AIMC Topic: Algorithms

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Effects on quality characteristics of ultrasound-treated gilaburu juice using RSM and ANFIS modeling with machine learning algorithm.

Ultrasonics sonochemistry
Gilaburu (Viburnum opulus L.) is a red-colored fruit with a sour taste that grows in Anatolia. It is rich in various antioxidant and bioactive compounds. In this study, bioactive compounds and ultrasound parameters of ultrasound-treated gilaburu wate...

Advanced deep learning algorithm for instant discriminating of tea leave stress symptoms by smartphone-based detection.

Plant physiology and biochemistry : PPB
The primary challenges in tea production under multiple stress exposures have negatively affected its global market sustainability, so introducing an infield fast technique for monitoring tea leaves' stresses has tremendous urgent needs. Therefore, t...

Evaluation of EEG Signals by Spectral Peak Methods and Statistical Correlation for Mental State Discrimination Induced by Arithmetic Tasks.

Sensors (Basel, Switzerland)
Bringing out brain activity through the interpretation of EEG signals is a challenging problem that involves combined methods of signal analysis. The issue of classifying mental states induced by arithmetic tasks can be solved through various classif...

Crossing-Point Estimation in Human-Robot Navigation-Statistical Linearization versus Sigma-Point Transformation.

Sensors (Basel, Switzerland)
Interactions between mobile robots and human operators in common areas require a high level of safety, especially in terms of trajectory planning, obstacle avoidance and mutual cooperation. In this connection, the crossings of planned trajectories an...

A novel plant type, leaf disease and severity identification framework using CNN and transformer with multi-label method.

Scientific reports
The growth of plants is threatened by numerous diseases. Accurate and timely identification of these diseases is crucial to prevent disease spreading. Many deep learning-based methods have been proposed for identifying leaf diseases. However, these m...

Prediction of Cognitive Impairment Risk among Older Adults: A Machine Learning-Based Comparative Study and Model Development.

Dementia and geriatric cognitive disorders
INTRODUCTION: The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention.

Long-term water demand forecasting using artificial intelligence models in the Tuojiang River basin, China.

PloS one
Accurate forecasts of water demand are a crucial factor in the strategic planning and judicious use of finite water resources within a region, underpinning sustainable socio-economic development. This study aims to compare the applicability of variou...

A novel machine learning-based prediction method for patients at risk of developing depressive symptoms using a small data.

PloS one
The prediction of depression is a crucial area of research which makes it one of the top priorities in mental health research as it enables early intervention and can lead to higher success rates in treatment. Self-reported feelings by patients repre...

DMA-HPCNet: Dual Multi-Level Attention Hybrid Pyramid Convolution Neural Network for Alzheimer's Disease Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Computer-aided diagnosis (CAD) plays a crucial role in the clinical application of Alzheimer's disease (AD). In particular, convolutional neural network (CNN)-based methods are highly sensitive to subtle changes caused by brain atrophy in medical ima...