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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Approaches to Translation in the Context of Theory of Speech Activity by Serhii Zasiekin

“…However, it is important to bear in mind that many of the ideas in the cognitive literature are mainly rooted in the psycholinguistic approaches to translation. …”
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Filtering Techniques To Reduce Speckle Noise And Image Quality Enhancement Methods On Porous Silicon Images Layers by Tifouti Issam, Rahmouni Salah, Meriane Brahim

“…Recently, many studies have examined filters for reducing or removing speckle noise, which is inherent to different images types such as Porous Silicon (PS) images, in order to ameliorate the metrological evaluation of their applications. …”
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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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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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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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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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Energy-Efficient model for integrated berth allocation and quay crane management by Saeedeh Khalilpoor, Mehdi A. Kamran, Reza Babazadeh, Reza Kia

“…Several numerical experiments in different dimensions are defined and implemented with both algorithms. The results analysis gives an overall perspective, while both algorithms show their value and strong points and weaknesses in meeting demanding requirements of modern container terminal logistics. …”
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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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Architecture of the discrete sosine transformation processor for image compression systems on the losless-to-lossy circuit by V. V. Kliuchenia

“…It is the inequality of the addition and multiplication operations when they are implemented on FPGAs that caused the search for DCT algorithms with the smallest number of factors. However, even this is not enough, since the structure of the multiplier is many times more complex than the structure of the adder, which made it necessary to look for ways to transform without using multiplications at all. …”
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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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Registered report protocol: A scoping review to identify potential predictors as features for developing automated estimation of the probability of being frail in secondary care. by Dirk H van Dalen, Angèle P M Kerckhoffs, Esther de Vries

“…Frailty is associated with adverse health outcomes and increased healthcare costs. Many validated instruments to detect frailty have been developed. …”
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