Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management by William Alberto Cruz Castañeda, Pedro Bertemes Filho

“…The study also establishes a baseline of twelve regression algorithms to assess the non-invasive glucose prediction performance regarding the mean squared error, root mean squared error, and r-squared score, and the catboost regressor outperforms the other models with 218.91 and 782.30 in MSE, 14.80 and 27.97 in RMSE, and 0.81 and 0.31 in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>, respectively, on training and test sets. …”
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A strategy for network multi-layer information fusion based on multimodel in user emotional polarity analysis by Ronghua Wang, Peng Zhuang

“…Despite the large number of negative users, the frequency of connections between active users was significantly higher than between negative users. Multiple algorithms were utilized for emotional analysis and prediction. …”
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An Expert Fitness Diagnosis System Based on Elastic Cloud Computing by Kevin C. Tseng, Chia-Chuan Wu

“…In addition, an elastic algorithm based on Poisson distribution is presented to allocate computation resources dynamically. …”
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Error-Mask-Adaptive Dynamic Filtering for Image Inpainting by Keunsoo Ko, Seunggyun Woo, Chang-Su Kim

“…A novel error-mask-adaptive dynamic filtering (EMDF) algorithm is proposed in this paper, which uses a continuous error mask to inpaint an image adaptively and faithfully. …”
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Perceived age estimation from facial image and demographic data in young and middle-aged South Korean adults by Ilkoo Ahn, Younghwa Baek, Bok-Nam Seo, Su Eun Lim, Kyoungsik Jung, Ho Seok Kim, Jeongkyun Kim, Sukyung Lee, Siwoo Lee

“…Thus, this study aimed to propose a novel perceived age estimation algorithm to meet the need for an objective method to predict perceived age. …”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…Interventions Participants were block randomised by a computer algorithm (stratified by severity and centre) to one of three trial arms: (1) usual care, (2) usual care + internet intervention and (3) usual care + internet intervention + telephone support. …”
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A Hybrid Deep Learning–Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Survivors of Cancer: Cross-Sectional Study by Tracy Huang, Chun-Kit Ngan, Yin Ting Cheung, Madelyn Marcotte, Benjamin Cabrera

“…ObjectiveThis study aimed to create a new feature selection algorithm to improve the performance of machine learning classifiers to predict negative long-term behavioral outcomes in survivors of cancer. …”
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Contrail altitude estimation using GOES-16 ABI data and deep learning by V. R. Meijer, V. R. Meijer, S. D. Eastham, S. D. Eastham, S. D. Eastham, I. A. Waitz, S. R. H. Barrett, S. R. H. Barrett

“…The altitude estimation algorithm outputs probability distributions for the contrail top altitude in order to represent predictive uncertainty. …”
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Research on Forecasting Sales of Pure Electric Vehicles in China Based on the Seasonal Autoregressive Integrated Moving Average–Gray Relational Analysis–Support Vector Regression M... by Ru Yu, Xiaoli Wang, Xiaojun Xu, Zhiwen Zhang

“…Secondly, variables that were highly correlated with sales were analyzed using gray relational analysis (GRA) and utilized as input parameters for the support vector regression (SVR) model, which was constructed to optimize sales predictions for EVs. Finally, a combined model incorporating different algorithms was verified against market sales data to explore the optimal sales prediction approach. …”
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Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

“…This paper applies machine learning models to predict travel time reliability in transportation networks, using XGBoost, LightGBM, and CatBoost optimized with seven metaheuristic algorithms. …”
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Advancement of artificial intelligence based treatment strategy in type 2 diabetes: A critical update by Aniruddha Sen, Palani Selvam Mohanraj, Vijaya Laxmi, Sumel Ashique, Rajalakshimi Vasudevan, Afaf Aldahish, Anupriya Velu, Arani Das, Iman Ehsan, Anas Islam, Sabina Yasmin, Mohammad Yousuf Ansari

“…At the same time, the rapidly increasing role of AI in diabetes care is woven into the story, mainly targeting how insulin therapy can be modified and personalized through algorithms and predictive modelling. It leaves a deep review of their pre-existing synergies, which helps understand how collaborative opportunities will unlock the future of T2DM care. …”
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Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation. by Wenjun Zhao, Erica Larschan, Björn Sandstede, Ritambhara Singh

“…Our algorithm overcomes this limitation by estimating gene velocities using optimal transport. …”
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Ga-based MPC for satellite’s attitude and orbit control by Prasitthichai Naronglerdrit, Manukid Parnichkun

“…We propose a novel method that utilizes a nonlinear control strategy optimized by a Genetic Algorithm (GA) in conjunction with Model Predictive Control (MPC), focusing on managing both attitude and orbit simultaneously. …”
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Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
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Performance of quantum approximate optimization with quantum error detection by Zichang He, David Amaro, Ruslan Shaydulin, Marco Pistoia

“…Abstract The quantum approximate optimization algorithm (QAOA) is a promising candidate for scaling up to tackle real-world applications. …”
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Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
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Fingernail analysis management system using microscopy sensor and blockchain technology by Shih Hsiung Lee, Chu Sing Yang

“…The performance of each feature extraction algorithm was analyzed for the two classifiers and the deep neural network algorithm was used comparatively. …”
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A Statistical Analysis Based Probabilistic Routing for Resource-Constrained Delay Tolerant Networks by Jixing Xu, Jianbo Li, Shan Jiang, Chenqu Dai, Lei You

“…In this paper, we propose an improved probabilistic routing algorithm that fully takes into account message's time-to-live when predicting the delivery probability. …”
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Addressing imbalanced data classification with Cluster-Based Reduced Noise SMOTE. by Javad Hemmatian, Rassoul Hajizadeh, Fakhroddin Nazari

“…CRN-SMOTE combines SMOTE for oversampling minority classes with a novel cluster-based noise reduction technique. In this cluster-based noise reduction approach, it is crucial that samples from each category form one or two clusters, a feature that conventional noise reduction methods do not achieve. …”
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Free field Active Noise Control system development using a 3D Finite Element based approach by Budnik Maximilian, Mees Valentin

“…It further allows for the optimization of control algorithms, evaluation of the attenuation performance, and methodical iteration of the overall concept design. …”
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