In robotic radiotherapy, systematic latencies have to be compensated by prediction of external optical surrogates. We investigate possibilities to increase the prediction accuracy using multi-modal sensors. The measurement setup includes position, acceleration, strain and flow sensors. To select the most relevant and least redundant information from the sensors and to limit the size of the feat...

Ultrasonography is an invaluable and widely used medical imaging tool. Nevertheless, automatic texture analysis on ultrasound images remains a challenging issue. This work presents and investigates a texture representation scheme on thyroid ultrasound images for the detection of hypoechoic and isoechoic thyroid nodules, which present the highest malignancy risk. The proposed scheme is based on ...

Abs t rac t . In this paper we examine the edge searching problem on pseudo 3-sided solid orthoconvex grids. We obtain a closed formula that expresses the minimum number of searchers required to search a pseudo 3-sided solid orthoconvex grid. From that formula and a rather straight forward algorithm we show that the problem is in P. We obtain a parallel version of that algorithm that places the...

Abstract Food instability has been linked to infertility, health issues, accelerated aging, incorrect insulin regulation, and more. Innovative approaches increased food availability quality. Agriculture environment monitoring systems need IoT machine learning. sensors provide all necessary data for agriculture production forecast, fertilizer management, smart irrigation, crop monitoring, diseas...

Needs of feature selection in medium and large problems increases in many fields including medical and image processing fields. Previous comparative studies of feature selection algorithms are not satisfactory in problem size and in criterion function. In addition, no way has not shown to compare algorithms with different objectives. In this study, we propose a unified way to compare a large va...

considering the importance of cd and u as pollutants of the environment, this study aims to predict the concentrations of these elements in a stream sediment from the eshtehard region in iran by means of a developed artificial neural network (ann) model. the forward selection (fs) method is used to select the input variables and develop hybrid models by ann. from 45 input candidates, 13 and 14 ...

• Forward and Inverse 32-, 64-, 128-, 256-, 512-, 1,024-, and 2,048-Point Complex FFT • Decimation–In-Time (DIT) Radix-2 Implementation Optimized for Actel FPGAs • Selection of Unconditional or Conditional Block Floating-Point Scaling • Embedded RAM-Block-Based Twiddle Factor Generator • 8to 16-Bit Configurable Input/Output Data and Twiddle Coefficients Precision • Naturally Ordered Input and O...

The feature selection problem in the field of classification consists of obtaining a subset of variables to optimally realize the task without taking into account the remainder variables. This work presents how the search for this subset is performed using the Scatter Search metaheuristic and is compared with two traditional strategies in the literature: the Forward Sequential Selection (FSS) a...

A method consisting of the combination of the Synthetic Minority Over-Sampling TEchnique (SMOTE) and the Sequential Forward Floating Selection (SFFS) technique is used to do band selection in a highly imbalanced, small size, two-class multispectral dataset of melanoma and non-melanoma lesions. The aim is to improve classification rate and help to identify those spectral bands that have a more i...

Multiresolution analysis (MRA) over graph representation of EEG data has proved to be a promising method for offline brain-computer interfacing (BCI) data analysis. For the first time we aim to prove the feasibility of the graph lifting transform in an online BCI system. Instead of developing a pointer device or a wheel-chair controller as test bed for human-machine interaction, we have designe...