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.

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.

The main objective of this study was to investigate the correlation between the indoor and outdoor ambient dose equivalent rates measured by the ion chamber inside and around the historical sacral objects at a few locations in Bosnia and Herzegovina. The investigated objects made of the traditional building materials were built in the Late Medieval, Post Medieval, and Ottoman Period of Bosnia and Herzegovina history. The LUDLUM Model 9DP instrument based on a pressurized ion chamber was selected for natural low level radiation measurements since the ionisation chambers have higher sensitivities than the other types of detectors. The detection capability of the LUDLUM Model 9DP pressurized ion chamber was examined in the laboratory conditions with a source of low activity and under natural environmental radiation conditions by measuring the indoor and outdoor dose rates. A weak positive correlation was found between the ambient dose equivalent rates inside the historical sacral objects and the dose rates outside the objects. The average evaluated value of the indoor to outdoor dose rate ratio of 1.07 for the studied historic objects is less than that obtained for the contemporary building materials such as concrete. No study on the indoor to outdoor dose rate ratio in Bosnia and Herzegovina measured by the LUDLUM 9DP dose rate meter based on an ion chamber has been conducted yet. In addition to direct measurements, the first gamma spectrometric analysis of a few samples of building materials from the Late Medieval period in Bosna and Herzegovina was performed. The results of the gamma analysis revealed almost uniform distribution of primordial radionuclides in the investigated samples. It was demonstrated that such materials had the reduced content of radioactive isotopes compared to the contemporary building materials and therefore they could have potential advantages in specific applications related to the environmentally sustainable architecture.

Introduction : In recent time medical image processing and analysis become an essential component in clinical practice. Medical images have a huge data to process due to increased image resolution. These tasks are inherently parallel in nature, so will fit to naturally to parallel processors like Central Processing Unit (CPU) and Graphics Processing Unit (GPU). Methods : In this work several common used image processing algorithms for 2D and 3D were evaluated regarding the computation performance increase using the GPUs and CPUs on a Personal Computer (PC). Results : For tested algorithms GPU leads to decreasing running times from 1.1 to 422 times.

Signal, image and Synthetic Aperture Radar imagery algorithms in recent time are used in a daily routine. Due to huge data and complexity, their processing is almost impossible in a real time. Often image processing algorithms are inherently parallel in nature, so they fit nicely into parallel architectures multicore Central Processing Unit (CPU) and Graphics Processing Unit GPUs. In this paper image processing algorithms were evaluated, which are capable to execute in parallel manner on several platforms CPU and GPU. All algorithms were tested in TensorFlow, which is a novel framework for deep learning, but also for image processing. Relative speedups compared to CPU were given for all algorithms. TensorFlow GPU implementation can outperform multi-core CPUs for tested algorithms, obtained speedups range from 3.6 to 15 times.

Medical image registration plays an important part in most today’s clinical procedures. Registration goal is to find transformation which warps one image into the space of another. Registration of moving organs in human body has a significant part in therapy planning. This task is harder in cases when one organ (tissue) slides along another, i.e. in a case of discontinuities in the motion field. Discontinuities introduce unwanted transformations which often lead to poor or unsatisfied registration results. In this paper we evaluate one form of discontinuities for two well-known and used registration algorithms namely Free Form Deformation and Demons.

The ferroresonant states associated with inductive voltage transformers may be generated by elimination of single-phase short-circuits in isolated distribution networks. The paper presents a qualitative analysis of causes of ferroresonance initiation, and significant parameters impacting ferroresonance, like zerosequence system capacitance and the number of connected voltage transformers. Using simulations, the causes of short-circuit occurrence for different system scenarios are investigated and damping devices for ferroresonance mitigations in a 35 kV isolated network are presented.