Data science and automation in the process of theorizing: Machine learning's power of induction in the co-duction cycle. by Daan Kolkman, Gwendolyn K Lee, Arjen van Witteloostuijn

“…When used as a part of a full research process, including inductive, deductive and abductive steps, machine learning can offer explanatory insights and provide a solid basis for theorization. …”
Get full text

Research on constrained policy reinforcement learning based multi-objective optimization of computing power network by Linjiang SHEN, Chang CAO, Chao CUI, Yan ZHANG

Get full text

The Assessment Instrument of Mathematics Learning Outcomes Based on HOTS Toward Two-Dimensional Geometry Topic by I Gede Wahyu Suwela Antara, I Komang Sudarma, I.Ketut Dibia

Get full text

Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning. by Robert van Dijk, John Arevalo, Mehrtash Babadi, Anne E Carpenter, Shantanu Singh

“…CytoSummaryNet uses self-supervised contrastive learning in a multiple-instance learning framework, providing an easier-to-apply method for aggregating single-cell feature data than previously published strategies. …”
Get full text

Using Positive Deviance as an Approach in Action Research to Optimize Parental Learning Assistance for Children with Disabilities by Wiwin Hendriani

“… The aim of this research is to assist parents of children with disabilities in optimizing the learning support they provide by leveraging the knowledge and experiences of those who have successfully improved their children's learning outcomes. …”
Get full text

Real-time recognition of spraying area for UAV sprayers using a deep learning approach. by Shahbaz Khan, Muhammad Tufail, Muhammad Tahir Khan, Zubair Ahmad Khan, Javaid Iqbal, Arsalan Wasim

“…Therefore, the study's objective was to develop an accurate real-time recognition system of spraying areas for UAVs, which is of utmost importance for UAV-based sprayers. A two-step target recognition system was developed by using deep learning for the images collected from a UAV. …”
Get full text

Learning from the past; thinking for the future: reflections on STEM and its integration in formal and informal settings by Justin Dillon, Victoria Wong

Get full text

Decision-Making Policy for Autonomous Vehicles on Highways Using Deep Reinforcement Learning (DRL) Method by Ali Rizehvandi, Shahram Azadi, Arno Eichberger

“…The first step is to create a highway traffic environment where the agent can be guided safely through surrounding vehicles. …”
Get full text

New Directions for retranslations research: Lessons Learned from the archaeology of retranslations in the finnish literary system by Kaisa Koskinen, Outi Paloposki

Get full text

From Task Distributions to Expected Paths Lengths Distributions: Value Function Initialization in Sparse Reward Environments for Lifelong Reinforcement Learning by Soumia Mehimeh, Xianglong Tang

“…This paper studies value function transfer within reinforcement learning frameworks, focusing on tasks continuously assigned to an agent through a probabilistic distribution. …”
Get full text

Need Analysis of Flipped Learning English-Based Speaking Materials for Faculty Economics and Business Students by Sumti Chusna, Nur Mukminatien, Ekaning Dewanti Laksmi

“…Need Assessment is the vital step to develop a learning material. This research focuses on mapping out the student's needs in the Foreign Language for Specific Course (FLSP) speaking class at the Faculty of Economic and Business, in one of a private university in Malang, Indonesia. …”
Get full text

Classification of Retinoblastoma Eye Disease on Digital Fundus Images Using Geometric Features and Machine Learning by Arif Setiawan

“…The classification of normal and retinoblastoma-affected retinas is a preliminary step in treating retinoblastoma tumors. Therefore, this study aimed to propose a new method for classifying normal and retinoblastoma-affected retinas using geometric feature extraction and machine learning. …”
Get full text

Development of a novel physics-informed machine learning model for advanced thermochemical waste conversion by Surika van Wyk

“…This is a promising first step towards improving data-driven ML models for application to thermochemical systems.…”
Get full text

NEW METHOD FOR BEARING INTELLIGENT DIAGNOSIS BASED ON COMPRESSED SENSING AND MULTILAYER EXTREME LEARNING MACHINE by CHEN WanSheng, WANG Zhen, ZHAO HongJian, WANG FengTao

“…This method greatly reduces the amount of data for bearing diagnostic signals and eliminate the step of feature selection in intelligent diagnosis. …”
Get full text

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review by ShiYing Shen, Wenhao Qi, Jianwen Zeng, Sixie Li, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Yankai Shi, Jiani Yao, Bingsheng Wang, Xiajing Lou, Simin Gu, Pan Li, Jinghua Wang, Guowei Jiang, Shihua Cao

“…Most studies focused on depression (23/42, 55%) and anxiety (9/42, 21%) using primarily wrist-worn devices (32/42, 76%) collecting heart rate (28/42, 67%), movement index (25/42, 60%), and step count (17/42, 40%) as key biomarkers. Deep learning models (eg, convolutional neural networks and long short-term memory) showed high accuracy, while traditional ML (eg, random forest) remained prevalent due to better interpretability. …”
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

Flipbook-based hybrid media in e-learning Pancasila education course at PGRI Yogyakarta University by Oktana Wahyu Perdana, Mukhamad Murdiono, T Heru Nurgiansah

“…The purpose of this research is to (1) develop a hybrid flipbook-based media in e-learning Pancasila Education courses as a step to reduce the use of internet quotas, (2) make Pancasila Education lectures varied and fun, and (3) know the validity of media, matrials, and design. …”
Get full text

High-Frequency Cryptocurrency Price Forecasting Using Machine Learning Models: A Comparative Study by Fátima Rodrigues, Miguel Machado

“…We compare various machine learning models, including recurrent neural networks (RNNs), time series analysis (ARIMA), and conventional regression algorithms, using minute-step Bitcoin price data over a 30-day period to predict prices 60 min ahead. …”
Get full text

Model-Aware End-to-End Learning for SISO Optical Wireless Communication Over Poisson Channel by Ling-Han Si-Ma, Zhao-Rui Zhu, Hong-Yi Yu

“…This study takes the first step toward applying end-to-end learning techniques in the field of the Poisson channel and lays a foundation for further works on this topic.…”
Get full text

Examining the Impact of Construction Field Trips on Learning Outcomes: Perspectives from Structural Architecture Courses by Wafa Labib, Amal Abdelsattar

“…This study introduces a hybrid teaching approach that integrates structured field trips with traditional lectures based on Kolb’s four-step experiential learning cycle to address this. …”
Get full text