This study provides an innovative architectural model for e-Health systems that aims to improve cyber resilience while maintaining high availability under fluctuating traffic loads. We examined typical cybersecurity i...
详细信息
This study aims to track and categorize milk quality grades using the Logistic Model Tree (LMT) algorithm, based on the analysis of 1,059 milk samples. The focus of the research is to evaluate key factors such as pH v...
详细信息
ISBN:
(数字)9798331533267
ISBN:
(纸本)9798331533274
This study aims to track and categorize milk quality grades using the Logistic Model Tree (LMT) algorithm, based on the analysis of 1,059 milk samples. The focus of the research is to evaluate key factors such as pH value, taste, smell, fat content, concentration, and color, which play a crucial role in determining the overall quality of milk. The goal is to create an efficient and standardized process for sorting cow's milk, which can save significant time and resources in the dairy industry. To identify the most suitable algorithm for this task, the research team initially tested 12 different algorithms, assessing their performance in predicting milk quality. Among these, the Logistic Model Tree (LMT) emerged as the most effective model, achieving an impressive accuracy rate of 99.76%. The LMT algorithm, known for combining the advantages of decision trees and logistic regression, demonstrated its ability to classify milk quality grades with high precision. The results of this study indicate that the LMT algorithm can be a valuable tool for automating the milk quality grading process. By leveraging key attributes such as pH, fat content, and color, it is possible to efficiently sort and grade milk, reducing the need for manual inspection and improving overall productivity in the dairy industry. This method offers a significant improvement over traditional quality assessment techniques and has the potential to be widely adopted for milk sorting and quality control applications.
This research aims to study, design, and develop a brain tumor classification system using artificial intelligence, specifically decision tree algorithms. The system's primary objective is to assist medical person...
详细信息
ISBN:
(数字)9798331533267
ISBN:
(纸本)9798331533274
This research aims to study, design, and develop a brain tumor classification system using artificial intelligence, specifically decision tree algorithms. The system's primary objective is to assist medical personnel in making decisions, as distinguishing between two types of brain tumors-benign and malignant (cancerous)-can be challenging, especially for less experienced medical staff. Due to the similarities between these two types of tumors, it may be difficult for medical practitioners with limited expertise to differentiate between them in a timely manner. The proposed brain tumor classification system is designed to address this challenge. The research team conducted the study over approximately seven months, starting from the second semester of the 2023 academic year through the first semester of the 2024 academic year. Experimental results revealed that among the tree-based algorithms, Random Forest achieved the highest accuracy, followed by M5P. The best average accuracy from the experiments was obtained using a 70% training and 30% testing split, yielding an accuracy of 96.83%. Therefore, the research team selected the 70% training and 30% testing split for model development, as it provided the highest accuracy compared to the 60% training and 40% testing split, and the 80% training and 20% testing split, which showed lower accuracy. The results demonstrate that the 70% training and 30% testing approach is optimal for the brain tumor classification system, ensuring high accuracy in classifying brain tumors.
Dual-arm manipulation is a key enabler for significantly enhancing the interaction between humans and robots, and their capabilities to purposefully shape the surrounding environment. However, the spatiotemporal coord...
详细信息
ISBN:
(数字)9798331509231
ISBN:
(纸本)9798331509248
Dual-arm manipulation is a key enabler for significantly enhancing the interaction between humans and robots, and their capabilities to purposefully shape the surrounding environment. However, the spatiotemporal coordination between the motion of the hands required for this type of actions makes their planning not trivial. A proper definition of these coordination patterns moving from the human example could simplify their translation on the robot side, fostering the generation of effective bimanual tasks. In this work, we propose Multivariate functional Principal Component Analysis (MfPCA) as a mathematical tool to encode inter-hands temporal kinematic covariations in terms of principal spatiotemporal coordination patterns in the Cartesian domain. We compared these patterns extracted from a dataset of human bimanual tasks with those resulting from the usage of classical fPCA, applied indep.ndently to each hand (univariate fPCA). We found that MfPCA allows for a better classification of the tasks, with respect to a state of the art taxonomy. For what concerns motion planning, MfPCA and fPCA yield similar accuracy in the reconstruction of the motion, but with a smaller number of principal components needed in the MfPCA case. These results, although preliminary, can open interesting perspectives for the usage of MfPCA for human-like bimanual motion planning and control of robotic manipulators, as well as for action recognition, to enable a more effective human-robot interaction.
This work describes the implementation of a bioinspired visual processing system on configurable logic, designed for the enhancement of relevant information on a real scene, for its use on a complete system to assist ...
详细信息
Traditionally, engineering studies have focused on preparing students technically and given little importance to social or ethical aspects, nor the ability to work in multi-disciplinary teams. Currently though, these ...
详细信息
In image analysis one often encounters spherical images, for instance in retinal imaging. The behavior of the vessels in the retina is an indicator of several diseases. To automate disease diagnosis using retinal imag...
详细信息
Charmed by the ease with which [vdS95] shows that its program makes progress, I state a theorem that allows for showing progress of a UNITY-like program in an easy way. I also give a proof of that theorem.
Charmed by the ease with which [vdS95] shows that its program makes progress, I state a theorem that allows for showing progress of a UNITY-like program in an easy way. I also give a proof of that theorem.
We introduce a digital hearing aid that compensate the signal spoken in sensorineural impaired listeners with object of improving their intelligibility. The technique used is based on a digital analysis/synthesis of s...
详细信息
We introduce a digital hearing aid that compensate the signal spoken in sensorineural impaired listeners with object of improving their intelligibility. The technique used is based on a digital analysis/synthesis of speech, we divided the input signal into short time blocks then we make a multiband analysis, non linear amplification and synthesis basing us in a sinusoidal model of the voice, according to the subjet's dynamic range in that band. This system has been implemented in real-time using a DSP (TMS320C30) based microprocessor board within a host personal computer IBM PC, having been one of the principal objectives of the project to make an easy implementation VLSI system and low consumption for it to be a portable digital hearing aid.
暂无评论