204.674 hasil untuk machine learning
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Artikel Jurnal
Fiber Break Prevention Using Machine Learning Approaches
…of fiber optic breakages in response to these difficulties by using machine learning approaches. The data collected by an optical fiber sensor and a distributed acoustic sensing interrogator unit (DAS). Five tools are used to simulate fiber break threats on the road surface and the fiber optic…
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Artikel Jurnal
HAND GESTURE RECOGNITION USING MACHINE LEARNING ALGORITHMS
Communication between people is an integral part of life. In the process of communication, people convey their emotions, thoughts, desires to each other. People with disabilities, such as deaf and dumb people, experience various difficulties in the process of communication [1]. Today, 5% of the…
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Artikel Jurnal
Prediction of GPCR activity using machine learning
GPCRs are the target for one-third of the FDA-approved drugs, however; the development of new drug molecules targeting GPCRs is limited by the lack of mechanistic understanding of the GPCR structure–activity-function relationship. To modulate the GPCR activity with highly specific drugs and minimal…
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Artikel Jurnal
ENSEMBLE MACHINE LEARNING FOR GLOBAL HYDROLOGICAL PREDICTION
Accurate global hydrological prediction is vital for sustainable water management but is often hindered by data complexity and fragmentation. This study introduces an advanced machine learning framework to predict long-term average discharge using widely available global hydrological station…
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Artikel Jurnal
APPLYING MACHINE LEARNING TO IDENTIFY COUNTERFEIT FOODS
…we will talk about how to identify low-quality products using modern machine learning. Recognition and classification of images and text based on machine learning can be a key technology in the fight against low[1]quality food. Automatic image and text recognition and classification of product…
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Artikel Jurnal
COMPARATIVE ANALYSIS OF FEDERATED MACHINE LEARNING ALGORITHMS
In this paper, the authors propose a new machine learning paradigm, federated machine learning. This method produces accurate predictions without revealing private data. It requires less network traffic, reduces communication costs and enables private learning from device to device. Federated…
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Artikel Jurnal Teks lengkap
Molecular and polymer representations for machine learning
…networks and large language models offer new pathways in representation learning, enabling molecular and polymer representations to be learned directly from structural inputs. These machine-learned embeddings promise more expressive, scalable, and transferable representations, potentially…
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Artikel Jurnal
Acacia Seed Classification Using Machine Learning Techniques
Accurate classification of Acacia seed species in Saudi Arabia is challenging due to subtle morphological similarities. This study presents a deep learning-based framework for classifying seven Acacia seed species using the EfficientNet-V2 B0 convolutional neural network. Seed images collected…
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Artikel Jurnal Teks lengkap
Chaos Prediction: Machine Learning Versus Dynamical Models
We address the question of whether machine learning can improve the predictability of chaos. Due to the presence of chaos, chaotic time series are “contaminated” beyond the horizon of predictability as numerical errors accumulate. Therefore, evaluations should be based on error-free computation of…
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Artikel Jurnal
Unraveling sperm kinematic heterogeneity with machine learning
…for analysis using conventional statistical methods. Advances in machine learning and deep learning have addressed these limitations by leveraging motility parameters and trajectory representations for automated classification and clustering of motility patterns. These methods, including supervised…
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Artikel Jurnal Teks lengkap
Machine Learning Models for Predicting Academic Performance
…more convenient, but there are still many problems that come with it. Machine learning is a very good tool to predict outcomes. The accurate prediction models can help with decision-making and improve data analysis efficiency. However, choosing the appropriate models and comparing the performance…
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Artikel Jurnal Teks lengkap
Machine learning methods in predicting antimicrobial resistance
…diverse strategies to combat AMR. Within the context of AMR diagnostics, machine learning approaches for predicting bacterial resistance are under active investigation. This paper reviews state-of-the-art methods for predicting antibiotic resistance in individual bacterial isolates. The review…
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Artikel Jurnal
DevRec: enhancing developer recommendation using machine learning
…Analysis (Statistical-SA) for ranking developer recommendations, and Machine Learning–Semantic Analysis (ML-SA) for predictive developer assignment. ML models are trained on previous developer behaviour and contributions across multiple projects to enhance recommendation accuracy. The framework is…
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Artikel Jurnal
High-tunnel Temperature Forecasting with Machine Learning
…manual ventilation and reduce crop risk. We evaluated the reuse of a machine learning (ML) artificial neural network (ANN) architecture, developed originally for solar radiation forecasting, for predicting internal high-tunnel temperatures. Three weather data sources were tested as model inputs…
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Artikel Jurnal
Rethinking data linkage through machine learning techniques
In this presentation we propose a combination of machine learning techniques to perform record linkage processes in the presence of high-volume data. Indeed, record linkage is a complex process composed of several steps, each of them exploiting different techniques. Machine learning algorithms are…
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Artikel Jurnal Teks lengkap
Interpretable Physics-Informed Machine Learning for Pyrolysis
…kinetics and the lack of mechanistic interpretability in modern Machine Learning (ML) models. This study addresses the black-box problem by comparing a standard Artificial Neural Network (ANN) against a novel Hybrid Physics-Informed Neural Network (PINN) and a Transparent Model (Rough Set ML, RSML)…
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Artikel Jurnal
On-Chip Age Estimation Using Machine Learning
…CMOS technology and aging model provided by GlobalFoundries (GF). The machine learning (ML) algorithm of support vector regression (SVR) is adapted for this application, using a training process that involves operating temperature, $\tau _{dv}$ , f, aging time and inter-die and intra-die process…
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Artikel Jurnal
MACHINE LEARNING FOR E-COMMERCE FRAUD DETECTION
The study examines the effectiveness, challenges, and best machine learning algorithms for detecting e-commerce fraud. This study uses a systematic literature review to evaluate the effectiveness of machine learning-based e-commerce fraud detection, identify challenges, and identify the most…
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Artikel Jurnal
Machine Learning Methods for Histopathological Image Analysis
Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have some issues to be considered. In this mini-review, we…
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