Wyniki wyszukiwania dla: algorithms performance
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Evaluation of Vehicle Routing Problem Algorithms for Transport Logistics Using Dedicated GIS System
PublikacjaThe development and research related to optimization of fleet management is of high interest among many industrial and scientific entities related to logistics and transport. Optimal distribution of transportation resources leads to significant cost reduction. In this context, scientific research related to so called Vehicle Routing Problem (VRP) which relies on determining the shortest transport routes for a strictly limited number...
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Mechatronic design o strongly nonlinear systems on a basis of three wheeled mobile platform
PublikacjaRemarkable grow in demand both of mobile platform operability performance and reduction of project leading time development encourage to apply modern algorithms and reliable engineering tools for the design process. The paper discusses the mechatronic design applied for the surveillance system based on the energy performance index algorithm. The exploited mechatronic techniques i.e. virtual prototyping, Hardware-In-the-Loop Simulation...
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Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption
PublikacjaMany important computational problems require utilization of high performance computing (HPC) systems that consist of multi-level structures combining higher and higher numbers of devices with various characteristics. Utilizing full power of such systems requires programming parallel applications that are hybrid in two meanings: they can utilize parallelism on multiple levels at the same time and combine together programming interfaces...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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On-line P-coloring of graphs
PublikacjaFor a given induced hereditary property P, a P-coloring of a graph G is an assignment of one color to each vertex such that the subgraphs induced by each of the color classes have property P. We consider the effectiveness of on-line P-coloring algorithms and give the generalizations and extensions of selected results known for on-line proper coloring algorithms. We prove a linear lower bound for the performance guarantee function...
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Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with moving measurment window
PublikacjaW artykule rozważana jest łączna estymacja przedziałowa zmiennych i parametrów w złożonej sieci dynamicznej w oparciu niepewne modele parametryczne i ograniczoną liczbę pomiarów. Opracowany został rekursywny algorytm estymacji z przesuwnym oknem pomiarowym, odpowiedni dla monitorowania sieci on-line. Okno pomiarowe pozwala na stabilizowanie klasycznego algorytmu rekurencyjnego estymacji i znacznie poprawienie obcisłości estymat....
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Optimization of FFF Process Parameters by Naked Mole-Rat Algorithms with Enhanced Exploration and Exploitation Capabilities
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Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms
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Improved maximum power point tracking algorithms by using numerical analysis techniques for photovoltaic systems
PublikacjaSolar photovoltaic (PV) panels generate optimal electricity when operating at the maximum power point (MPP). This study introduces a novel MPP tracking algorithm that leverages the numerical prowess of the predictor-corrector method, tailored to accommodate voltage and current fluctuations in PV panels resulting from variable environmental factors like solar irradiation and temperature. This paper delves into the intricate dynamics...
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Better polynomial algorithms for scheduling unit-length jobs with bipartite incompatibility graphs on uniform machines
PublikacjaThe goal of this paper is to explore and to provide tools for the investigation of the problems of unit-length scheduling of incompatible jobs on uniform machines. We present two new algorithms that are a significant improvement over the known algorithms. The first one is Algorithm 2 which is 2-approximate for the problem Qm|p j = 1, G = bisubquartic|Cmax . The second one is Algorithm 3 which is 4-approximate for the problem Qm|p...
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Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements
PublikacjaIn this work the swarm behavior principles of Craig W. Reynolds are combined with deterministic traits. This is done by using leaders with motions based on space filling curves like Peano and Hilbert. Our goal is to evaluate how the swarm of agents works with this approach, supposing the entire swarm will better explore the entire space. Therefore, we examine different combinations of Peano and Hilbert with the already known swarm...
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ADAPTATION OF ENGINEERING FEA-BASED ALGORITHMS TO LCF FAILURE AND MATERIAL DATA PREDICTION IN OFFSHORE DESIGN
PublikacjaThere is an ever growing industrial demand for quantitative assessment of fatigue endurance of critical structural details. Although FEA-based calculations have become a standard in engineering design, problems involving the Low-To-Medium cycle range (101-104) remain challenging. This paper presents an attempt to optimally choose material data, meshing density and other algorithm settings in the context of recent design of the...
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KernelHive: a new workflow-based framework for multilevel high performance computing using clusters and workstations with CPUs and GPUs
PublikacjaThe paper presents a new open-source framework called KernelHive for multilevel parallelization of computations among various clusters, cluster nodes, and finally, among both CPUs and GPUs for a particular application. An application is modeled as an acyclic directed graph with a possibility to run nodes in parallel and automatic expansion of nodes (called node unrolling) depending on the number of computation units available....
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Analysis of IMS/NGN Call Processing Performance Using Phase-Type Distributions Based on Experimental Histograms
PublikacjaThe paper describes our further research done with the proposed analytical and simulation traffic models of the Next Generation Network (NGN), which is standardized for delivering multimedia services with strict quality and includes elements of the IP Multimedia Subsystem (IMS). The aim of our models of a single IMS/NGN domain is to evaluate two standardized call processing performance parameters, which appropriate values are very...
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Comparative Analysis of MicroRNA-Target Gene Interaction Prediction Algorithms Based on Integrated P-Value Calculation
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Effects of scatter plot initial solutions on regular grid facility layout algorithms in typical production models
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Designing RBFNs Structure Using Similarity-Based and Kernel-Based Fuzzy C-Means Clustering Algorithms
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Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublikacjaThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Navigational radar tracking of a maritime terget in clutter: A comparisonof IMM-NN and IMM-PDA filtering algorithms.
PublikacjaW rozdziale omawia się implementację algorytmów estymacji stanu obiektów morskich na podstawie informacji wieloradarowej. Odpowiednia fuzja danych(pomiarów lub wektorów stanu) z wielu radarów, obserwujących wspólny obszar,polepsza możliwości wykrywania celów i umożliwia uzyskanie dokładniejszych ocen parametrów ruchu obserwowanych obiektów. Algorytmy śledzące (TA) opierają się na procedurach asocjacji pomiarów (PTA)....
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Increasing the Geometrical and Interpretation Quality of Unmanned Aerial Vehicle Photogrammetry Products Using Super-Resolution Algorithms
PublikacjaUnmanned aerial vehicles (UAVs) have now become very popular in photogrammetric and remote-sensing applications. Every day, these vehicles are used in new applications, new terrains, and new tasks, facing new problems. One of these problems is connected with flight altitude and the determined ground sample distance in a specific area, especially within cities and industrial and construction areas. The problem is that a safe flight...
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Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
PublikacjaThis paper provides the first review to date which gathers, describes, and assesses, to the best of our knowledge, all available publications on automating cerebral microbleed (CMB) detection. It provides insights into the current state of the art and highlights the challenges and opportunities in this topic. By incorporating the best practices identified in this review, we established guidelines for the development of CMB detection...
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Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.
PublikacjaML algorithms are very effective tools for medical data analyzing, especially at image recognition. Although they cannot be considered as a stand-alone diagnostic tool, because it is a black-box, it can certainly be a medical support that minimize negative effect of human-factors. In high-risk domains, not only the correct diagnosis is important, but also the reasoning behind it. Therefore, it is important to focus on trustworthiness...
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Applying Fuzzy Logic of Expert Knowledge for Accurate Predictive Algorithms of Customer Traffic Flows in Theme Parks
PublikacjaThis study analyzes two forecasting models based on the application of fuzzy logic and evaluates their effectiveness in predicting visitor expenditure and length of stay at a popular theme park. The forecasting models are based on a set of more than 600 decision rules constructed in the form of a complex series of IF-THEN statements. These algorithms store expert knowledge. A descriptive instrument that records the individual visitor's...
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Comparative analysis of IP-based mobility protocols and fast handover algorithms in IEEE 802.11 based WLANs
PublikacjaA rapid growth of IP-based networks and services created the vast collection of resources and functionality available to users by means of an uniform method of access - an IP protocol. At the same time, advances in design of mobile electronic devices allowed them to reach utility level comparable to stationary, desktop computers, while still retaining their mobility advantage. Unfortunately, the base IP protocol does not perform...
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Redesign of the Research Platform for Monitoring, Control and Security of Critical Infrastructure Systems
PublikacjaCritical Infrastructure Systems (CISs) play a key role in modern societies. Their sustainable operation depends heavily on the performance of dedicated structures and algorithms targeting monitoring, control and security aspects. In previous work a Research Platform (RP) for the design and simulation of such systems was presented. This works updates the information on the RP through the description of major hardware and software...
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Adaptive Identification of Underwater Acoustic Channel with a Mix of Static and Time-Varying Parameters
PublikacjaWe consider the problem of identification of communication channels with a mix of static and time-varying parameters. Such scenarios are typical, among others, in underwater acoustics. In this paper, we further develop adaptive algorithms built on the local basis function (LBF) principle resulting in excellent performance when identifying time-varying systems. The main drawback of an LBF algorithm is its high complexity. The subsequently...
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Quality Evaluation of Novel DTD Algorithm Based on Audio Watermarking
PublikacjaEcho cancellers typically employ a doubletalk detection (DTD) algorithm in order to keep the adaptive filter from diverging in the presence of near-end speech signal or other disruptive sounds in the microphone signal. A novel doubletalk detection algorithm based on techniques similar to those used for audio signal watermarking was introduced by the authors. The application of the described DTD algorithm within acoustic echo cancellation...
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The Potential of Greed for Independence
PublikacjaThe well-known lower bound on the independence number of a graph due to Caro and Wei can be established as a performance guarantee of two natural and simple greedy algorithms or of a simple randomized algorithm. We study possible generalizations and improvements of these approaches using vertex weights and discuss conditions on so-called potential functions p(G) : V(G) -> N_0 defined on the vertex set of a graph G for which suitably...
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Optimization of the Hardware Layer for IoT Systems using a Trust Region Method with Adaptive Forward Finite Differences
PublikacjaTrust-region (TR) algorithms represent a popular class of local optimization methods. Owing to straightforward setup and low computational cost, TR routines based on linear models determined using forward finite differences (FD) are often utilized for performance tuning of microwave and antenna components incorporated within the Internet of Things systems. Despite usefulness for design of complex structures, performance of TR methods...
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AUTOMATIC OPTIMIZATION OF ADAPTIVE NOTCH FILTER’S FREQUEN CY TRACKING
PublikacjaEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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Automatic Optimization Of Adaptive Notch Filter’s Frequency Tracking
PublikacjaEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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Automatic Correction of Non-Anechoic Antenna Measurements using Low-Pass Filters
PublikacjaPrototype measurements belong to key steps in the development of antenna structures. They are normally performed in expensive facilities, such as anechoic chambers (ACs). Alternatively, antenna performance can be extracted (at a low cost) in non-anechoic conditions upon appropriate post-processing. Unfortunately, existing correction algorithms are difficult to set up and prone to failure, which limits their practical usefulness....
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Adaptive Wavelet-Based Correction of Non-Anechoic Antenna Measurements
PublikacjaNon-anechoic measurements represent an affordable alternative to evaluation of antenna performance in expensive, dedicated facilities. Due to interferences and noise from external sources of EM radiation, far-field results obtained in non-ideal conditions require additional post-processing. Conventional correction algorithms rely on manual tuning of parameters, which make them unsuitable for reliable testing of prototypes. In this...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublikacjaIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Computer experiments with a parallel clonal selection algorithm for the graph coloring problem
PublikacjaArtificial immune systems (AIS) are algorithms that are based on the structure and mechanisms of the vertebrate immune system. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents a parallel island model algorithm based on the clonal selection principles for solving the Graph Coloring Problem. The performance of...
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Parameter and delay estimation of linear continuous-time systems
PublikacjaIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous identification...
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A simple way of increasing estimation accuracy of generalized adaptive notch filters
PublikacjaGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. It is shown that frequency biases, which arisein generalized adaptive notch filtering algorithms, can be significantly reduced by incorporating in the adaptive loop an appropriately chosen decision delay. The resulting performance...
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Diagnostic system of wheeled tractors detecting four defect's categories
PublikacjaIn a classical approach to damage diagnosis, the technical condition of an analyzed machine is identified based on the measured symptoms, such as performance, thermal state or vibration parameters. In wheeled tractor the fundamental importance has monitoring and diagnostics during exploitation concerning technical inspection and fault element localizations. The main functions of a diagnostic system are: monitoring tractor components...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Parallel multithread computing for spectroscopic analysis in optical coherence tomography
PublikacjaSpectroscopic Optical Coherence Tomography (SOCT) is an extension of Optical Coherence Tomography (OCT). It allows gathering spectroscopic information from individual scattering points inside the sample. It is based on time-frequency analysis of interferometric signals. Such analysis requires calculating hundreds of Fourier transforms while performing a single A-scan. Additionally, further processing of acquired spectroscopic information...
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Some Optimization Methods for Simulations in Volunteer and Grid Systems
PublikacjaIn this chapter, some optimization methods have been presented for improving performance of simulations in the volunteer and grid computing system called Comcute. Some issues related to the cloud computing can be solved by presented approaches as well as the Comcute platform can be used to simulate execution of expensive and energy consuming long-term tasks in the cloud environment. In particular, evolutionary algorithms as well...
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Parameter and delay estimation of linear continuous-time systems
PublikacjaIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is usually described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous...
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A Human Behaviour Model Agent for Testing of Voluntary Computing Systems
PublikacjaPaper presents a design and performance of a voluntary-based distributed computing system testing agent, implementing a human behaviour model. The agent, nicknamed iRobot, was designed and implemented to enable controlled, large scale testing of core algorithms of Comcute - a new voluntary distributed computing platform complementary to BOINC. The main agent design goals were: emulation of human behaviour when browsing web pages,...
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On–line Parameter and Delay Estimation of Continuous–Time Dynamic Systems
PublikacjaThe problem of on-line identification of non-stationary delay systems is considered. The dynamics of supervised industrial processes are usually modeled by ordinary differential equations. Discrete-time mechanizations of continuous-time process models are implemented with the use of dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures mechanized in recursive forms are applied for simultaneous...
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NVRAM as Main Storage of Parallel File System
PublikacjaModern cluster environments' main trouble used to be lack of computational power provided by CPUs and GPUs, but recently they suffer more and more from insufficient performance of input and output operations. Apart from better network infrastructure and more sophisticated processing algorithms, a lot of solutions base on emerging memory technologies. This paper presents evaluation of using non-volatile random-access memory as a...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Model Management for Low-Computational-Budget Simulation-Based Optimization of Antenna Structures Using Nature-Inspired Algorithms
PublikacjaThe primary objective of this study is investigation of the possibilities of accelerating nature-inspired optimization of antenna structures using multi-fidelity EM simulation models. The primary methodology developed to achieve acceleration is a model management scheme which the level of EM simulation fidelity using two criteria: the convergence status of the optimization algorithm, and relative quality of the individual designs...