The original serial implementation of the segmentation algorithm exhibits suboptimal performance, motivating a systematic optimization effort without compromising accuracy.

This study deals with the unfolded quantities based on the time intervals between successive neutron events from the aspect of the power law. Neutrons from spontaneous fission in special nuclear material induce fission in most cases. In this study, it was demonstrated that the inverse value of the number of induced neutrons decreases following a power function with the increasing radius of a plutonium metal sphere. In addition, it was considered an increase in the neutron background level with increasing altitudes. The inverse value of the mean neutron counting rate depending on altitudes can be described with a power function merely for higher elevations. A linear relationship was obtained by plotting the quantities on logarithmic axes against each other indicating generally a power law relationship for both investigated phenomena. The results of this study showed a connection between two seemingly unrelated neutron phenomena through power laws based on the distributions of time intervals between successive neutron counts. The empirical evidence implies that a connection between the observed quantities in a log-log plot is unchanged except for a multiplicative constant.

This paper presents a simulation study of a first order plus dead time system (FOPDT) controlled with proportional integral derivative (PID) controller tuned by optimizing several objective functions and treating several different scenarios. Objective functions used are Integral of Absolute Magnitude of Error (IAE), Integral of Time multiplied by the Absolute Error (ITAE), Integral of the Square Error (ISE), Integral of Time multiplied by the Square Error (ITSE) and Mean of the Integral Square Error (MISE). Scenarios include unit step response and total energy effort analysis: with and without disturbance present, unit step response in case of model to true system mismatch in time constants. Time constants being dominant time constant of the process and dead time constant. optimization algorithm used is particle swarm optimization (PSO) algorithm.

Systematic monitoring of environmental radionuclides with the aim of early warning in emergency situations in Federation of Bosnia and Herzegovina (FB&H) was established in 2004. Environmental radiation monitoring network includes six automatic monitoring stations over the FB&H territory. This paper deals with the first study of ambient dose equivalent rates collected over the period of 2012-2017 with the main objective to investigate the temporal and spatial variations in the outdoor background radiation. The correlation analysis between the continuously acquired gamma dose rates and the simultaneous meteorological records on a daily basis contributed to a better interpretation of daily variations of the measured data. Derivation of the net ambient dose equivalent rates and the terrestrial radiation component from routine monitoring data was carried out as a prerequisite for adequate monitoring of background radiation. In addition, the terrestrial background component was estimated from the soil radionuclides at the same monitoring sites. The correlation analysis in a form of bivariation statistics between activity concentration of each pair of primordial radionuclides in the soil samples show that primordial radionuclides are not uniformly distributed over the FB&H territory. The mean values with the combined standard uncertainties for the terrestrial component evaluated from the soil radionuclides of (74.4 ± 12.5) nSv/h and from routine monitoring data of (81.8 ± 17.9) nSv/h are within the ranges reported for East and South European countries. The sources of statistical and systematic uncertainties were analyzed. The applied procedure of the terrestrial radiation component evaluation based on the daily monitoring data could be of complementary significance related to the existing evaluation procedures with a smaller sampling time of monitoring records. The results of the present study indicate that the acquired monitoring data are reliable enough to correctly assess the radiological situation in FB&H. In case of an emergency situation, the results obtained could be useful for a better identification of contaminated area.

In this paper, we present an implementation and analysis of the mean shift algorithm. The mean shift is a general non-parametric mode finding/clustering procedure widely used in image processing and analysis and computer vision techniques such as image denoising, image segmentation, motion tracking, etc.

Artefacts caused by the presence of metallic implants and prosthesis appear as dark and bright streaks in computed tomography (CT) images, that obscure the information about underlying anatomical structures. These phenomena can severely degrade the image quality and hinder the correct diagnostic interpretation. Although many techniques for the reduction of metal artefacts have been proposed in literature, their effectiveness is still limited. In this paper, an application of a convolutional neural networks (CNN) to the problem of metal artefact reduction (MAR) in the image domain is investigated. Experimental results show that image-domain CNN can substantially suppresses streaking artefacts in the reconstructed images.