Unified modeling language code generation from diagram images using multimodal large language models by Averi Bates, Ryan Vavricka, Shane Carleton, Ruosi Shao, Chongle Pan

“…The experiments measured the code generation accuracy across different model sizes and training strategies. …”
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Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting? by Nouf Alturayeif, Jameleddine Hassine

“…Data leakage can occur at either the dataset-level (i.e., during dataset construction) or at the code-level. Existing studies introduced methods to detect code-level data leakage using manual and code analysis approaches. …”
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Can LLMs effectively assist medical coding? Evaluating GPT performance on DRG and targeted clinical tasks by Yeli Feng

“…Both results are comparable to the best methods in comparison that training deep leaning models or fine-tuning LLMs. Conclusions This study demonstrates that for targeted coding tasks, DRG and other simplified scenarios, off-the-shelf GPT models guided by carefully designed prompts can achieve performance comparable to state-of-the-art methods. …”
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The impact of training using six thinking hats versus video training on nursing students’ insulin administration skills: a mixed-methods study by Ayşe Soylu, Ahmet Seven, Dilek Soylu

“…The control group (n = 30) received traditional training only. The six thinking hats group (n = 30) received traditional training and six thinking hats training. …”
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Adaptive Neural-Network-Based Lossless Image Coder with Preprocessed Input Data by Grzegorz Ulacha, Ryszard Stasinski

“…Its adaptation is done for each coded pixel separately; no initial training using learning image sets is necessary. …”
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Multi-objective portfolio optimization using real coded genetic algorithm based support vector machines by B. Surja, L. Chin, F. Kusnadi

“…Single optimal portfolios were created using the real coded genetic algorithm based on different sets of objectives: Maximizing short-term and long-term returns, maximizing liquidity, and minimizing risk. …”
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Energy optimization induces predictive-coding properties in a multi-compartment spiking neural network model. by Mingfang Zhang, Raluca Chitic, Sander M Bohté

“…Predictive coding is a prominent theoretical framework for understanding hierarchical sensory processing in the brain, yet how it could be implemented in networks of cortical neurons is still unclear. …”
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Simultaneous discovery of quantum error correction codes and encoders with a noise-aware reinforcement learning agent by Jan Olle, Remmy Zen, Matteo Puviani, Florian Marquardt

“…In this work, we significantly expand the power of RL approaches to QEC code discovery. Explicitly, we train an RL agent that automatically discovers both QEC codes and their encoding circuits for a given gate set, qubit connectivity and error model, from scratch. …”
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Point Cloud Geometry Scalable Coding Using a Resolution and Quality-Conditioned Latents Probability Estimator by Daniele Mari, Andre F. R. Guarda, Nuno M. M. Rodrigues, Simone Milani, Fernando Pereira

“…., the ability to generate a progressive bitstream, containing a base layer followed by multiple enhancement layers, that allow decoding the same bitstream serving multiple reconstructions and visualization specifications. While scalable coding is a well-known and addressed feature in conventional image and video codecs, this paper focuses on a new and very different problem, notably the development of scalable coding solutions for deep learning-based Point Cloud (PC) coding. …”
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Gradient Amplification: An Efficient Way to Train Deep Neural Networks by Sunitha Basodi, Chunyan Ji, Haiping Zhang, Yi Pan

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From Ethics to Ethos: An Expanded Agenda for Counsellor Training and Development by Jim Schirmer

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COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization by Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qi, Jack Xin, Xin Li, Penghang Yin

“…Post-training quantization (PTQ) has emerged as a practical approach to compress large neural networks, making them highly efficient for deployment. …”
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Competency assessment in fraud detection at BPK: Challenges and enhancements by Dadang Sukma, Ratna Wardhani

“…It investigates internal factors through the auditor's code of ethics and reviews performance reports to evaluate fraud detection skills. …”
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Adaptation of the competence approach to the methodology of training it specialists in the field of programming by E. V. Savina, K. Ya. Radjabov, T. I. Isabekova

“…The research methods include: analysis of evaluation materials; methods based on algorithms for decomposing the program code proposed for solving the problem; methods for analyzing data from open sources, methods for analyzing algorithms and data structures. …”
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An Improved Software Source Code Vulnerability Detection Method: Combination of Multi-Feature Screening and Integrated Sampling Model by Xin He, Asiya, Daoqi Han, Shuncheng Zhou, Xueliang Fu, Honghui Li

“…Vulnerability detection in software source code is crucial in ensuring software security. Existing models face challenges with dataset class imbalance and long training times. …”
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Barriers to the success of cardiopulmonary resuscitation teams in emergency departments: A perspective from nurses by Alireza Sadeghi, Hosein Jahani, Mojtaba Senmar, Farzaneh Mehdipour, Amir Reza Mirzaei, Ali Poorshivaee, Faranak Sadat Hosseini

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Methodology for implementing an interdisciplinary project based on no-code technology in the process of teaching students of the master's programme "Multimedia design" by Tamara S. Severova

“…It was established that the problem of teaching students in creative training areas technical skills required for creating Internet products can be solved by using no-code technology and the individual project method. …”
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Visually Secure Deep Joint Source-Channel Coding With Chaotic Map Against Deep Known-Plaintext Attack by Yuyang Fu, Katsuya Suto

“…In recent years, deep learning-based joint source-channel coding (DJSCC) has gained significant attention for its impressive performance in image transmission. …”
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CoPaD-Mark: A Coded Parallelizable Deep Learning-Based Scheme for Robust Image Watermarking by Andy M. Ramos, Cecilio Pimentel, Daniel P. B. Chaves

“…In this work, we propose a coded, parallelizable, and deep learning-based image watermarking scheme (CoPaD-Mark). …”
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Effect of Hardiness Training on Self-Esteem and Adjustment of Addicted Male by Mohammad Javad Aghajani

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