Precision farming technologies refer to a set of cutting-edge tools and strategies implemented optimize the management plantation. Smart meter devices, IoT technologies, Wireless Sensor Networks are only few examples innovative systems increasingly employed from an Agriculture 4.0 point view. Recent literature has paid close attention role Artificial Intelligence (AI) Deep Learning (DL) algorithms in helping farmers improving soil productivity. In this regard, paper presents design Network...

In the past three years, deep convolutional neural networks (DCNNs) have achieved promising results in detecting skin cancer. However, improving accuracy and efficiency of automatic detection melanoma is still urgent due to visual similarity benign malignant dermoscopic images. There also a need for fast computationally effective systems mobile applications targeting caregivers homes. This paper presents You Only Look Once (Yolo) algorithms, which are based on DCNNs applied melanoma. The...

Skin cancers are the most diagnosed worldwide, with an estimated > 1.5 million new cases in 2020. Use of computer-aided diagnosis (CAD) systems for early detection and classification skin lesions helps reduce cancer mortality rates. Inspired by success transformer network natural language processing (NLP) deep convolutional neural (DCNN) computer vision, we propose end-to-end CNN hybrid model a focal loss (FL) function to classify lesion images. First, extracts low-level, local feature maps...

The recent development of highly automated machinery and intelligent industrial plants has increasingly enabled the continuous monitoring their efficiency condition, with aim maintaining high production minimal malfunctions. Typical condition fault detection applications are often achieved using acoustic vibrational techniques, but availability distributed electrical measurements opens new opportunities for impact on systems. Even if artificial intelligence-based approaches can be used to...

Early detection of melanoma is one the greatest challenges dermatologic practice today. A new diagnostic method, "ELM 7 point checklist", defines a set seven features, based on colour and texture parameters, which describe malignancy lesion. It has been presented as faster with same accuracy than traditional ABCD criteria in diagnosis melanoma. In this paper system for automated melanocytic skin lesions, ELM checklist, introduced.

This paper describes the implementation and experimental verification of an instrument fault detection (IFD) scheme for stroke sensors. In scheme, a nonlinear autoregressive with exogenous inputs (NARX) neural network works as soft sensor generation residuals, while rule-based decision maker provides classification. The was thought to be implemented in firmware central units control semiactive suspension systems motorbikes. Execution times compatible real-time application constraints are...

The use of microelectro-mechanical systems (MEMS)-based inertial measurement units (IMUs) is widespread in many applications concerning monitoring, diagnostic, and/or controlling navigation and transportation systems, as well low-cost for automotive aeronautical fields. data provided by the set sensors typically present IMUs, accelerometers, gyroscopes, magnetometers, are often used also feeding suitable filtering positioning algorithms able to correct attitude path vehicle on which they...

Skin cancer is one of the most threatening cancers, which spreads to other parts body if not caught and treated early. During last few years, integration deep learning into skin has been a milestone in health care, dermoscopic images are right at center this revolution. This review study focuses on state-of-the-art automatic diagnosis from based learning. work thoroughly explores existing its application diagnosing images. aims present summarize latest methodology melanoma classification...

Early detection of melanoma is one the greatest challenges dermatologic practice today. A new diagnostic method, "ELM 7 point checklist", defines a set seven features, based on color and texture parameters, which describe malignancy lesion. This paper describes image processing algorithms developed for occurrence "Atypical Pigment Network" Vascular Pattern" that are two important criteria "7-point checklist" method

Epiluminescence microscopy (ELM) is a non-invasive technique used to enhance visualization of microscopic structures pigmented lesions for the early detection melanoma. The 7-point check-list diagnostic method that requires identification only seven dermoscopic criteria, defining image through use algorithms. This paper describes an experimental automated diagnosis set-up melanocytic skin processing methodology focused on finding presence different epiluminescence parameters. In this allows...

The environmental acoustic noise is considered as a big risk for today's population health. Consequently, the regulations in many countries commit themselves to control exposition of people, imposing limits level. In comparison between measured value and threshold, uncertainty has be taken into account. this paper, procedure evaluation traffic measurements due variability measurand proposed. A deep analysis five bootstrap (normal, basic percentile, t-student, bias corrected accelerated...

Nowadays, the air quality has become one of most important problem in modern cities. The particulate matters represents principal causes respiratory problems. industrial products and vehicular traffic had contributed to several phenomena increasing atmospheric pollutants as ammonia, carbon dioxide, PM so on. Although importance regarding monitoring this substances, European countries still be a low number measurement stations probably due high cost them not neglectable dimensions. However,...

This paper deals with ELM image processing for automatic analysis of pigmented skin lesions which represents one the greatest challenges dermatologic practice today. The "ELM 7 point checklist" defines a set seven features, based on colour and texture parameters, describe malignancy lesion. It has been revealed as faster same accuracy than traditional ABCD criteria in diagnosis melanoma. A preliminary approach to automated melanocytic lesions, checklist is proposed. In particular, algorithms...

Early detection of melanoma is one the greatest challenges dermatologic practice today. A new diagnostic method, "ELM 7 point checklist", defines a set seven features, based on colour and texture parameters, which describe malignancy lesion. It has been presented as faster with same accuracy than traditional ABCD criteria in diagnosis melanoma. In this paper system for automated melanocytic skin lesions, ELM checklist, introduced.

Advanced metering infrastructures (AMIs) are thought to deliver services both citizens and utility companies in smart city context. All based on battery powered terminal devices (smart meters), which get the internet through suitable gateways. Smart meters usually featured with radio frequency short range antennas must be within coverage of at least one gateway. The economic sustainability AMIs depends right compromise between number necessary gateways lifetime device battery. In this paper...

This article describes the development and experimental verification of an instrument fault accommodation (IFA) scheme for front rear suspension stroke sensors in motorcycles equipped with electronically controlled semiactive systems. In particular, IFA is based on use nonlinear autoregressive exogenous inputs (NARX) neural networks (NNs) employed as soft feeding control strategy back measurement even presence faults occurred sensors. Different NN architectures have been trained tuned by...

Deep convolution neural networks (DCNNs) enable effective methods to predict the melanoma classes otherwise found with ultrasonic extraction. However, gathering large datasets in local hospitals Sweden can take years. Small will result models poor accuracy and insufficient generalization ability, which has a great impact on result. This paper proposes use K-Fold cross validation approach based DCNN algorithm working small sample dataset. The performance of model is verified via Vgg16...