mullica Jaroensutasinee, Chonthicha Khongthong, John Rex P. Piamonte, Elena B. Sparrow

“…The data from the Plantower PMS3003 sensor were then compared to the Davis AirLink values using calibration curves created by machine learning algorithms. …”
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Pathological omics prediction of early and advanced colon cancer based on artificial intelligence model by Zhe Wang, Yang Wu, Yingjie Li, Qingwen Wang, Hongfei Yi, Hongyan Shi, Xinyue Sun, Chengxiang Liu, Kuanyu Wang

“…Cellprofiler and CLAM tools were used to extract pathological features, and machine learning algorithms and deep learning algorithms were used to construct prediction models. …”
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Deep Learning-Based Cloud Detection for Optical Remote Sensing Images: A Survey by Zhengxin Wang, Longlong Zhao, Jintao Meng, Yu Han, Xiaoli Li, Ruixia Jiang, Jinsong Chen, Hongzhong Li

“…This review provides a comprehensive overview of cloud detection algorithms based on deep learning from the perspective of semantic segmentation, and elaborates on the research progress, advantages, and limitations of different categories in this field. …”
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Battery Cell Charging Behavior Analysis Using Constant Current and Constant Voltage Methods by Anna Cyntia, Muhammad Imran Hamid, Ayu Elsa Afriyanti

“…MATLAB is used in conjunction with certain mathematical algorithms, such as numerical integration and curve fitting, to simulate the charging process, utilizing parameters including a constant current of 1C and a voltage threshold of 4.2V. …”
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DEVELOPMENT OF A GRAVITATIONAL AND PENDULUM SOLAR TRACKER FOR STANDALONE PHOTOVOLTAIC PANELS by Jorge A. Wissmann, Carlos E. C. Nogueira, Marcelo M. M. Zampiva, Jair A. C. Siqueira, Doglas Bassegio

“…A tracking prototype was developed whose structure is classified as chronological due to its fixed rotation, manual as it requires daily adjustment, single-axis azimuthal, and "analog" as it lacks motors, sensors, or algorithms. The results showed that the developed tracking prototype achieved a 9.69% energy production increase during the research period, with peaks of 35.51% on sunny days, and a significant efficiency improvement during the early morning and late afternoon. …”
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Crack Detection in Civil Infrastructure: A Method-Scenario Review by Chang Haochen, Gu Weifan, Guo Baohua, Bassir David

“…This paper presents a systematic review of crack detection technologies organized under a novel “method-scenario” framework that categorizes techniques based on their underlying algorithms and the specific application contexts (e.g., pavements, bridges, tunnels, and specialized materials). …”
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Professional Judgment and Skepticism Amidst the Interaction of Artificial Intelligence and Human Intelligence by Delia DELIU

“…However, it also raises ethical concerns regarding data privacy, algorithmic bias, and accountability. These concerns highlight the importance of maintaining human oversight and ethical standards in audit practices. …”
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Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification by Yunna Mentari Indah, Rafika Aristawidya, Anwar Fitrianto, Erfiani Erfiani, L.M. Risman Dwi Jumansyah

“…The study applied these algorithms to analyze the most influential variables affecting HDI. …”
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COVID-19 Pandemic Forecasting Using CNN-LSTM: A Hybrid Approach by Zuhaira M. Zain, Nazik M. Alturki

“…Along with recent advances in soft computing technology, researchers are now actively developing and enhancing different mathematical and machine-learning algorithms to forecast the future trend of this pandemic. …”
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Stock price prediction based on dual important indicators using ARIMAX: A case study in Vietnam by Wang Pai-Chou, Vo Tram Thi Hoai

“…To demonstrate the effectiveness of this method, we compared it with four other methods – long-short term memory, genetics algorithms with long-short term memory, XGBoost, and Meta Prophet – in predicting the next day’s closing price of the Vietnam stock index from January 2013 to April 2023. …”
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Edge vs. Cloud: Empirical Insights into Data-Driven Condition Monitoring by Chikumbutso Christopher Walani, Wesley Doorsamy

“…The tested induction machine fault diagnosis models are developed using popular algorithms, namely support vector machines, k-nearest neighbours, and decision trees. …”
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A Survey of Dental Caries Segmentation and Detection Techniques by Vincent Majanga, Serestina Viriri

“…It involves discussing the methods and algorithms used in segmenting and detecting dental caries. …”
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Experimental performance analysis of lightweight block ciphers and message authentication codes for wireless sensor networks by Sooyeon Shin, Minwoo Kim, Taekyoung Kwon

“…For resource-constrained nature of these special networks, the design of lightweight cryptography has become active research topic over the last several years. In this article, we provide experimental performance analysis of several lightweight block ciphers and message authentication codes to help for choosing better algorithms for wireless sensor networks in terms of efficiency. …”
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Student Dropout Prediction Using Random Forest and XGBoost Method by Lalu Ganda Rady Putra, Didik Dwi Prasetya, Mayadi Mayadi

“…The performance of Random Forest and XGBoost was compared based on accuracy, specificity, and sensitivity. …”
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A monitoring network SIMNet for weld penetration status based on multimodal fusion by Qi Jiang, Yiming Wang, Yan Kong, Yu Liu, Ce Ma

“…The experimental results demonstrate that SIMNet achieves the best performance with a mean squared error (MSE) of 0.1141 mm, compared to other mainstream algorithms. Furthermore, the inference speed with multimodal input reaches 60 frames per second (FPS), enabling quantitative and real-time multimodal fusion intelligent penetration state monitoring.…”
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A New Signal Processing Method for Time-of-Flight and Center Frequency Estimation by Olgirdas Tumšys

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Evaluation of the ecological niche model approach in spatial conservation prioritization. by Fumiko Ishihama, Akio Takenaka, Hiroyuki Yokomizo, Taku Kadoya

“…We evaluated three ENM algorithms (GLM, GAM, and random forests). We used virtual community data generated by simulation for the evaluation. …”
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MiR-124 Radiosensitizes human colorectal cancer cells by targeting PRRX1. by Yuqin Zhang, Lin Zheng, Jing Huang, Fei Gao, Xiaoshan Lin, Lian He, Dan Li, Zhijun Li, Yi Ding, Longhua Chen

“…MicroRNAs (miRNAs) are involved in essential biological activities, including chemoresistance and radioresistance. Several research studies have indicated that miRNA played an important role in sensitizing cellular response to ionizing radiation (IR). …”
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Evaluating the Efficacy of Adjuvant Radiotherapy in the Management of Advanced Oral Cancer Cases by Radhika Thakkar, M. Rama Nalini, Rohit K. Jha, Mudita Chaturvedi, Raja S. Prathigudupu, S. Hemavathy, B S Dayanithi

“…To improve treatment algorithms and investigate cutting-edge therapeutic techniques for this difficult condition, further research is necessary.…”
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Stroke Risk Classification Using the Ensemble Learning Method of XGBoost and Random Forest by Gullam Almuzadid, Egia Rosi Subhiyakto

“…The proposed approach significantly improved predictive accuracy compared to previous research, demonstrating the effectiveness of ensemble learning and preprocessing methods in developing reliable, high-performing machine learning models for early stroke risk assessment.…”
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