Quality assessment of chicken using machine learning and electronic nose by Hassan Anwar, Talha Anwar

“…This study investigates the use of an electronic nose system—a sensor array that detects odors and generates data, which is then analyzed by machine learning algorithms to predict chicken freshness. …”
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Machine learning supported ground beef freshness monitoring based on near‐infrared and paper chromogenic array by Yihang Feng, Yi Wang, Burcu Beykal, Zhenlei Xiao, Yangchao Luo

“…Recent advancements in spectroscopic and chromogenic sensor array technologies have opened up new avenues for monitoring meat quality parameters, offering the potential for real‐time, accurate, and cost‐effective solutions. …”
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Electronic nose and machine learning for modern meat inspection by Ivan Shtepliuk, Guillem Domènech-Gil, Viktor Almqvist, Arja Helena Kautto, Ivar Vågsholm, Sofia Boqvist, Jens Eriksson, Donatella Puglisi

“…In this study, we propose a novel method to modernize meat inspection using an electronic nose combined with machine learning (ML), with focus on pig meat as a case study. …”
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Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…Characteristic gas detection can be an efficient way to predict the degree of thermal runaway of a lithium battery. In this work, a sensor array consisting of three commercial MOS sensors was employed to discriminate between three target gases, CO, H₂ and a mixture of the two, which are characteristic gases released during the thermal runaway of lithium batteries. …”
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Applications of Machine Learning in Food Safety and HACCP Monitoring of Animal-Source Foods by Panagiota-Kyriaki Revelou, Efstathia Tsakali, Anthimia Batrinou, Irini F. Strati

“…Several non-destructive techniques are presented, including spectroscopic methods, smartphone-based sensors, paper chromogenic arrays, machine vision, and hyperspectral imaging combined with ML algorithms. …”
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Synthesis and characterization of hematite nanomaterials imprinted with acetone, ethanol and methanol for AI-Based IoT gas sensor arrays by Rana M. Abdelghani, Abd El-Hady B. Kashyout, Iman Morsi, Taha Elsayed Taha, Naglaa F. Soliman, Walid El-Shafai

“…The dataset, obtained from sensor responses to different concentrations of acetone, ethanol, and methanol, was analyzed using multiple hybrid machine learning models, including CNN-LSTM, PCA-CNN-LSTM, PCA-XGBoost, Random Forest (RF), RF-GB, RF-GB-NN, and KNN. …”
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Hand Gesture Recognition on Edge Devices: Sensor Technologies, Algorithms, and Processing Hardware by Elfi Fertl, Encarnación Castillo, Georg Stettinger, Manuel P. Cuéllar, Diego P. Morales

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Assessing Data Fusion in Sensory Devices for Enhanced Prostate Cancer Detection Accuracy by Jeniffer Katerine Carrillo Gómez, Carlos Alberto Cuastumal Vásquez, Cristhian Manuel Durán Acevedo, Jesús Brezmes Llecha

“…The data fusion was assessed and it successfully improved the accuracy of detecting prostate-related conditions and distinguishing healthy patients, achieving the highest success rate possible (100%) in classification through machine learning methods, outperforming the results obtained from individual electronic devices.…”
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Machine learning algorithms for manufacturing quality assurance: A systematic review of performance metrics and applications by Ashfakul Karim Kausik, Adib Bin Rashid, Ramisha Fariha Baki, Md Mifthahul Jannat Maktum

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Early Detection of Alzheimer’s Disease via Machine Learning-Based Microwave Sensing: An Experimental Validation by Leonardo Cardinali, Valeria Mariano, David O. Rodriguez-Duarte, Jorge A. Tobón Vasquez, Rosa Scapaticci, Lorenzo Crocco, Francesca Vipiana

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Early diagnosis of lung cancer using a sensor gas analysis complex: case report by E. O. Rodionov, D. E. Kulbakin, D. V. Podolko, E. V. Obkhodskaya, A. V. Obkhodskiy, S. V. Miller, A. A. Mokh, V. I. Sachkov, A. S. Popov, V. I. Chernov

“…Conclusion. Machine learning algorithms are actively used to diagnose socially significant diseases. the platforms being developed based on arrays of chemical sensors with data analysis using a neural network are promising candidates for implementation in screening activities.…”
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Development of Self-Powered Energy-Harvesting Electronic Module and Signal-Processing Framework for Wearable Healthcare Applications by Jegan Rajendran, Nimi Wilson Sukumari, P. Subha Hency Jose, Manikandan Rajendran, Manob Jyoti Saikia

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Electronic Nose System Based on Metal Oxide Semiconductor Sensors for the Analysis of Volatile Organic Compounds in Exhaled Breath for the Discrimination of Liver Cirrhosis Patient... by Makhtar War, Benachir Bouchikhi, Omar Zaim, Naoual Lagdali, Fatima Zohra Ajana, Nezha El Bari

“…This study included 55 participants: 27 LC patients and 28 HCs. Sensor’s measurement data were analyzed using machine learning techniques, such as principal component analysis (PCA), discriminant function analysis (DFA), and support vector machines (SVMs) that were utilized to uncover meaningful patterns and facilitate accurate classification of sensor-derived information. …”
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Heuristic XAI: AIME and HMM Integration Improved-Feature-Importance Assessment Through Heuristics by Takafumi Nakanishi, Ponlawat Chophuk, Krisana Chinnasarn

“…The explainability of AI and machine learning models has become crucial, drawing significant attention to explainable AI (XAI) technologies. …”
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Deep Learning‐Based 3D Microseismic Event Direct Location Using Simultaneous Surface and Borehole Data by Yuanyuan Yang, Omar M. Saad, Tariq Alkhalifah

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Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) by Montaser N.A. Ramadan, Mohammed A.H. Ali, Shin Yee Khoo, Layth Hamad, Mohammad Alkhedher

“…The device's innovative design integrates an advanced sensor array with seamless Bluetooth connectivity, offering real-time data synchronization with mobile applications. …”
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