Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases by Jina Lee (3138492)

“…To validate the accuracy of the model, the results obtained from the proposed algorithm were compared to experimental data for 37 binary aqueous mixture systems covering properties such as density, heat capacity, viscosity, and thermal conductivity. …”

Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases by Jina Lee (3138492)

“…To validate the accuracy of the model, the results obtained from the proposed algorithm were compared to experimental data for 37 binary aqueous mixture systems covering properties such as density, heat capacity, viscosity, and thermal conductivity. …”

Overview of the influence of parameterization on the models’ performance when predicting essential genes as determined by their MCC. by Vítor Vieira (12937218)

Overview of the influence of parameterization on the models’ performance when predicting flux activity and using MCC as the evaluation metric. by Vítor Vieira (12937218)

Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf by Sai Sakunthala Guddanti (17739363)

“…A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. …”

Image from video analysis. by Yunlin Li (6049214)

Raw Data for "Development of Decision Support Systems Based on Fuzzy and Binary Logic for the FOREX Foreign Exchange Market" by Serhii Hetsko (22413559)

Surround Suppression mechanism. by Elnaz Nemati (21402730)

MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

“…Theoretical and applied experiments are conducted using four solvers: QBSolv, D-Wave Hybrid binary quadratic model 2, D-Wave Advantage system 4.1, and Gurobi. …”

Development of a Battery of <i>In Silico</i> Prediction Tools for Drug-Induced Liver Injury from the Vantage Point of Translational Safety Assessment by James Rathman (1632322)

“…A human DILI training set of 305 oral marketed drugs was prepared and a binary classification scheme applied. The second knowledge base consists of mammalian repeated dose toxicity with liver toxicity data from various regulatory sources. …”

Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective by Xiangyang Jia (10026932)

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…Data sources included peer-reviewed publications and reputable open-access repositories such as the NanoPharos database. …”

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

DataSheet1_Effective Search of Triterpenes with Anti-HSV-1 Activity Using a Classification Model by Logistic Regression.pdf by Keiko Ogawa (1796347)

“…In this study, we constructed a binary classification model (i.e., active or inactive) using a logistic regression algorithm. …”