Review of Research on Trajectory Prediction of Road Pedestrian Behavior by YANG Zhiyong, GUO Jieru, GUO Zihang, ZHANG Ruixiang, ZHOU Yu

“…This paper also reviews commonly used datasets and evaluation metrics in the field, providing a thorough evaluation of current algorithmic performance. Finally, it addresses the challenges in pedestrian trajectory prediction for autonomous driving, particularly the dynamic coupling between pedestrians with multi-directional traffic and infrastructure, offering potential solutions and discussing future research directions.…”
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EFFICIENCY OF RAW GLUTEN CONTENT PREDICTION IN WHEAT KERNELS by A. V. Pasynkov, E. N. Pasynkova

“…There have been developed and presented an algorithm and results of testing the predictive capabilities of the equation based on independent data. …”
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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…Software defect prediction (SDP) is used to identify defects in software modules that can be a challenge in software development. …”
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Correlation and Prediction Analysis of Cyanobacteria with Water Environment Data by Sang-Leen Yun

“…Furthermore, cyanobacteria occurrence was predicted using a random forest algorithm, with a linear regression model serving as a baseline for comparison. …”
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Method and application of stability prediction model for rock slope by Yun Qi, Chenhao Bai, Xuping Li, Hongfei Duan, Wei Wang, Qingjie Qi

“…To accurately and efficiently predict the stability state of slopes, we propose a combined model that integrates the Newton–Raphson optimization algorithm (NRBO) with an optimized extreme gradient boosting tree (XGBoost). …”
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Machine learning prediction of pKa of organic acids by Juda Baikété, Alhadji Malloum, Jeanet Conradie

“…The model trained with the ExTr algorithm showed the best prediction performance with an overall mean absolute error (MAE) value of 1.41 pKa units. …”
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Pathway activation model for personalized prediction of drug synergy by Quang Thinh Trac, Yue Huang, Tom Erkers, Päivi Östling, Anna Bohlin, Albin Osterroos, Mattias Vesterlund, Rozbeh Jafari, Ioannis Siavelis, Helena Backvall, Santeri Kiviluoto, Lukas Orre, Mattias Rantalainen, Janne Lehtiö, Soren Lehmann, Olli Kallioniemi, Yudi Pawitan, Trung Nghia Vu

“…Computational models based on the integration of omics data have been used to identify synergistic combinations, but predicting drug synergy remains a challenge. Here, we introduce Drug synergy Interaction Prediction (DIPx), an algorithm for personalized prediction of drug synergy based on biologically motivated tumor- and drug-specific pathway activation scores (PASs). …”
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Prediction of Clinical Bronchiectasis from Asymptomatic Radiological Bronchiectasis by Fan Y, Li Z, Jiang N, Zhou Y, Song J, Yu F, Zhang J, Wang X

“…ROC, a calibration and decision curve were used to assess the predictive performance of our new prediction model.Results: 370 patients (74, 20% with CB) were finally included. …”
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THE ACCEPTANCE OF AN EDUCATIONAL INTEGRATED DEVELOPMENT ENVIRONMENT TO LEARN PROGRAMMING FUNDAMENTALS by Nor Farahwahida Mohd Noor, Aslina Saad, Abu Bakar Ibrahim, Norashady Mohd Noor

“…Hence, the development process of the C-SOLVIS can be used as a guideline for educational software development, especially in the field of programming education. …”
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Utilizing Artificial Intelligence for Adaptive Scenario Development in Interprofessional Education by Hatice Şahin, Aysel Baser

“…Overreliance on AI also risks reducing critical thinking and creativity, while concerns such as algorithmic bias and data privacy must be carefully addressed to ensure equitable educational practices.…”
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Energy management in autonomous hybrid electric vehicles: A review by Abid H., Kissaoui M., Raihani A., Zaggaf M.H.

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Competence model scheming of the graduate as an assessment tool for the quality of education by E. N. Shaforostova, A. A. Valova

“…At the present time of the society development, the task of process improvement of the quality of education is especially actual and the main tool of its decision is introduction in educational process of new federal educational standards. …”
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Development and external validation of a nomogram prediction model based on quantitative coronary angiography for predicting ischemic lesions: a multi-centre study by Shuai Yang, Shuai Yang, Shuang Leng, Shuang Leng, Zhouchi Wang, Jiang Ming Fam, Jiang Ming Fam, Adrian Fatt Hoe Low, Adrian Fatt Hoe Low, Ru-San Tan, Ru-San Tan, Ping Chai, Ping Chai, Lynette Teo, Lynette Teo, Chee Yang Chin, Chee Yang Chin, John C. Allen, Mark Yan-Yee Chan, Mark Yan-Yee Chan, Khung Keong Yeo, Khung Keong Yeo, Aaron Sung Lung Wong, Aaron Sung Lung Wong, Soo Teik Lim, Soo Teik Lim, Qinghua Wu, Liang Zhong, Liang Zhong, Liang Zhong

“…For per-patient analysis, the corresponding values were 85.8%, 85.7%, 86.0% in the development cohort and 82.2%, 83.3%, 81.1% in the validation cohort.ConclusionThe nomogram may be useful for predicting ischemic lesions using QCA measurements and the LASSO regression algorithm, with external validation indicating potential predictive value in cardiology care settings.…”
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Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting by Wensheng Dai, Jui-Yu Wu, Chi-Jie Lu

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Comparative Analysis of Gradient Descent Learning Algorithms in Artificial Neural Networks for Forecasting Indonesian Rice Prices by Rica Ramadana, Agus Perdana Windarto, Dedi Suhendro

“…The commonly used algorithm for prediction in ANN is Backpropagation, which yields high accuracy but tends to be slow during the training process and is prone to local minima. …”
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Abstract 035: Workflow Improvements from Automated LVO Detection Algorithms Are Dependent on Care Team Engagement by Hussain M Azeem

“…Introduction Automated machine learning (ML)‐based large vessel occlusion (LVO) detection algorithms have been shown to improve in‐hospital workflow metrics including door to groin time (DTG). …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…The second model pairs eXtreme Gradient Boosting (XGBoost), a highly efficient boosting algorithm for tabular data, with an Artificial Neural Network (ANN). …”
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Improving brain tumor classification: An approach integrating pre-trained CNN models and machine learning algorithms by Mohamed R. Shoaib, Jun Zhao, Heba M. Emara, Ahmed S. Mubarak, Osama A. Omer, Fathi E. Abd El-Samie, Hamada Esmaiel

“…This study provides valuable insights into the interplay between CNN models, feature extraction techniques, and machine learning algorithms for brain tumor classification, highlighting the efficacy of DenseNet201 combined with SVM and MLP.…”
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Assessing Volatility Behaviors of Cross-Currency Derivatives in India's Exchange Markets Using Machine Learning Algorithms by Aman Shreevastava, Bharat Kumar Meher, Virgil Popescu, Ramona Birau, Mritunjay Mahato

“…This paper studies the volatility of INR based cross country futures (USD, JPY and EUR) and performs forecasting using ML Algorithm and utilizes LSTM for prediction. The study proves to be a first of its kind study involving cross-country futures and is a beacon of hope for all future research on similar subjects. …”
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Development of Residual Dense U-Net (RDU-Net)-Based Metal Artefacts Reduction Technique Using Spectral Photon Counting CT by Osama Khan, Briya Tariq, Nadine Francis, Nabil Maalej, Abderaouf Behouch, Amer Kashif, Asim Waris, Aamir Raja

“…The proposed model was quantitatively evaluated, with and without the metal artefact reduction (MAR) algorithm, using line profiles, histogram analysis, signal-to-noise ratio (SNR), root mean squared error (RMSE), and structural similarity index measure (SSIM). …”
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