Search
Search results for: DETECTION ALGORITHMS
-
COMPARISON OF CHOSEN METAHEURISTIC ALGORITHMS FOR THE OPTIMIZATION OF THE ABRASIVE WATER JET TREATMENT PROCESS
Publication -
Binarization of document images using the modified local-global Otsu and Kapur algorithms
Publication -
Intelligent acquisition of audio signals, employing neutral networks and rough set algorithms
PublicationAlgorytmy oparte na sztucznych sieciach neuronowych i metodzie zbiorówprzybliżonych zostały zastosowane do lokalizacji sygnałów fonicznych obar-czonych pasożytniczym szumem i rewerberacjami. Informacja o kierunku napły-wania dźwięku była uzyskiwana na wyjściach tych algorytmów na podstawie re-prezentacji parametrycznej. Przedstawiono wyniki eksperymentalne i przepro-wadzono ich dyskusję.
-
Optimal design and control tuning of the power generation interfaces using genetic algorithms
PublicationReferat przedstawia zastosowania algorytmów genetycznych do rozwiązywania klasycznych problemów w elektrotechnice. Zostały one zastosowane do optymalizacji parametrów regulatora VSC w celu zmniejszenia strat mocy i dostrajania tych parametrów w stanach przejściowych. Wyniki rozważań zostały potwierdzone za pomocą badań symulacyjnych.
-
BIOLOGICAL AGE ASSESSMENT ALGORITHMS BASED ON X-RAY IMAGES OF BONE TISSUE
Publication-
-
Some Artificial Intelligence Driven Algorithms For Mobile Edge Computing in Smart City
PublicationSmart mobile devices can share computing workload with the computer cloud that is important when artificial intelligence tools support computer systems in a smart city. This concept brings computing on the edge of the cloud, closer to citizens and it can shorten latency. Edge computing removes a crucial drawback of the smart city computing because city services are usually far away from citizens, physically. Besides, we introduced...
-
Gradient based basis function algorithms for identification of quasi periodically varying processes.
PublicationW pracy przedstawiono problem identyfikacji systemów, których parametry zmieniają się w sposób pseudookresowy. Pokazano sposób, w jaki można modelować takie systemy przy zastosowaniu metody harmonicznych funkcji bazowych.Przedstawiono dwa sposoby dekompozycji (struktura szeregowa i równoległa) takich układów na elementy związane z poszczególnymi funkcjami bazowymi. Zaprezentowany został sposób śledzenia częstotliwości funkcji...
-
Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublicationThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
-
Validation of Interpolation Algorithms for Multiscale UV-VIS Imaging Using UAV Spectrometer
PublicationIn this study, we present a comparison of popular methods for the interpolation of irregular spatial data in order to determine the applicability of each algorithm for hyperspectral reflectance estimation. The algorithms were benchmarked against a very high-resolution orthoimage from an RGB camera and medium-resolution satellite imagery from Sentinel-2A. We tested five interpolation algorithms: Triangulated Irregular Network (TIN),...
-
Performance of the Direct Sequence Spread Spectrum Underwater Acoustic Communication System with Differential Detection in Strong Multipath Propagation Conditions
PublicationThe underwater acoustic communication (UAC) operating in very shallow-water should ensure reliable transmission in conditions of strong multipath propagation, significantly disturbing the received signal. One of the techniques to achieve this goal is the direct sequence spread spectrum (DSSS) technique, which consists in binary phase shift keying (BPSK) according to a pseudo-random spreading sequence. This paper describes the DSSS...
-
A ship domain-based model of collision risk for near-miss detection and Collision Alert Systems
PublicationThe paper presents a new model of ship collision risk, which utilises a ship domain concept and the related domain-based collision risk parameters. An encounter is here described by five variables representing: degree of domain violation (DDV), relative speed of the two vessels, combination of the vessels’ courses, arena violations and encounter complexity. As for the first three variables, their values can be directly computed...
-
Modeling of medium flow processes in transportation pipelines - the synthesis of their state-space models and the analysis of the mathematical properties of the models for leak detection purposes
PublicationThe dissertation concerns the issue of modeling the pipeline flow process under incompressible and isothermal conditions, with a target application to the leak detection and isolation systems. First, an introduction to the model-based process diagnostics is provided, where its basic terminology, tools, and methods are described. In the following chapter, a review of the state of the art in the field of leak detection and isolation...
-
An Overview of the Development of a Real-Time System for Endoscopic Video Classification
PublicationThe article presents the results of improving endoscopic image classification algorithms in an effort towards applying them in a real-time diagnosis supporting system. Methods for the detection and removal of personal data are presented and discussed. The currently developed recognition algorithms have been improved in terms of accuracy and performance to make them suitable for a real-life implementation. Their test results are...
-
Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
-
Algorytmy przetwarzania widm Ramana w procesie detekcji substancji chemicznych
PublicationRozprawa przedstawia szczegółowo algorytmy, jakie są stosowane podczas przetwarzania widm Ramana, rejestrowanych przenośnym spektrometrem o skończonej rozdzielczości. Pracę podzielono na osiem rozdziałów. W pierwszym określono cel i tezy pracy. Rozdział drugi opisuje podstawowe pojęcia dotyczące zjawiska Ramana oraz zasady budowy urządzeń do pomiarów widm Ramana. W rozdziale trzecim scharakteryzowano błędy występujące podczas pomiarów...
-
An Approach to Bass Enhancement in Portable Computers Employing Smart Virtual Bass Synthesis Algorithms
PublicationThe 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...
-
Evaluation of Vehicle Routing Problem Algorithms for Transport Logistics Using Dedicated GIS System
PublicationThe 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...
-
Comparison of Two Nonlinear Predictive Control Algorithms for Dissolved Oxygen Tracking Problem at WWTP
PublicationThe wastewater treatment plant is classified as a complex system, due to its nonlinear dynamics, large uncertainty of disturbance inputs, multiple time scales in the internal process dynamics, and multivariable structure. The aeration process, in turn, is an important and expensive part of wastewater treatment plant operation. All operating parameters of the aeration in biological processes are to be precisely controlled to provide...
-
Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform
PublicationResults of evaluation of the background subtraction algorithms implemented on a supercomputer platform in a parallel manner are presented in the paper. The aim of the work is to chose an algorithm, a number of threads and a task scheduling method, that together provide satisfactory accuracy and efficiency of a real-time processing of high resolution camera images, maintaining the cost of resources usage at a reasonable level. Two...
-
A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms
PublicationThis 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.
-
Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublicationIn 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...
-
Replica Exchange and Multicanonical Algorithms with the Coarse-Grained United-Residue (UNRES) Force Field
Publication -
Efficient parallel algorithms in global optimization of potential energy functions for peptides, proteins, and crystals
Publication -
The Speedup Analysis in GEM Detector Based Acquisition System Algorithms with CPU and PCIe Cards
Publication -
Application of Graph Theory Algorithms in Non-disjoint Functional Decomposition of Specific Boolean Functions
Publication -
Optimal Placement of Phasor Measurement Unit in Power System using Meta-Heuristic Algorithms
PublicationThe phasor measurement units (PMUs) play an important and vital role in power system monitoring and controlling, since they provide the power system phasors stamped with a common real time reference through a global positioning system (GPS). Indeed, from economical point of view it is not possible to set PMUs in all system buses due to the high cost and the requirement of more complex communication...
-
Comparisons of envelope morphological filtering methods and various regular algorithms for surface texture analysis
Publication -
Methods of Natural Image Preprocessing Supporting the Automatic Text Recognition Using the OCR Algorithms
Publication -
Optimizing acoustic field intesity algorithms using the sound ray surface density method.
PublicationW artykule przedstawiono zagadnienia optymalizacji algorytmów komputerowych obliczeń rozkładów natężeń pola akustycznego w akwenie w zależności od za- mierzonych warunków hydrologicznych pod kątem skrócenia czasu obliczń.
-
Evaluation of propagation parameters of open guiding structures with the use of complex root finding algorithms
PublicationAn efficient complex root tracing algorithm is utilized for the investigation of electromagnetic wave propagation in open guiding structures. The dispersion characteristics of propagated and leaky waves are calculated for a couple of chosen waveguides. The efficiency of the root tracing algorithm is discuses and compared to a global root finding algorithm.
-
Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms
PublicationOver 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...
-
Adaptive stochastic and hybrid nonlinear optimization algorithms for improving the effectiveness of the biological processes at WWTP
PublicationWastewater 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...
-
Task Scheduling – Review of Algorithms and Analysis of Potential Use in a Biological Wastewater Treatment Plant
PublicationThe 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...
-
On Improved-Reliability Design Optimization of High-Frequency Structures Using Local Search Algorithms
PublicationThe role of numerical optimization has been continuously growing in the design of high-frequency structures, including microwave and antenna components. At the same time, accurate evaluation of electrical characteristics necessitates full-wave electromagnetic (EM) analysis, which is CPU intensive, especially for complex systems. As rigorous optimization routines involve repetitive EM simulations, the associated cost may be significant....
-
Comparison of construction algorithms for minimal, acyclic, deterministicfinite state automata from sets of strings.
PublicationArtykuł porównuje różne metody tworzenia minimalnych, acyklicznych, deterministycznych automatów skończonych ze zbiorów słów. Wdrożone i porównane zostały metody przyrostowe, prawie przyrostowe i nieprzyrostowe.
-
A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis 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...
-
Fast Algorithms for Identification of Time-Varying Systems with Both Smooth and Discontinuous Parameter Changes
PublicationThe 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.
-
Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
-
A New, Reconfigurable Circuit Offering Functionality of AND and OR Logic Gates for Use in Algorithms Implemented in Hardware
PublicationThe paper presents a programmable (using a 1-bit signal) digital gate that can operate in one of two OR or AND modes. A circuit of this type can also be implemented using conventional logic gates. However, in the case of the proposed circuit, compared to conventional solutions, the advantage is a much smaller number of transistors necessary for its implementation. Circuit is also much faster than its conventional counterpart. The...
-
Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
-
Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
-
Conditions for increasing the recognition of degradation in thermal-flow diagnostics, taking into account environmental legal aspects
PublicationThe ever-increasing demand for electricity and the need for conventional sources to cooperate with renewable ones generates the need to increase the efficiency and safety of the generation sources. Therefore, it is necessary to find a way to operate existing facilities more efficiently with full detection of emerging faults. These are the requirements of Polish, European and International law, which demands that energy facilities...
-
Speech codec enhancements utilizing time compression and perceptual coding
PublicationA method for encoding wideband speech signal employing standardized narrowband speech codecs is presented as well as experimental results concerning detection of tonal spectral components. The speech signal sampled with a higher sampling rate than it is suitable for narrowband coding algorithm is compressed in order to decrease the amount of samples. Next, the time-compressed representation of a signal is encoded using a narrowband...
-
Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublicationThis paper presents an algorithm for real‐time detection of the heart rate measured on a person’s wrist using a wearable device with a photoplethysmographic (PPG) sensor and accelerometer. The proposed algorithm consists of an appropriately trained LSTM network and the Time‐Domain Heart Rate (TDHR) algorithm for peak detection in the PPG waveform. The Long Short‐Term Memory (LSTM) network uses the signals from the accelerometer...
-
Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
-
Erroneous Vehicle Velocity Estimation Correction Using Anisotropic Magnetoresistive (AMR) Sensors
PublicationMagnetic field sensors installed in the road infrastructure can be used for autonomous traffic flow parametrization. Although the main goal of such a measuring system is the recognition of the class of vehicle and classification, velocity is the essential parameter for further calculation and it must be estimated with high reliability. In-field test campaigns, during actual traffic conditions, showed that commonly accepted velocity...
-
Sparse autoregressive modeling
PublicationIn the paper the comparison of the popular pitch determination (PD) algorithms for thepurpose of elimination of clicks from archive audio signals using sparse autoregressive (SAR)modeling is presented. The SAR signal representation has been widely used in code-excitedlinear prediction (CELP) systems. The appropriate construction of the SAR model is requiredto guarantee model stability. For this reason the signal representation...
-
Audio-visual surveillance system for application in bank operating room
PublicationAn audio-visual surveillance system able to detect, classify and to localize acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of acoustic...
-
Non-invasive blood glucose monitoring with Raman spectroscopy: prospects for device miniaturization
PublicationThe number of patients with diabetes has reached over 350 million, and still continues to increase. The need for regular blood glucose monitoring sparks the interest in the development of modern detection technologies. One of those methods, which allows for noninvasive measurements, is Raman spectroscopy. The ability of infrared light to penetrate deep into tissues allows for obtaining measurements through the skin without its...
-
Processing of acoustical data in a multimodal bank operating room surveillance system
PublicationAn automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of...