Artificial Intelligence and Internet of Things Integration in Pharmaceutical Manufacturing: A Smart Synergy by Reshma Kodumuru, Soumavo Sarkar, Varun Parepally, Jignesh Chandarana

“…<b>Background:</b> The integration of artificial intelligence (AI) with the internet of things (IoTs) represents a significant advancement in pharmaceutical manufacturing and effectively bridges the gap between digital and physical worlds. With AI algorithms integrated into IoTs sensors, there is an improvement in the production process and quality control for better overall efficiency. …”
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A Signal Subspace Speech Enhancement Approach Based on Joint Low-Rank and Sparse Matrix Decomposition by Chengli SUN, Jianxiao XIE, Yan LENG

“…However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within enhanced speech in low signal-to-noise ratio (SNR) situations. …”
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Introduction to the Special Thematic Issue "Virtual Reality and Eye Tracking" by Béatrice Hasler, Rudolf Groner

“… Technological advancements have made it possible to integrate eye tracking in virtual reality (VR) and augmented reality (AR). Many new VR/AR headsets already include eye tracking as a standard feature. …”
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Unconditional advantage of noisy qudit quantum circuits over biased threshold circuits in constant depth by Michael de Oliveira, Sathyawageeswar Subramanian, Leandro Mendes, Min-Hsiu Hsieh

“…Furthermore, steady advances in classical algorithms and machine learning make the issue of provable, practically demonstrable quantum advantage a moving target. …”
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Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review by Anastasios Anastasiadis, Antonios Koudonas, Georgios Langas, Stavros Tsiakaras, Dimitrios Memmos, Ioannis Mykoniatis, Evangelos N. Symeonidis, Dimitrios Tsiptsios, Eliophotos Savvides, Ioannis Vakalopoulos, Georgios Dimitriadis, Jean de la Rosette

“…Results: A total of 69 studies were identified. The main subjects were related to the detection of urinary stones, the prediction of the outcome of conservative or operative management, the optimization of operative procedures, and the elucidation of the relation of urinary stone chemistry with various factors. …”
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Interpretable machine learning model of effective mass in perovskite oxides with cross-scale features by Changjiao Li, Zhengtao Huang, Hua Hao, Zhonghui Shen, Guanghui Zhao, Ben Xu, Hanxing Liu

“…However, previous works were mainly devoted to algorithm improvement, while the essential multi-scale characteristics are not well addressed. …”
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SMART HYBRID MODELS FOR IMPROVED BREAST CANCER DETECTION by Nageswara Rao Gali, Panduranga Vital Terlapu, Yasaswini Mandavakuriti, Sai Manoj Somu, Madhavi Varanasi, Vijay Telugu, Maheswara Rao V V R

“…Mitigating this threat focuses on early detection and prevention by adopting novel techniques. Many researchers have turned to Machine Learning algorithms to develop prognosis systems. …”
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Short-Term Energy Consumption Prediction in Korean Residential Buildings Using Optimized Multi-Layer Perceptron by Fazli Wahid, Do Hyeun Kim

“…Two main training algorithms namely scaled conjugate gradient, and Levenberg-Marquardt back propagation algorithms were used for training. …”
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Charting the path forward: CT image quality assessment - an in-depth review by Siyi Xun, Qiaoyu Li, Xiaohong Liu, Pu Huang, Guangtao Zhai, Yue Sun, Peter H. N. de With, Mingxiang Wu, Tao Tan

“…It helps improve the accuracy of CT scanning equipment and the performance of CT system reconstruction algorithms, and provides a new idea for CT image processing algorithms. …”
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Detection of Mycotoxins in Cereal Grains and Nuts Using Machine Learning Integrated Hyperspectral Imaging: A Review by Md. Ahasan Kabir, Ivan Lee, Chandra B. Singh, Gayatri Mishra, Brajesh Kumar Panda, Sang-Heon Lee

“…This review explores hyperspectral imaging (HSI) integrated with machine learning (ML) algorithms as a promising approach for detecting and quantifying mycotoxins in cereal grains and nuts. …”
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Error Data Analytics on RSS Range-Based Localization by Shuhui Yang, Zimu Yuan, Wei Li

“…The significance of our discovery has two folds: First, we present a general expression for localization error data analytics, which can explain and predict the accuracy of range-based localization algorithms; second, the further study on the general analytics expression and its minimum can be used to optimize current localization algorithms.…”
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exoALMA. IX. Regularized Maximum Likelihood Imaging of Non-Keplerian Features by Brianna Zawadzki, Ian Czekala, Maria Galloway-Sprietsma, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Himanshi Garg, Cassandra Hall, Thomas Hilder, Jane Huang, John D. Ilee, Andrea Isella, Andrés F. Izquierdo, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan A. Loomis, Ryuta Orihara, Christophe Pinte, Daniel J. Price, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard-Fernandez, David J. Wilner, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida

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Analysis of Synergistic Changes in PM_2.5 and O₃ Concentrations Based on Structural Equation Model Study by Zhangwen Su, Liming Yang, Yimin Chen, Rongyu Ni, Wenlong Wang, Honghao Hu, Bin Xiao, Sisheng Luo

“…In areas without coordinated changes, the main impact of meteorological factors remains unchanged, and the relationship between the two anthropogenic emission sources and their effects on PM_2.5 and O₃ are complex, with different directions and levels involved. …”
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SkinSage XAI: An explainable deep learning solution for skin lesion diagnosis by Geetika Munjal, Paarth Bhardwaj, Vaibhav Bhargava, Shivendra Singh, Nimish Nagpal

“…While deep learning algorithms have greatly enhanced the categorization of skin lesions, the black‐box nature of many models limits interpretability, posing challenges for dermatologists. …”
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Suppressing the Endogenous Negative Influence Through Node Intervention in Social Networks by Satoshi Furutani, Tatsuhiro Aoshima, Toshiki Shibahara, Mitsuaki Akiyama, Masaki Aida

“…We prove that this problem is NP-hard and propose approximation algorithms to identify optimal intervention nodes that minimize the negative influence. …”
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An Effective Ensemble Approach for Preventing and Detecting Phishing Attacks in Textual Form by Zaher Salah, Hamza Abu Owida, Esraa Abu Elsoud, Esraa Alhenawi, Suhaila Abuowaida, Nawaf Alshdaifat

“…Phishing email assaults have been a prevalent cybercriminal tactic for many decades. Various detectors have been suggested over time that rely on textual information. …”
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Labelling Training Samples Using Crowdsourcing Annotation for Recommendation by Qingren Wang, Min Zhang, Tao Tao, Victor S. Sheng

“…Among the ground truth inference algorithms, both HILED and HILI improve the performance of baselines; meanwhile, HILED performs better than HILI.…”
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An Efficient and Fast Model Reduced Kernel KNN for Human Activity Recognition by Zongying Liu, Shaoxi Li, Jiangling Hao, Jingfeng Hu, Mingyang Pan

“…With accumulation of data and development of artificial intelligence, human activity recognition attracts lots of attention from researchers. Many classic machine learning algorithms, such as artificial neural network, feed forward neural network, K-nearest neighbors, and support vector machine, achieve good performance for detecting human activity. …”
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Secret Key Generation Protocol for Optical OFDM Systems in Indoor VLC Networks by Yahya Mohammed Al-Moliki, Mohammed Thamer Alresheedi, Yahya Al-Harthi

“…Nevertheless, the common keys generation algorithms can be very complex and costly in many setups. …”
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Epileptic Seizure Detection in EEG Signals Using Machine Learning and Deep Learning Techniques by Hepseeba Kode, Khaled Elleithy, Laiali Almazaydeh

“…Machine Learning (ML) and Deep learning (DL) algorithms have emerged as powerful feature extraction and classification tools in EEG signal analysis. …”
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