A Novel Approach to the Prediction of Alzheimer’s Disease Progression by Leveraging Neural Processes and a Transformer Encoder Model by Emad Al-Anbari, Hossein Karshenas, Bijan Shoushtarian

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Machine Learning Models and Mathematical Approaches for Predictive IoT Smart Parking by Vesna Knights, Olivera Petrovska, Jasmina Bunevska-Talevska, Marija Prchkovska

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STID-Net: Optimizing Intrusion Detection in IoT with Gradient Descent by James Deva Koresh Hezekiah, Usha Nandini Duraisamy, Kalaichelvi Nallusamy, Avudaiammal Ramalingam, Saranya Chandran, Murugesan Rajeswari Thiyagupriyadharsan, Periasamy Selvaraju, Rajagopal Maheswar

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A meta-analysis for the nighttime light remote sensing data applied in urban research: Key topics, hotspot study areas and new trends by Baiyu Dong, Ruyi Zhang, Sinan Li, Yang Ye, Chenhao Huang

“…Although there are currently some review articles focusing on NTL-based urban studies, they lack visual analysis of research keywords based on co-occurrence analysis, as well as the research topics and changes of global countries and regions. …”
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A Time-resolved High-resolution Spectroscopic Analysis of Ionized Calcium and Dynamical Processes in the Ultra-hot Jupiter HAT-P-70 b by Adam B. Langeveld, Emily K. Deibert, Mitchell E. Young, Ernst de Mooij, Ray Jayawardhana, Chris Simpson, Jake D. Turner, Laura Flagg

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TENOR AS A MULTIMODAL REGISTER CHARACTERISTIC OF THE INSTAGRAM PROFILE (a compared analysis of Queen Rania’s official website and Instagram profile in Arabic and English) by Oksana A. Babelyuk, Yuliya Ya. Zaza

“…The applied socio- semantic analysis of multimodal signs on Queen Rania’s profile revealed a correlation between the interpersonal and ideational functions. …”
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Time Series Modelling of the Caspian Kutum (Rutilus frisii) Catch Using SARIMA Model by Fateh Moezzi, Hadi Poorbagher, Soheil Eagderi, Jahangir Feghhi

“…There were decreasingtrends in its catch levels in the last years. Identifying temporal trends of its catch could helpadopt proper plans to maintain the stocks of this important species and achieve sustainableexploitation goals. …”
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Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognition by Zeinab Hassani, Davud Mohammadpur, Hossein Safari

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Proprioceptive Training Study for the Optimization of the 110 M. Hurdles Technique by S. Alecu, D. Ionescu-Bondoc, A. Onea, F.B. Waer

“…Our study aims to quantify the technical performance of the hurdle step via biomechanical analysis. This involves measuring kinematic parameters and their association with the enhancement of coordination abilities, derived from tailored proprioceptive training. …”
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Time-Series Autoregressive Models for Point and Interval Forecasting of Raw and Derived Commercial Near-Infrared Spectroscopy Measures: An Exploratory Cranial Trauma and Healthy Co... by Amanjyot Singh Sainbhi, Logan Froese, Kevin Y. Stein, Nuray Vakitbilir, Rakibul Hasan, Alwyn Gomez, Tobias Bergmann, Noah Silvaggio, Mansoor Hayat, Jaewoong Moon, Frederick A. Zeiler

“…Further work is required to assess the ability to forecast high-frequency NIRS signals using ARIMA and ARIMA-variant models in healthy and cranial trauma populations.…”
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An Intelligent Method for Day-Ahead Regional Load Demand Forecasting via Machine-Learning Analysis of Energy Consumption Patterns Across Daily, Weekly, and Annual Scales by Monica Borunda, Arturo Ortega Vega, Raul Garduno, Luis Conde, Manuel Adam Medina, Jeannete Ramírez Aparicio, Lorena Magallón Cacho, O. A. Jaramillo

“…Before training, the load dataset is grouped by its statistical seasonality through K-means clustering analysis. Clustering load demand, along with similar-day data management, enables more focused training of the LSTM network on uniform data subsets, enhancing the model’s ability to capture temporal patterns and reducing the complexity associated with high variability in demand data. …”
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Robust Land-Surface Parameterisation for Repeated Topographic Surveys in Dynamic Environments with Adaptive State-Space Models by Daniel R. Newman, Yuichi S. Hayakawa

“…The results demonstrated that adaptive Kalman filters address challenges related to the sensitivity of conventional Kalman filter performance to sub-optimal parameterisation, and they are robust estimators for both terrain analysis and surface change analysis when multiple surveys are available. …”
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Parameter optimisation for a physical model of the vocal system by Mateo Cámara, José Luis Blanco, Joshua D. Reiss

“…Optimisation is performed over time windows to ensure temporal coherence, introducing modifications to SOTA objective metrics. …”
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A hybrid deep learning model for predicting atmospheric corrosion in steel energy structures under maritime conditions based on time-series data by Mohamed El Amine Seghier Ben, Tam T. Truong, Christian Feiler, Daniel Höche

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Gait analysis with smart insoles can identify patients at risk of tibial shaft fracture nonunion as early as six weeks after surgery: longitudinal and cross-sectional study by Elke Warmerdam, Marcel Orth, Max Müller, Tim Pohlemann, Bergita Ganse, Bergita Ganse

“…Unfortunately, it often takes months of observation until the indication for revision surgery or other interventions is given, which is why additional methods are desirable to enhance the ability to predict and prevent nonunion earlier.ObjectiveAs gait patterns and subjective outcomes obtained by questionnaires improved during regular fracture healing, the aim of this study was to determine whether gait analyses with instrumented insoles and patient-reported outcome measurement information system (PROMIS) questionnaires could be used to detect patients at risk of developing nonunion during the healing phase after tibial shaft fracture.MethodsData were collected from a longitudinal and a cross-sectional tibial fracture cohort via gait analysis with instrumented insoles (OpenGO, Moticon GmbH, Munich, Germany) and in addition via PROMIS questionnaires. …”
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COMMUNICATION TOPICS AND STRATEGIES IN E-MAIL CONSULTATION: COMPARISON BETWEEN AMERICAN AND INTERNATIONAL UNIVERSITY STUDENTS by Sigrun Biesenbach-Lucas

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Assessing dynamic brain activity during verbal associative learning using MEG/fMRI co-processing by Sangeeta Nair, Jerzy P. Szaflarski, Yingying Wang, Diana Pizarro, Jeffrey F. Killen, Jane B. Allendorfer

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Associations between previous local health expenditures and COVID-19 mortality outcomes large cities in the united states: results from a forward-selecting linear regression analys... by Matthew R Boyce, John Kraemer, Rebecca Katz

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A study of dynamic functional connectivity changes in flight trainees based on a triple network model by Lu Ye¹, Liya Ba¹, Dongfeng Yan¹

“…Independent component analysis (ICA), sliding window, and K-means clustering approaches were utilized for evaluating functional network connectivity (FNC) and temporal metrics based on the triple networks. …”
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Large Pretrained Foundation Model for Key Performance Indicator Multivariate Time Series Anomaly Detection by Xu Wang, Qisheng Xu, Kele Xu, Ting Yu, Bo Ding, Dawei Feng, Yong Dou

“…Yet, the development of effective deep learning models is hindered by several challenges: scarce and complex labeled data, noise interference from data handling, the necessity to capture temporal dependencies in time series KPI data, and the complexity of multivariate data analysis. …”
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