A Hybrid Automata-Driven Machine Learning Framework for Real-Time Energy Optimization in Smart Buildings by Rikame Rajashri, Ranjan Mritunjay Kr., Jadhav Monali, Wankhede Shrushti, Bankar Sakshi, Bachhav Pranjal

“…These inputs train the predictive models like Random Forest, XGBoost, LightGBM, and Neural Networks to predict energy requirements. …”
Get full text

Integration of Accelerometers and Machine Learning with BIM for Railway Tight- and Wide-Gauge Detection by Jessada Sresakoolchai, Chayutpong Manakul, Ni-Asri Cheputeh

“…These data are processed and analyzed using supervised machine-learning algorithms to classify and predict potential tight- and wide-gauge events. …”
Get full text

An accuracy-privacy optimization framework considering user’s privacy requirements for data stream mining by Waruni Hewage, R. Sinha, M. Asif Naeem

“…Additionally, a data fitting module using kernel regression is integrated, a unique approach that predicts accuracy levels based on user-defined privacy thresholds. …”
Get full text

Design of Trabecular Bone Mimicking Voronoi Lattice-Based Scaffolds and CFD Modelling of Non-Newtonian Power Law Blood Flow Behaviour by Haja-Sherief N. Musthafa, Jason Walker

“…Designing scaffolds similar to the structure of trabecular bone requires specialised algorithms. Existing scaffold designs for bone tissue engineering have repeated patterns that do not replicate the random stochastic porous structure of the internal architecture of bones. …”
Get full text

Gaussian Process Regression and Machine Learning Methods for Carbon-Based Material Adsorption by Manar Ahmed Hamza, Maha M. Althobaiti, Fahd N. Al-Wesabi, Rana Alabdan, Hany Mahgoub, Anwer Mustafa Hilal, Abdelwahed Motwakel, Mesfer Al Duhayyim

“…In the existing system, random forest and ANN methods were used for TC and SMX for predicting the quantities of antibiotics in the CBMs. …”
Get full text

Topology aware multitask cascaded U-Net for cerebrovascular segmentation. by Pierre Rougé, Nicolas Passat, Odyssée Merveille

“…This loss requires computing the skeletons of both the manual annotation and the predicted segmentation in a differentiable way. Currently, differentiable skeletonization algorithms are either inaccurate or computationally demanding. …”
Get full text

Higgs boson production in association with massive bottom quarks at NNLO+PS by Christian Biello, Javier Mazzitelli, Aparna Sankar, Marius Wiesemann, Giulia Zanderighi

“…We present an extensive phenomenological analysis both at the inclusive level and considering bottom jets using flavour-tagging algorithms. By comparing four-flavour and five-flavour scheme predictions at NNLO+PS, we find that the NNLO corrections in the four-flavour scheme resolve the long-standing tension between the two schemes. …”
Get full text

Transcriptome associated with single-cell analysis reveal the role of S-palmitoylation in coronary artery disease by Yiming Xing, Xianhe Lin

“…Nomogram and ROC curve analyses revealed robust diagnostic predictive capabilities grounded in the three hub genes. …”
Get full text

Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations by Bogdan Felician Abaza, Vlad Gheorghita

“…The integration of intelligent monitoring systems and self-learning algorithms is reshaping machining processes, enabling higher efficiency, precision, and sustainability. …”
Get full text

Explicit and Implicit Knowledge in Large-Scale Linguistic Data and Digital Footprints from Social Networks by Maria Pilgun

“…This research aims to develop and test algorithms for analyzing both explicit and implicit information in user-generated content and digital interactions. …”
Get full text

The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules by Zuhua Song, Qian Liu, Jie Huang, Dan Zhang, Jiayi Yu, Bi Zhou, Jiang Ma, Ya Zou, Yuwei Chen, Zhuoyue Tang

“…Recursive feature elimination was employed for variable selection. Three ML algorithms—support vector machine (SVM), logistic regression (LR), and naive Bayes (NB)—were implemented to construct predictive models. …”
Get full text

An Application of Modified S-CLSVOF Method to Kelvin-Helmholtz Instability and Comparison with Theoretical Result by Naoki Shimada, Mako Sato, Yuta Yaegashi, Thorsten Koch, Thi Thai Le

Get full text

Structural-methodical model of computer program for control of theoretical knowledge of cadets by V. V. Bulgakov

“…The review of computer programs used in the educational process showed that the number of software products independently created in educational organizations, which have a wide range of functions for the preparation and control of theoretical knowledge, are quite rare. …”
Get full text

COMMUNICATIVE TOOLS FOR COUNTERING MISINFORMATION by Vladyslav Voichuk

“…At the same time, digital technologies such as data analysis algorithms or artificial intelligence offer new opportunities to combat fakes. …”
Get full text

Improved Mixture Cure Model Using Machine Learning Approaches by Huina Wang, Tian Feng, Baosheng Liang

“…Through a literature review and numerical studies, this article discusses the advantages and disadvantages of the progressions of mixture cure models incorporating machine learning techniques such as SVMs for model improvements. Machine learning algorithms have advantages in model flexibility and computation. …”
Get full text

Regression-based investigation of latency in automated networks by Urooj Khan, Tariq Soomro, M.N. Brohi

“…Current systems utilizing Cloud-Fog architecture are still struggling to achieve this target. Many proposed algorithms are deployed to reduce the system latency to an acceptable level. …”
Get full text

Development and Validation of a Reduced DME Mechanism Applicable to Various Combustion Modes in Internal Combustion Engines by Gregory T. Chin, J.-Y. Chen, Vi H. Rapp, R. W. Dibble

“…The construction of reduced chemistry was carried out with automatic algorithms incorporating newly developed strategies. …”
Get full text

A comparison of several intrusion detection methods using the NSL-KDD dataset by hazem salim abdullah

“…This research investigates the way to classify and predict cyber-attacks on the NSL-KDD dataset using intrusion detection methods the investigation contrasts the capabilities of various algorithms, including RNN, MLP, CNN-LSTM, and ANN, in recognizing attacks. …”
Get full text

Optimising Daily Fantasy Sports Teams with Artificial Intelligence by Beal Ryan, Norman Timothy J., Ramchurn Sarvapali D.

“…To this end, we propose a number of new models and algorithms to solve the team formation problems posed by DFS. …”
Get full text

Machine Learning-Assisted 3D Flexible Organic Transistor for High-Accuracy Metabolites Analysis and Other Clinical Applications by Caizhi Liao, Huaxing Wu, Luigi G. Occhipinti

“…This paper presents an innovative approach combining machine learning-assisted 3D flexible fiber-based organic transistor (FOT) sensors for high-accuracy metabolite analysis and potential diagnostic applications. Machine learning algorithms further enhance the analytical capabilities of FOT sensors by effectively processing complex data, identifying patterns, and predicting diagnostic outcomes with 100% high accuracy. …”
Get full text