Early Detection of Parkinson’s Disease Using AI Techniques and Image Analysis by Marilena Ianculescu, Corina Petean, Virginia Sandulescu, Adriana Alexandru, Ana-Mihaela Vasilevschi

“…Methods: The best approach is selected to be integrated in a neurodegenerative disease management platform called NeuroPredict. The most innovative aspects of the presented approaches are related to the employed feature extraction techniques that convert hand-drawn spirals into a frequency spectra, so that frequency features may be extracted and utilized as inputs for various classification algorithms. …”
Get full text

Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model by Victor Fernandez, Virgilio Pérez, Rosa Roig

“…This study presents a comprehensive mobility network model designed to predict and optimize the energy supply for FEVs within smart cities. …”
Get full text

Circulating MicroRNAs as Novel Biomarkers in Risk Assessment and Prognosis of Coronary Artery Disease by Chiara Vavassori, Eleonora Cipriani, Gualtiero Ivanoe Colombo

“…Nevertheless, available cardiovascular risk prediction algorithms still miss a significant portion of individuals at-risk. …”
Get full text

Employing Data Mining Techniques and Machine Learning Models in Classification of Students’ Academic Performance. by Hussein, Alkattan, Alhumaima, Ali Subhi, Oluwaseun, Adelaja A., Abotaleb, Mostafa, Mijwil, Maad M., Pradeep, Mishra, Sekiwu, Denis, Bamwerinde, Wilson, Turyasingura, Benson

“…The study deals with the use of data mining techniques to build a classification model to predict students' academic performance. The research indicates that the use of machine learning models and data mining methods can reveal hidden patterns and relationships in big data, making them indispensable tools in the field of education analysis. …”
Get full text

Robust time series analysis for forecasting photovoltaic energy yield by Sapundzhi Fatima, Chikalov Aleksandar, Georgiev Slavi, Georgiev Ivan, Todorov Venelin

“…This study introduces an approach to forecasting the power output of a photovoltaic (PV) system by employing an ARIMA-based algorithm. Two distinct ARIMA models were designed – one generated via SPSS and one selected by the researchers. …”
Get full text

A framework based on mechanistic modelling and machine learning for soil moisture estimation by Sabri Kanzari, Sana Ben Mariem, Samir Ghannem, Safouane Mouelhi, Hiba Ghazouani, Bechir Ben Nouna

“…These values were used as inputs to the Hydrus 1D model to generate soil water content profiles over a 27-year period. 109 profiles were calculated using machine learning algorithms (regression trees; random forest; support vector machine) to predict soil moisture content from daily values of rainfall and evaporation. …”
Get full text

Field calibration of fine particulate matter low-cost sensors in a highly industrialized semi-arid conurbation by Mariana Villarreal-Marines, Michael Pérez-Rodríguez, Yasmany Mancilla, Gabriela Ortiz, Alberto Mendoza

“…We also tested the Extreme Gradient Boosting (XGBoost) algorithm for classification and field calibration of the PM2.5 data derived from the LCS. …”
Get full text

Identification of Papua Cenderawasih Batik Motifs using Local Binary Pattern and K-Nearest Neighbor by Dian Dwi Ariani, Sitti Zuhriyah, Eva Yulia Puspaningrum, Mahabintang Pallawabonang

“…Future research could improve model accuracy by utilizing larger data sets and classification algorithms to make the models more accurate.…”
Get full text

An Innovative Proposal for Developing a Dynamic Urban Growth Model Through Adaptive Vector Cellular Automata by Ahmet Emir Yakup, Ismail Ercument Ayazli

“…For the simulation phase, an adaptive VCA-based urban growth model was developed to predict LULC changes through to 2040. The results demonstrate that the proposed algorithm can achieve a satisfactory level of accuracy in modeling urban growth.…”
Get full text

From word models to executable models of signaling networks using automated assembly by Benjamin M Gyori, John A Bachman, Kartik Subramanian, Jeremy L Muhlich, Lucian Galescu, Peter K Sorger

“…Abstract Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. …”
Get full text

Probabilistic Routing Based on Two-Hop Information in Delay/Disruption Tolerant Networks by Xu Wang, Rongxi He, Bin Lin, Ying Wang

“…Probabilistic routing protocol using history of encounters and transitivity (PRoPHET) is an efficient history-based routing protocol specifically proposed for DTNs, which only utilizes the delivery predictability of one-hop neighbors to make a decision for message forwarding. …”
Get full text

Pig behavior recognition and disease warning based on compressed sensing and long-short term memory network by Ren Wang, Mingdong Zhao

“…The improved k-means clustering algorithm is combined with convolutional neural network and long and short term memory network to provide early warning for pig diseases. …”
Get full text

Historical Reconstruction of Astronaut Cancer Risk: Context for Recent Solar Minima by Tony C. Slaba

“…To provide additional context for this level of variation, two different nuclear interaction models are used within the radiation transport algorithms used to propagate GCR ions and secondary particles through shielding and tissue. …”
Get full text

Risk Assessment for Water Disaster of Karst Tunnel Based on the Weighting of Reliability Measurement and Improved Extension Cloud Model by Yingli Jiang, Jie Cui, Hao Liu, Yanlong Zhang

“…Secondly, according to the two different entropy algorithms of the extension cloud model, an improved extension cloud model is proposed based on the entropy algorithm fusion of game theory. …”
Get full text

Machine learning discovery of the dielectric properties of strontium-containing condensed matter by Dongyang Huang, Jiaxing Fu, Chenghao Yu

“…Traditional theoretical predictions or first-principles calculations of dielectric constants are often challenging and require significant time and computational resources. …”
Get full text

A machine learning-derived angiogenesis signature for clinical prognosis and immunotherapy guidance in colon adenocarcinoma by Hengrui Du, Haochen Wang, Yuxiang Chen, Xixi Zhou

“…The optimal CARS constructed using the RSF + StepCox [forward] algorithm had superior performance for clinical prognostic prediction and served as an independent risk predictor for COAD. …”
Get full text

Variational Approach for Learning Community Structures by Jun Jin Choong, Xin Liu, Tsuyoshi Murata

“…More specifically, supervised and semisupervised learning tasks such as link prediction and node classification have achieved remarkable results. …”
Get full text

An explainable and federated deep learning framework for skin cancer diagnosis. by Shuvo Biswas, Sajeeb Saha, Muhammad Shahin Uddin, Rafid Mostafiz

“…To ensure model interpretability, an XAI-based algorithm named Local Interpretable Model-Agnostic Explanations (LIME) was used to explain the predictions of the proposed framework. …”
Get full text

Multisource Heterogeneous Sensor Processing Meets Distribution Networks: Brief Review and Potential Directions by Junliang Wang, Ying Zhang

“…Through a brief analysis of existing technologies and algorithms, this article reviews the technological development of MSH data analysis in DNs. …”
Get full text

Research on flight detection and data compliance analysis methods for ice meteorological by DING Junliang

“…Domestic icing meteorological prediction algorithms are calibrated and verified, and safety control strategies and risk degradation measures for natural icing flight test are explored. …”
Get full text