Ngā hua rapu - language learning algorithm

Whakamahine hua
  1. 141

    Training Large Models on Heterogeneous and Geo-Distributed Resource with Constricted Networks Zan Zong, Minkun Guo, Mingshu Zhai, Yinan Tang, Jianjiang Li, Jidong Zhai

    I whakaputaina 2025-06-01

    As the computational demands driven by large model technologies continue to grow rapidly, leveraging GPU hardware to expedite parallel training processes has emerged as a commonly-used strategy. When computational resources within a single cluster are insufficient for large-model training, the hybri...

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  2. 142

    Recurrent Neural Network Optimized by Grasshopper for Accurate Audio Data-Based Diagnosis of Parkinson's Disease Saif Wali Ali Alsudani, Ghassan Khudair Saud

    I whakaputaina 2025-06-01

    Proposed here is a speech-based diagnostic framework for detecting Parkinson's disease that utilizes a Long Short-Term Memory neural network and the Grasshopper Optimization Algorithm. The framework aims to improve the detection of PD while ensuring accurate and efficient classification of spe...

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    “… Proposed here is a speech-based diagnostic framework for detecting Parkinson's disease that utilizes a Long Short-Term Memory neural network and the Grasshopper Optimization Algorithm. The framework aims to improve the detection of PD while ensuring accurate and efficient classification of speech-based signals. …”
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  3. 143

    Event Prediction Using Spatial–Temporal Data for a Predictive Traffic Accident Approach Through Categorical Logic Eleftheria Koutsaki, George Vardakis, Nikos Papadakis

    I whakaputaina 2025-06-01

    An event is an occurrence that takes place at a specific time and location that can be either weather-related (snowfall), social (crime), natural (earthquake), political (political unrest), or medical (pandemic) in nature. These events do not belong to the “normal” or “usual” spectrum and result in...

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  4. 144

    Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes Yanying Li, Zaiwen Ni, Binqing Xiao

    I whakaputaina 2025-07-01

    Process anomaly detection in financial services systems is crucial for operational compliance and risk management. However, traditional process mining techniques frequently neglect the detection of significant low-frequency abnormalities due to their dependence on frequency and the inadequate incorp...

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    “…The empirical results demonstrate that the E-Heuristic Miner significantly outperforms traditional machine learning methods and process mining algorithms in process anomaly detection. …”
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  5. 145

    Two-Step CNN Framework for Text Line Recognition in Camera-Captured Images Yulia S. Chernyshova, Alexander V. Sheshkus, Vladimir V. Arlazarov

    I whakaputaina 2020-01-01

    In this paper, we introduce an “on the device” text line recognition framework that is designed for mobile or embedded systems. We consider per-character segmentation as a language-independent problem and individual character recognition as a language-dependent one. Thus, the p...

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  6. 146

    AI approaches for phenotyping Alzheimer's disease and related dementias using electronic health records Sara Knox, Stephanie Aghamoosa, Paul M. Heider, Maxwell Cutty, Andrew Wright, Dmitry Scherbakov, Gabriel Hood, Sara A. Nolin, Jihad S. Obeid

    I whakaputaina 2025-04-01

    Abstract INTRODUCTION The current standard electronic (e‐)phenotype for identifying patients with Alzheimer's disease and related dementias (ADRD) from medical claims data yields suboptimal diagnostic accuracy. This study leveraged artificial intelligence (AI)–based text‐classification methods...

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    “…We trained several AI‐based text‐classification models, including bag‐of‐words models, deep learning, and large language models (LLMs), to make ADRD determinations from clinical notes. …”
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  7. 147

    AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis Bhekisipho Twala

    I whakaputaina 2025-07-01

    BackgroundParkinson’s disease (PD) represents one of the most prevalent neurodegenerative disorders globally, affecting over 10 million individuals worldwide. Traditional diagnostic approaches rely heavily on clinical observation and subjective assessment, often leading to delayed or inaccurate diag...

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    “…The integration of multiple data modalities and advanced machine learning algorithms enables earlier detection, more accurate monitoring, and optimized therapeutic interventions. …”
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  8. 148

    Technology acceptance model for online education: identifying interdisciplinary topics and their evolution based on BERTopic model Songyu Jiang, Hao Li, Du Gan

    I whakaputaina 2025-01-01

    As online education technologies rapidly evolve, understanding the dynamics of user acceptance has become a central concern. This study aims to map the intellectual and thematic landscape of Technology Acceptance Model (TAM) research within online education, highlighting key patterns and emerging tr...

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    “…We employed a combination of bibliometric analysis and topic modeling using the BERTopic algorithm to identify collaboration structures and thematic developments.The results reveal four major research themes: learning outcomes, AI-driven pedagogy, professional domain applications, and English language digital learning. …”
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  9. 149

    AdaGram in Python: An AI Framework for Multi-Sense Embedding in Text and Scientific Formulas Arun Josephraj Arokiaraj, Samah Ibrahim, André Then, Bashar Ibrahim, Stephan Peter

    I whakaputaina 2025-07-01

    The Adaptive Skip-gram (AdaGram) algorithm extends traditional word embeddings by learning multiple vector representations per word, enabling the capture of contextual meanings and polysemy. Originally implemented in Julia, AdaGram has seen limited adoption due to ecosystem fragmentation and the com...

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    “…The Adaptive Skip-gram (AdaGram) algorithm extends traditional word embeddings by learning multiple vector representations per word, enabling the capture of contextual meanings and polysemy. …”
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  10. 150

    Engineering of educational programs through the application of intelligent technologies Mikhail S. Gasparian, Sergey A. Lebedev, Yury F. Telnov

    I whakaputaina 2017-02-01

    One of the key tasks of the present stage of the education system development in Russia is to improve the practical orientation of specialists’ training for the modern labor market. On the agenda, there are the issues of modernization of educational programs in the direction of a closer relationship...

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    “…The methods of semantic modeling of informational and educational space, allowing to systematize the knowledge of the professional area in the form of conceptual models of ontologies and repositories of learning objects are offered as the methods of engineering.As the result of the correlation analysis of the categories of existing educational and professional standards, the mechanism to overcome the contradictions between the language of professional competences of educational standards and requirements of the labour functions of the professional standards is proposed. …”
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  11. 151

    SpeakerNet for Cross-lingual Text-Independent Speaker Verification Hafsa HABIB, Huma TAUSEEF, Muhammad Abuzar FAHIEM, Saima FARHAN, Ghousia USMAN

    I whakaputaina 2020-11-01

    Biometrics provide an alternative to passwords and pins for authentication. The emergence of machine learning algorithms provides an easy and economical solution to authentication problems. The phases of speaker verification protocol are training, enrollment of speakers and evaluation of unknown voi...

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    “…The emergence of machine learning algorithms provides an easy and economical solution to authentication problems. …”
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  12. 152

    Vision-Based Navigation and Perception for Autonomous Robots: Sensors, SLAM, Control Strategies, and Cross-Domain Applications—A Review Eder A. Rodríguez-Martínez, Wendy Flores-Fuentes, Farouk Achakir, Oleg Sergiyenko, Fabian N. Murrieta-Rico

    I whakaputaina 2025-07-01

    Camera-centric perception has matured into a cornerstone of modern autonomy, from self-driving cars and factory cobots to underwater and planetary exploration. This review synthesizes more than a decade of progress in vision-based robotic navigation through an engineering lens, charting the full pip...

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    “…Building on these foundations, we review the navigation and control strategies, spanning classical planning, reinforcement and imitation learning, hybrid topological–metric memories, and emerging visual language guidance. …”
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  13. 153

    Local adaptation and validation of a transdiagnostic risk calculator for first episode psychosis using mental health patient records Elizabeth Ford, James Stone, James Stone, James Stone, Dominic Oliver, Dominic Oliver, Dominic Oliver, Benjamin Fell, Gloria Roque, Sam Robertson, Paolo Fusar-Poli, Paolo Fusar-Poli, Paolo Fusar-Poli, Paolo Fusar-Poli, Kathryn Greenwood, Kathryn Greenwood

    I whakaputaina 2025-07-01

    BackgroundFew at-risk adults are identified by specialized services prior to the development of a first episode of psychosis. A transdiagnostic risk calculator, predicting psychosis using electronic health record (EHR) data, was developed in London, UK to identify patients at risk, using structured...

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    “…We developed new machine-learning NLP algorithms for diagnosis, symptom and substance use concepts by fine-tuning existing open-source transformer models. …”
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  14. 154

    Integrating structured and unstructured data for livestock price forecasting: a sustainability study from South Korea Yifan Zhu, Yifan Zhu, Yifan Zhu, Tserenpurev Chuluunsaikhan, Jong-Hyeok Choi, Aziz Nasridinov

    I whakaputaina 2025-07-01

    Accurate forecasting of food prices is important for market regulation and long-term sustainability of the livestock industry. However, traditional forecasting methods often fail to consider unexpected external factors, such as disease outbreaks and natural disasters. Social media and online news ha...

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    “…Additionally, we develop a Korean-language sentiment lexicon using an improved Term Frequency–Inverse Document Frequency (ITF-IDF) algorithm, enabling morpheme-level sentiment analysis for better sentiment extraction in Korean contexts. …”
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  15. 155

    Evaluating the Predictive Power of Software Metrics for Fault Localization Issar Arab, Kenneth Magel, Mohammed Akour

    I whakaputaina 2025-06-01

    Fault localization remains a critical challenge in software engineering, directly impacting debugging efficiency and software quality. This study investigates the predictive power of various software metrics for fault localization by framing the task as a multi-class classification problem and evalu...

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    “…We fitted thousands of models and benchmarked different algorithms—including deep learning, Random Forest, XGBoost, and LightGBM—to choose the best-performing model. …”
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  16. 156

    Integrating Gut Microbiome and Metabolomics with Magnetic Resonance Enterography to Advance Bowel Damage Prediction in Crohn’s Disease Huang L, Meng J, Lin S, Peng Z, Zhang R, Shen X, Zheng W, Zheng Q, Wu L, Wang X, Wang Y, Mao R, Sun C, Li X, Feng ST

    I whakaputaina 2025-06-01

    Lili Huang,1,* Jixin Meng,1,2,* Shaochun Lin,1,* Zhenpeng Peng,1,* Ruonan Zhang,1 Xiaodi Shen,1 Weikai Zheng,1 Qingzhu Zheng,1 Luyao Wu,1 Xinyue Wang,1 Yangdi Wang,1 Ren Mao,3 Canhui Sun,1 Xuehua Li,1 Shi-Ting Feng1 1Department of Radiology, The First...

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    “…The relationships between microbial/metabolic factors and MRE features were explored using correlation and mediation analyses. Seven machine learning algorithms, each paired with seven distinct combinations of multi-omics features, were evaluated using nested 5-fold cross-validation to construct an optimal prediction model. …”
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  17. 157

    Harnessing artificial intelligence of things for cardiac sensing: current advances and network-based perspectives Hao Ren, Hao Ren, Hao Ren, Fengshi Jing, Yongcong Ma, Ruining Wang, Chaocheng He, Yufan Wang, Jiandong Zhou, Yu Sun

    I whakaputaina 2025-07-01

    BackgroundWith the rapid advancements in science and technology, artificial intelligence (AI) has become increasingly integral to various medical applications, including medical devices and assistive healthcare tools. Extensive research highlights the significant potential of AI in the development o...

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    “…A total of 2,128 papers were included in the analysis.ConclusionFrom our perspective, current advancements in AI-powered IoT cardiac sensors primarily focus on optimizing AI algorithms, such as deep learning techniques, and enhancing the functionality of smart wearable devices for precision medicine. …”
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  18. 158

    Development of Competent Mathematical Speech of Students at Technical University A. V. Muzhikova, M. N. Gabova

    I whakaputaina 2020-02-01

    The development of literate speech of students, including mathematics, as one of the areas of communicative component of learning outcomes, is a requirement of higher education standards. The authors have analysed the educational standards for the content of the requirements to the general education...

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    “…The prepared organizational and methodological support of teaching, the systemic educational work allow students to improve their speech skills and skills of active use of mathematical language as a universal language of science, to develop logical, algorithmic and mathematical thinking, the ability to apply methods of mathematical analysis and modeling, theoretical and experimental research in solving professional problems.…”
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  19. 159

    Big Data Analysis Using Apache Spark MLlib and Hadoop HDFS with Scala and Java Hoger Khayrolla Omar, Alaa Khalil Jumaa

    I whakaputaina 2019-05-01

    Nowadays with the technology revolution the term of big data is a phenomenon of the decade moreover, it has a significant impact on our applied science trends. Exploring well big data tool is a necessary demand presently. Hadoop is a good big data analyzing technology, but it is slow because the Job...

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    “…The results showed that the performance of Scala about 10% to 20% is better than Java depending on the algorithm type. The aim of the study is to analyze big data with more suitable programming languages and as consequences gaining better performance. …”
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  20. 160

    A Multi-Modal Attentive Framework That Can Interpret Text (MMAT) Vijay Kumari, Sarthak Gupta, Yashvardhan Sharma, Lavika Goel

    I whakaputaina 2025-01-01

    Deep learning algorithms have demonstrated exceptional performance on various computer vision and natural language processing tasks. However, for machines to learn information signals, they must understand and have enough reasoning power to respond to general questions based on the linguistic featur...

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    “…Deep learning algorithms have demonstrated exceptional performance on various computer vision and natural language processing tasks. …”
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