Analysis to Predict the Number of New Students At UNU Pasuruan using Arima Method by Fachri Ayudi Fitrony, Laksmita Dewi Supraba, Tessa Rantung, I Made Artha Agastya, Kusrini Kusrini

Get full text

A variable metric proximal stochastic gradient method: An application to classification problems by Pasquale Cascarano, Giorgia Franchini, Erich Kobler, Federica Porta, Andrea Sebastiani

“…Due to the continued success of machine learning and deep learning in particular, supervised classification problems are ubiquitous in numerous scientific fields. …”
Get full text

SURVEY AND PROPOSED METHOD TO DETECT ADVERSARIAL EXAMPLES USING AN ADVERSARIAL RETRAINING MODEL by Thanh Son Phan, Quang Hua Ta, Duy Trung Pham, Phi Ho Truong

“…However, in recent years, machine learning models have been the target of various attack methods. …”
Get full text

A Multi-Scale Interpretability-Based PET-CT Tumor Segmentation Method by Dangui Yang, Yetong Wang, Yimeng Ma, Houqun Yang

“…Furthermore, the method outperforms the best comparative methods on all three datasets, achieving DSC improvements of 1.46, 1.27, and 1.93, respectively. …”
Get full text

IchthyNet: An Ensemble Method for the Classification of In Situ Marine Zooplankton Shadowgraph Images by Brittney Slocum, Bradley Penta

Get full text

A joint data and knowledge‐driven method for power system disturbance localisation by Zikang Li, Jiyang Tian, Hao Liu

Get full text

Evaluation of participation in the case method: elements to consider for its incorporation in digital environments by Andrés Chiappe, Edinson Oswaldo Delgado Rivas, Sandra Idrovo Carlier, Fabiola Mabel Sáez Delgado

Subjects: “…case method. learning evaluation. pedagogical research. student participation.…”
Get full text

The digital literacy of first-year students and its function in an online method of delivery by Rahmat Budiman, Andre Iman Syafrony

“…Design/methodology/approach – This research was conducted using a quantitative method to investigate first-year students' digital literacy and its effect on their interaction in online learning. …”
Get full text

Method of Underwater Acoustic Signal Denoising Based on Dual-Path Transformer Network by Yongqiang Song, Feng Liu, Tongsheng Shen

Get full text

Improved Phase Diversity Wavefront Sensing with a Deep Learning-Driven Hybrid Optimization Approach by Yangchen Wang, Ming Wen, Hongcai Ma

“…To address these challenges, this paper proposes a hybrid PDWS method that integrates deep learning with nonlinear optimization to improve efficiency and accuracy. …”
Get full text

An experimental investigation of HAM, a novel mnemonic technique for learning L2 homonyms and homophones by Charles M. Mueller

“… Over the past 40 years, extensive research has examined the effectiveness of mnemonics for vocabulary learning. Much of this research has investigated the keyword method (Atkinson & Raugh, 1975), which involves linking an image related to a to-be-learned L2 word with animage related to a similar-sounding L1 word. …”
Get full text

The Use of Active Learning Strategies to Foster Effective Teaching in Higher Education Institutions by Aryan Hussein Sulaiman Dzaiy, Saman Ahmed Abdullah

Subjects: “…Active learning, Student engagement, Higher education, Teaching methods, Learning outcomes.…”
Get full text

A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…By leveraging machine learning and statistical learning techniques, we aim to develop a robust clinical decision support system for dental practitioners.MethodsThis research aims to predict the eruption of 3rd molars in the mandible by analyzing three parameters: the distance from the lower 2nd molar to the anterior border, the mesiodistal width of the third molar, and the distance from the apex of the root to the inferior border of the mandible. …”
Get full text

“I Learned How to Think, Not What to Think.” Student Perspectives on an Interdisciplinary Undergraduate Honours Programme by Jenny Godley, Lori Jane Pasaraba, Megan Wilson, Mabel Teye-Kau, Mark Migotti

Subjects: Get full text

Applying the Aajiiqatigiingniq Research Methodology: approaches and lessons learned through collaborative survey development and analysis by Natalie Ann Carter, Shirley Tagalik, Gita Ljubicic

Get full text

Education About Digital Health and Artificial Intelligence and Learning Needs: Perspectives of Undergraduate Nursing Students by Manal Kleib, Antonia Arnaert, Lynn M. Nagle, Rebecca Sugars

Subjects: Get full text

Susceptibility assessment method for reservoir landslides considering the effect of reservoir impoundment by Rong-jie He, Nan Jiang, Kun Zhang, Liang Zhao, Jia-wen Zhou

“…In this paper, we proposed the use of the original and revised logistic regression models (machine learning methods) to analyze the landslide susceptibility after the second stage of reservoir impoundment. …”
Get full text

Smart grid forecasting method based on data preprocessing and Bi-LSTM by LI Yan, LIU Xinyue, QIAO Junjie, WANG Maotao, LIU Yifan, QI Leijie

Get full text

Impact of SAR Image Quantization Method on Target Recognition With Neural Networks by Kangwei Li, Di Wang, Daoxiang An

“…Despite deep neural network models achieving recognition rates exceeding 99% under standard operating conditions on the moving and stationary target acquisition and recognition dataset, the unique imaging mechanisms of SAR, its background dependency, variations in imaging parameters, and diversity in preprocessing lead to highly variable image statistical characteristics, thereby affecting the performance of deep learning models. Dataset bias, particularly the bias induced by different SAR image quantization methods, is one of the key factors impacting the generalization capability of models. …”
Get full text

Non-stationary signal combined analysis based fault diagnosis method by Zhe CHEN, Yuqi HU, Shiqing TIAN, Huimin LU, Lizhong XU

“…Considering the complementarity between the deep learning,spectrum and time frequency analysis methods,a multi-stream framework was designed by combining the convolutional network,Fourier transform and wavelet package decomposition methods,with the aim to analyze the non-stationary signal.Accordingly,a none-stationary signal combined analysis based fault diagnosis method was proposed to extract features in difference aspects.The fault diagnosis experiments demonstrate that the combined analysis method can efficiently and stably depict the fault and significantly improve the performance of fault diagnosis.…”
Get full text