Examining What Causes Perceived Dissonance in Musical Intervals and the Effect of Timbre on Dissonance
Music is an important part of the day for many of us, but what makes some combinations of sound more pleasant to the ear than others? In this article the authors investigate the role of some characteristics of sound on the perception of a pleasant vs harsh musical note.
Read More...OTGP: An innovative biometric authentication system with on-the-go passwords using a novel typing signature
This manuscript describes a new method of on-the-go passwords using typing characteristics. The authors developed a keyboard and keystroke recording setup and tested it with 30 participants. The results indicated the five chosen parameters are distinct across participants yet consistent across time for each participant, making it a plausible candidate for a behavior-based password system.
Read More...Leveraging transfer learning with convolutional neural networks for cardiovascular disease detection
This study shows the efficacy of leveraging transfer learning, specifically from residual networks, to detect CVDs and possible signs of CVDs. The findings indicate that leveraging transfer learning from residual networks alongside medical professionals is a highly promising approach for CVD detection and diagnosis, warranting further investigation.
Read More...Evaluating key factors in emotion detection models for AI-driven personalized bibliotherapy
This study evaluates the potential of natural language processing (NLP) models in an emotion-driven bibliotherapy framework to improve mental health challenges.
Read More...Predicting clogs in water pipelines using sound sensors and machine learning linear regression
The authors looked the ability of sound sensors to predict clogged pipes when the sound intensity data is run through a machine learning algorithm.
Read More...Deep sequential models versus statistical models for web traffic forecasting
The authors looked at ways to provide better forecasting on website traffic. They found that deep learning models performed better than statistical models.
Read More...Epileptic seizure detection using machine learning on electroencephalogram data
The authors use machine learning and electroencephalogram data to propose a method for improving epilepsy diagnosis.
Read More...Evaluating the clinical applicability of neural networks for meningioma tumor segmentation on 3D MRI
Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
Read More...Predictions of neural control deficits in elders with subjective memory complaints and Alzheimer’s disease
The authors compare neuroimaging datasets to identify potential new biomarkers for earlier detection of Alzheimer's disease.
Read More...Time-Efficient and Low-Cost Neural Network to detect plant disease on leaves and reduce food loss and waste
About 25% of the food grown never reaches consumers due to spoilage, and 11.5 billion pounds of produce from gardens are wasted every year. Current solutions involve farmers manually looking for and treating diseased crops. These methods of tending crops are neither time-efficient nor feasible. I used a convolutional neural network to identify signs of plant disease on leaves for garden owners and farmers.
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