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Wyniki wyszukiwania dla: algorithms performance
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Fast Algorithms for Identification of Time-Varying Systems with Both Smooth and Discontinuous Parameter Changes
PublikacjaThe problem of noncausal identification of a time-varying linear system subject to both smooth and occasional jump-type changes is considered and solved using the preestimation technique combined with the basis function approach to modeling the variability of system parameters. The proposed estimation algorithms yield very good parameter tracking results and are computationally attractive.
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Adaptive stochastic and hybrid nonlinear optimization algorithms for improving the effectiveness of the biological processes at WWTP
PublikacjaWastewater treatment plays an important factor in the modern world. Insufficient treatment may result in environmental pollution which can further lead to disasters and diseases. However, processes that take place inside wastewater treatment plants (WWTP) are highly complex in nature, therefore it is difficult to design an efficient, optimal control system. The problem regarding biochemical reactions inside Sequential Batch Reactor...
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Comparisons of envelope morphological filtering methods and various regular algorithms for surface texture analysis
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Replica Exchange and Multicanonical Algorithms with the Coarse-Grained United-Residue (UNRES) Force Field
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Efficient parallel algorithms in global optimization of potential energy functions for peptides, proteins, and crystals
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The Speedup Analysis in GEM Detector Based Acquisition System Algorithms with CPU and PCIe Cards
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A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms
PublikacjaThis paper presents a comparison of different normalization methods applied to the set of feature vectors of music pieces. Test results show the influence of min-nlax and Zero-Mean normalization methods, employing different distance functions (Euclidean, Manhattan, Chebyshev, Minkowski) as a pre-processing for genre classification, on k-Nearest Neighbor (kNN) algorithm classification results.
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An Approach to Bass Enhancement in Portable Computers Employing Smart Virtual Bass Synthesis Algorithms
PublikacjaThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The developed algorithms are related to intelligent, rule-based setting of synthesis parameters according to music genre of an audio excerpt and to the type of a portable device in use. To find optimum synthesis parameters of the VBS algorithms, subjective listening tests based on a parametric procedure...
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublikacjaIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms
PublikacjaOver the past few decades, the increasing number of vehicles and imperfect road traffic management have been sources of congestion in cities and reasons for deteriorating health of its inhabitants. With the help of computer simulations, transport engineers optimise and improve the capacity of city streets. However, with an enormous number of possible simulation types, it is difficult to grasp valuable, innovative solutions which...
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Task Scheduling – Review of Algorithms and Analysis of Potential Use in a Biological Wastewater Treatment Plant
PublikacjaThe idea of task scheduling is to increase the efficiency of a system by minimising wasted time, evenly loading machines, or maximising the throughput of machines. Moreover, the use of appropriate scheduling algorithms often leads to a reduction in the energy costs of the process. Task scheduling problems are found in a variety of industrial areas, and their scale changes significantly depending on the problem. This review shows...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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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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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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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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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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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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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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UAV measurements and AI-driven algorithms fusion for real estate good governance principles support
PublikacjaThe paper introduces an original method for effective spatial data processing, particularly important for land administration and real estate governance. This approach integrates Unmanned Aerial Vehicle (UAV) data acquisition and processing with Artificial Intelligence (AI) and Geometric Transformation algorithms. The results reveal that: (1) while the separate applications of YOLO and Hough Transform algorithms achieve building detection...
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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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Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms
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Optimization of FFF Process Parameters by Naked Mole-Rat Algorithms with Enhanced Exploration and Exploitation Capabilities
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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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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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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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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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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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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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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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Comparative Analysis of MicroRNA-Target Gene Interaction Prediction Algorithms Based on Integrated P-Value Calculation
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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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Credit Decision Support Based on Real Set of Cash Loans Using Integrated Machine Learning Algorithms
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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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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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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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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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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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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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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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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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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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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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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...