Good practice for assignment of breeds and populations—a review by H. Wilmot, H. Wilmot, N. Gengler

“…In the case selection of SNPs is necessary, we advise the use of one stage methodologies and to define a threshold for this selection. Then, machine learning can be used to develop the model per se, based on the selected or available markers. …”
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IMPROVING INTRUSION DETECTION USING TREE ADJOINING GRAMMAR GUIDED GENETIC PROGRAMMING by Vũ Văn Cảnh, Hoàng Tuấn Hảo, Nguyễn Văn Hoàn

“…Some studies using machine learning technology have been applied in intrusion detection. …”
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Comorbidity Networks From Population-Wide Health Data: Aggregated Data of 8.9M Hospital Patients (1997–2014) by Elma Dervić, Katharina Ledebur, Stefan Thurner, Peter Klimek

“…The dataset provides the possibility to researchers to create their own, tailor-made comorbidity networks from real patient data that can be used as a starting point in quantitative and machine learning methods. This data platform is intended to lead to deeper insights into a wide range of epidemiological, public health, and biomedical research questions.…”
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Directed Energy Deposition via Artificial Intelligence-Enabled Approaches by Utkarsh Chadha, Senthil Kumaran Selvaraj, Aakrit Sharma Lamsal, Yashwanth Maddini, Abhishek Krishna Ravinuthala, Bhawana Choudhary, Anirudh Mishra, Deepesh Padala, Shashank M, Vedang Lahoti, Addisalem Adefris, Dhanalakshmi S

“…Moreover, artificial intelligence and machine learning implementation has increased for further applications and advancements. …”
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Data analysis-based framework for the design and assessment of chemical process plants: a case study in amine gas-treating systems by Rahul Gupta, Gladys Navas, Daniela Galatro

“…This work presents a process-integrity assessment framework to chemical process design that combines first principles, heuristics, vendor specifications, standards/codes, data analysis, and machine learning modelling, hypothesized as an efficient route for optimal process design. …”
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Hybrid Technique to Improve the River Water Level Forecasting Using Artificial Neural Network-Based Marine Predators Algorithm by Sarah J. Mohammed, Salah L. Zubaidi, Nadhir Al-Ansari, Hussein Mohammed Ridha, Nabeel Saleem Saad Al-Bdairi

“…This paper proposes a novel hybrid machine learning model based on an artificial neural network (ANN) and the Marine Predators algorithm (MPA) for modeling monthly water levels of the Tigris River in Al-Kut, Iraq. …”
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Comparison of Matrix Decomposition in Null Space-Based LDA Method by Carissa Devina Usman, Farikhin, Titi Udjiani

“…Problems with small sample sizes and high dimensionality are common in pattern recognition. Almost all machine learning algorithms degrade in high-dimensional data, so that singularities in the scatter matrices, the main problem of the Linear Discriminant Analysis (LDA) technique, might result. …”
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Effective Processing of Radar Data for Bridge Damage Detection by Tomasz Owerko, Przemysław Kuras

“…In addition, the distribution of errors and the sensitivity of classifiers based on the DSF parameter and Cook’s distances leaving them will enable the automation of the classification process using machine learning. The proposed method is universal; in particular, it can be used for radar interferometry methods because it is resistant to potentially variable environmental conditions.…”
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Content-Based Image Retrieval Using Colour, Gray, Advanced Texture, Shape Features, and Random Forest Classifier with Optimized Particle Swarm Optimization by Manoharan Subramanian, Velmurugan Lingamuthu, Chandran Venkatesan, Sasikumar Perumal

“…The matching accuracy and the speed of image retrieval are improved by an ensemble of machine learning algorithms for the similarity search.…”
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Similarity-Based Summarization of Music Files for Support Vector Machines by Jan Jakubik, Halina Kwaśnicka

“…These results suggest that adjusting deep learning methods to build data representations that target a specific classifier or regressor can open up new perspectives for the use of standard machine learning methods in music domain.…”
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Random Forest–Based Coal Mine Roof Displacement Prediction and Application by Hongxia Li, Rong Wu, Jianan Gao

“…Therefore, this study puts forward the machine learning method to study the advance prediction of coal roadway roof displacement. …”
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EXAMINING THE IMPACT OF AI TECHNOLOGY ON MARKETING STRATEGIES IN FINANCIAL SERVICES by POPESCU JENICA, SPULBAR LUCIAN FLORIN, SMARANDESCU ANDREI

“…The study delves into specific AI applications, such as predictive analytics for understanding customer behavior, machine learning models for dynamic customer segmentation, and automation tools that streamline targeted campaigns. …”
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Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer by J.-S. Chou, H.-M. Nguyen, H.-P. Phan, K.-L. Wang

“…The novel framework evaluates machine learning, time series deep learning, and convolutional neural networks (CNNs), identifying the most effective models to be enhanced by the Age of Exploration-Inspired Optimizer (AEIO) algorithm. …”
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Improving Diabetic Patients Monitoring System Using (NCA-CNN) Algorithm based on loT by Ayas Talib Mohammad, Jaber Parchami

“… The Internet of Things (IoT) and Artificial Intelligence (AI), particularly Machine Learning (ML), have both seen significant advancements in recent years, which has resulted in significant leaps forward in the development of health monitoring systems. …”
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Inteligencia artificial y derechos humanos by Juan Esteban Yanguas Ramón, Isabella Narváez Peña

“…El artículo explora, desde la teoría, diversos conceptos, pasando por el machine learning y la analítica de datos, así como los derechos humanos desde definiciones informales hasta formales, analizando sus elementos y los sistemas de protección de estos derechos. …”
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Evaluation of Different Stemming Techniques on Arabic Customer Reviews by Hawraa Fadhil Khelil, Mohammed Fadhil Ibrahim, Hafsa Ataallah Hussein, Raed Kamil Naser

“…This work sheds light on utilizing and investigating more machine learning (ML) techniques and evaluating the results.  …”
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A Novel Method to Forecast Nitrate Concentration Levels in Irrigation Areas for Sustainable Agriculture by Halil Karahan, Müge Erkan Can

“…The proposed model, although based on an artificial neural network (ANN), also has the potential to be adapted for methods used in machine learning and artificial intelligence, such as Support Vector Machines, Decision Trees, Random Forests, and Ensemble Learning Methods.…”
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Fault detection in beam structure using adaptive immune based approach by Sasmita Sahu, Shakti P. Jena

“…Recently with the application of machine learning approaches and the soft computing, the damage can be detected easily. …”
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PreLect: Prevalence leveraged consistent feature selection decodes microbial signatures across cohorts by Yin-Cheng Chen, Yin-Yuan Su, Tzu-Yu Chu, Ming-Fong Wu, Chieh-Chun Huang, Chen-Ching Lin

“…Upon rigorous benchmarking against established feature selection methodologies across 42 microbiome datasets, PreLect demonstrated superior classification capabilities compared to statistical methods and outperformed machine learning-based methods by selecting features with greater prevalence and abundance. …”
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GDPR-oriented intelligent checking method of privacy policies compliance by Xin LI, Peng TANG, Xiheng ZHANG, Weidong QIU, Hong HUI

“…The implementation of the EU’s General Data Protection Regulation (GDPR) has resulted in the imposition of over 300 fines since its inception in 2018.These fines include significant penalties for prominent companies like Google, which were penalized for their failure to provide transparent and comprehensible privacy policies.The GDPR, known as the strictest data protection laws in history, has made companies worldwide more cautious when offering cross-border services, particularly to the European Union.The regulation's territorial scope stipulates that it applies to any company providing services to EU citizens, irrespective of their location.This implies that companies worldwide, including domestic enterprises, are required to ensure compliance with GDPR in their privacy policies, especially those involved in international operations.To meet this requirement, an intelligent detection method was introduced.Machine learning and automation technologies were utilized to automatically extract privacy policies from online service companies.The policies were converted into a standardized format with a hierarchical structure.Through natural language processing, the privacy policies were classified, allowing for the identification of relevant GDPR concepts.In addition, a constructed GDPR taxonomy was used in the detection mechanism to identify any missing concepts as required by GDPR.This approach facilitated intelligent detection of GDPR-oriented privacy policy compliance, providing support to domestic enterprises while they provided cross-border services to EU users.Analysis of the corpus samples reveals the current situation that mainstream online service companies generally fail to meet GDPR compliance requirements.…”
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