Second Language Motivational Selves and Interactional Pragmatics in Study Abroad: A Qualitative Study by Jun Lang, Feng Xiao, Minghua Zhang

“…Participants were four U.S. learners of Chinese who studied and interned abroad in Fall 2021 and 2022. They completed a role-play task on pragmatics in interaction, a survey on learning background and social contact, a survey on L2 motivational selves, and a semi-structured interview on their study abroad experience. …”
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Predicting Missing Values in Survey Data Using Prompt Engineering for Addressing Item Non-Response by Junyung Ji, Jiwoo Kim, Younghoon Kim

“…Traditional methods for addressing missing data, such as statistical imputation techniques and deep learning models, often fall short when dealing with the rich linguistic content of survey data. …”
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Summer Practicum: Extending the Partnership for Pre-Service Teachers to a Local High School by Jim Mostofo

“…This paper describes such a partnership with a local high school in which pre-service teachers from a university’s college of education completed their practicum hours over the summer in advance for their fall classes. My dual role in this partnership as a professor in the college of education and as the director of the summer partnership is discussed. …”
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Analyzing resuscitation conference content through the lens of the chain of survival by Nino Fijačko, Sebastian Schnaubelt, Vinay M Nadkarni, Špela Metličar, Robert Greif

“…Additionally, artificial intelligence, deep learning, and machine learning approaches for data analysis were examined. …”
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Research on Seismic Signal Denoising Model Based on DnCNN Network by Li Duan, Jianxian Cai, Li Wang, Yan Shi

“…Conventional algorithms for seismic signal denoising often fall short due to their reliance on manually determined feature functions and threshold parameters. …”
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Interpretable Clustering Using Dempster-Shafer Theory by Aram Adamyan, Hovhannes Hovanesyan, Daniel Radrigan, Nelson Baloian, Ashot Harutyunyan

“…This work underscores the increasing importance of interpretability in machine learning, particularly in unsupervised learning, where transparency is typically challenging to achieve. …”
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BHGNN-RT: Capturing bidirectionality and network heterogeneity in graphs. by Xiyang Sun, Fumiyasu Komaki

“…Graph neural networks (GNNs) have shown great promise for representation learning on complex graph-structured data, but existing models often fall short when applied to directed heterogeneous graphs. …”
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ANALYSIS OF USE OF PHYPHOX APPLICATIONS FOR PHYSICS PRACTICUMS USING SMARTPHONES ON COLLISION MATERIAL by Mega Indah Puspita Sari, Heru Kuswanto, Mohammad Abdul Khafid

“…Smartphones are a physical learning medium that can support students to experiment with measurement devices. …”
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Rethinking Pro Bono: Students Lending a Legal Hand by Sebastian De Brennan

“…Many teachers have limited time and resources and may be tempted to fall back on a fairly basic model for teaching negotiation skills. …”
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Trajectory Tracking Control of a Six-Degree-of-Freedom Manipulator Based on EAVOA-LADRC by Xinxin Shi, Haihao Yu

“…In order to solve the problem that the AVOA is unbalanced between the exploration stage and the development stage, and is prone to fall into the local optimal solution, the Kent Chaos initialization, Cauchy inverse learning, optimization of the F computation, and introduction of inhibition coefficients are proposed as the improvement strategies. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures. …”
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Emerging trends in Alzheimer's disease diagnosis and prediction using artificial intelligence: A bibliometric analysis of the top cited 100 articles by Guangheng Zhang, Weijie Zhao, Shimeng Lv, Ziyue Wang, Yunhao Yi, Haoteng Ma, Yitong Lu, Wei Yan, Jing Teng

“…The keywords identified fall into 9 categories. The most frequently occurring keywords are “Alzheimers disease”, “mild cognitive impairment”, “classification”, “MRI”, “deep learning”, “diagnosis”, “dementia”, “biomarkers”, “brain atrophy”, “machine learning”, “voxel based morphometry”, “prediction”, and “patterns”. …”
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Student performance and perceptions in a hybrid laboratory model: an exploratory study of interactive virtual simulations and in-person integration in a foundational microbiology c... by Vanessa Ayer Miller, Timothy Marks, Dorothea K. Thompson

“…Study participants comprised students (n = 49) enrolled in a foundational microbiology course at a private university in the Fall semesters of 2022 and 2023. Identical quizzes were administered to assess learning performance of students who received the VLS first and those who completed the IP lab first. …”
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Computerized cognitive retraining (ReadON.ai) among children diagnosed with attention deficit hyperactivity disorder by Jagriti Grover, Sampurna Chakraborty, Rushi, Sonia Puar

“…Traditional methods like medication and behavior therapy fall short in managing ADHD’s cognitive domains, urging the adoption of innovative approaches like cognitive training programs specifically adopting the emerging technology such as ReadON.ai. …”
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Outdoor Clothing Design for Traffic Safety Based on Big Data and Artificial Intelligence by Ya Zhou, Yun Shi

“…To this end, this paper adopts a Deep Belief Network (DBN), which is trained layer by layer through Restricted Boltzmann Machine (RBM), and successfully solves the problems of lack of a large number of labeled samples and easy to fall into local optimum. The first experiment is to test the accuracy of various machine learning algorithms for clothing size measurement. …”
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Indoor fire and smoke detection based on optimized YOLOv5. by Md Shafak Shahriar Sozol, M Rubaiyat Hossain Mondal, Achmad Husni Thamrin

“…Traditional detection techniques that use smoke, heat, or fire sensors often fail due to false positives and slow response time. Existing deep learning-based object detectors fall short of improved accuracy in indoor settings and real-time tracking, considering the dynamic nature of fire and smoke. …”
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DEVELOPMENT OF INTERACTIVE TEACHING MATERIALS WITH RME-BASED ISPRING SUITE TO IMPROVE STUDENTS' CREATIVE THINKING SKILLS by Barra P Pradja, Nisvu Nanda Saputra, Abdul Baist, Retno Andriyani, Hairul Saleh, Ratu Sarah Fauziah Iskandar

“…Moreover, improving pupils' capacity for creative thought is known to fall into the effective group based on the results of the n-gain test. …”
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Service Function Chain Migration: A Survey by Zhiping Zhang, Changda Wang

“…Traditional optimization algorithms often fall short in large-scale, heterogeneous networks due to limited computational efficiency and scalability. …”
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Enhanced rain removal network with convolutional block attention module (CBAM): a novel approach to image de-raining by Ping Jiang, Junzi Zhang, Jiejie Chen

“…Traditional methods often fall short and require significant computational resources. …”
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Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells. by Owen M O'Connor, Mary J Dunlop

“…Deep learning-based methods for identifying and tracking cells within microscopy images have revolutionized the speed and throughput of data analysis. …”
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