Wyszukiwarka
Wyniki wyszukiwania dla: algorithms performance
-
Neural Network Subgraphs Correlation with Trained Model Accuracy
PublikacjaNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
-
Evaluation of Workflow Runtime Platforms in Service Composition
PublikacjaTypically, workflow applications are constructed from basic functionalities that may be realized by alternative services deployed in heterogeneous runtime platforms. Depending on workflow structure and selection of services, the applications differ in attributes such as price, Quality of Service (QoS) and others. In the paper, we propose a method of evaluation of workflow runtime platforms using Data Envelopment Analysis. We present...
-
Sensorless induction motor drive with voltage inverter and sine-wave filter
PublikacjaThis paper presents a speed sensorless control system of an induction motor with an output LC filter. It is known that the parameters design of the filter gives sine wave motor supply voltage but complicates control and estimation process. The reason is that the voltage drop and phase shift between filter input and output signals are imposed, and hence the motor voltages and currents differ from the inverter output waveforms. To...
-
Application of Web-GIS and Cloud Computing to Automatic Satellite Image Correction
PublikacjaRadiometric calibration of satellite imagery requires coupling of atmospheric and topographic parameters, which constitutes serious computational problems in particular in complex geographical terrain. Successful application of topographic normalization algorithms for calibration purposes requires integration of several types of high-resolution geographic datasets and their processing in a common context. This paper presents the...
-
Optimization-Based High-Frequency Circuit Miniaturization through Implicit and Explicit Constraint Handling: Recent Advances
PublikacjaMiniaturization trends in high-frequency electronics have led to accommodation challenges in the integration of the corresponding components. Size reduction thereof has become a practical necessity. At the same time, the increasing performance demands imposed on electronic systems remain in conflict with component miniaturization. On the practical side, the challenges related to handling design constraints are aggravated by the...
-
Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublikacjaBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
-
<title>DOOCS and MatLab control environment for FPGA-based cavity simulator and controller in TESLA (SIMCON 2.1) part I: algorithms</title>
Publikacja -
Contactless Hearing Aid for Infants Employing Signal Processing Algorithms. [Bezkontaktowy aparat słuchowy dla niemowląt wykorzystujący algorytmy przetwarzania sygnału]
PublikacjaZaprojektowany bezkontaktowy aparat słuchowy umiejscawiany jest w łóżeczku niemowlęcia. Aparat składający się z matrycy 4 mikrofonów oraz prototypowej karty z procesorem DSP pracuje w polu swobodnym. Przetworzony sygnał mowy emitowany jest z wykorzystaniem miniaturowych głośników. Opracowane algorytmy pozwalają na elminację akustycznych sprzężeń zwrotnych, które mogą wystepować ze względu na niewielką odległość mikrofonów od głośników...
-
Modified version of roulette selection for evolution algorithms - the fan selection.Zmodyfikowana wersja selekcji metodą ruletki dla algorytmów ewolucyjnych - selekcja ''wachlarzowa''.
PublikacjaW pracy przedstawiono zmodyfikowaną wersję selekcji metodą ruletki - selekcję ''wachlarzową''. Metoda ta polega na zwiększaniu prawdopodobieństw przeżycia lepszych osobników kosztem gorszych. Do testowania i oceny jakości proponowanej metody użyto funkcji testujących spotykanych w literaturze. Uzyskane wyniki selekcji wachlarzowej porównano z wynikami selekcji metodą ruletki i selekcji elitarystycznej.
-
Artificial Intelligence in the Diagnosis of Onychomycosis—Literature Review
PublikacjaOnychomycosis is a common fungal nail infection that is difficult to diagnose due to its similarity to other nail conditions. Accurate identification is essential for effective treatment. The current gold standard methods include microscopic examination with potassium hydroxide, fungal cultures, and Periodic acid-Schiff biopsy staining. These conventional techniques, however, suffer from high turnover times, variable sensitivity,...
-
Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
-
A framework for automatic detection of abandoned luggage in airport terminal
PublikacjaA framework for automatic detection of events in a video stream transmitted from a monitoring system is presented. The framework is based on the widely used background subtraction and object tracking algorithms. The authors elaborated an algorithm for detection of left and removed objects based on mor-phological processing and edge detection. The event detection algorithm collects and analyzes data of all the moving objects in...
-
Customized crossover in evolutionary sets of safe ship trajectories
PublikacjaThe paper presents selected aspects of evolutionary sets of safe ship trajectories-a method which applies evolutionary algorithms and some of the assumptions of game theory to solving ship encounter situations. For given positions and motion parameters of the ships, the method finds a near optimal set of safe trajectories of all ships involved in an encounter. The method works in real time and the solutions must be returned within...
-
Two Time-Scale Hierarchical Control of Integrated Quantity and Quality in Drinking Water Distribution Systems
PublikacjaThe paper considers a feedback optimising control of drinking water distribution systems (DWDS). Although the optimised pump and valves scheduling and disinfectant injection control attracted considerable attention over last two decades most of the contributions were limited to an open-loop optimisation repetitively performed during the DWDS operation. Also, while a strong interaction between the water quantity and quality exists...
-
Variable-structure algorithm for identification of quasi-periodically varying systems
PublikacjaThe paper presents a variable-structure version of a generalized notchfiltering (GANF) algorithm. Generalized notch filters are used for identification of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The proposed algorithm is a cascade of two GANF filters: a multiple-frequency "precise" filter bank, used for precise system tracking, and a...
-
Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublikacjaThis 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...
-
Influence of a Radio Frequency on RF Fingerprinting Accuracy Based on Ray Tracing Simulation
PublikacjaIn this paper the influence of a radio signal frequency on performance of Indoor Positioning System based on fingerprinting has been examined using ray-tracing simulations. It has been simulated how spatial distribution of an RF signal strength change with the signal’s frequency. The results were used to show its’ impact on the behavior of localization algorithms that are employing RSS measurements to determine node’s position...
-
Min-max optimization of node‐targeted attacks in service networks
PublikacjaThis article considers resilience of service networks that are composed of service and control nodes to node-targeted attacks. Two complementary problems of selecting attacked nodes and placing control nodes reflect the interaction between the network operator and the network attacker. This interaction can be analyzed within the framework of game theory. Considering the limited performance of the previously introduced iterative...
-
Optimally regularized local basis function approach to identification of time-varying systems
PublikacjaAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state of the art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
-
Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublikacjaThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
-
BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublikacjaDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
-
MICROSEISMIC EVENT DETECTION USING DIFFERENT ALGORITHMS ON REAL DATA FROM PATCH ARRAY GEOPHONE GRID FROM EASTERN POMERANIA FRACTURING JOB
PublikacjaThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing process. Hydraulic fracturing is a method of reservoir stimulation used especially for unconventional gas recovery. A matrix of several thousand geophones is placed on the surface of earth to record every little tremor of ground induced by fracturing process. Afterwards, the signal is analysed and the place of tremor occurrence...
-
Sparse autoregressive modeling
PublikacjaIn 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...
-
A self-optimization mechanism for generalized adaptive notch smoother
PublikacjaTracking of nonstationary narrowband signals is often accomplished using algorithms called adaptive notch filters (ANFs). Generalized adaptive notch smoothers (GANSs) extend the concepts of adaptive notch filtering in two directions. Firstly, they are designed to estimate coefficients of nonstationary quasi-periodic systems, rather than signals. Secondly, they employ noncausal processing, which greatly improves their accuracy and...
-
From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
-
Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System
PublikacjaBluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in...
-
Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
-
Two Approaches to Constructing Certified Dominating Sets in Social Networks
PublikacjaSocial networks are an important part of our community. In this context, certified dominating sets help to find in networks a group of people, referring as officials, such that 1) for each civilian, there is an official that can serve the civilian, and 2) no official is adjacent to exactly one civilian, to prevent potential abuses. To delve deeper into this topic, this study considers two approaches to the problem of finding certified...
-
Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
-
Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublikacjaWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
-
SegSperm - a dataset of sperm images for blurry and small object segmentation
Dane BadawczeMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
-
Analysis and Optimization of Dimensional Accuracy and Porosity of High Impact Polystyrene Material Printed by FDM Process: PSO, JAYA, Rao, and Bald Eagle Search Algorithms
Publikacja -
Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
-
A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublikacjaPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
-
Low-Cost Unattended Design of Miniaturized 4 × 4 Butler Matrices with Nonstandard Phase Differences
PublikacjaDesign of Butler matrices dedicated to Internet of Things and 5th generation (5G) mobile systems—where small size and high performance are of primary concern—is a challenging task that often exceeds capabilities of conventional techniques. Lack of appropriate, unified design approaches is a serious bottleneck for the development of Butler structures for contemporary applications. In this work, a low-cost bottom-up procedure for...
-
Three solvers for MIMO noise radar clutter cancellation - a performance comparison
PublikacjaThe problem of canceling strong clutter echos in a MIMO noise radar is considered. Execution times of three algorithms is compared. The first solution is a standard Least Squares approach employing Cholesky decomposition of the transmitted signal sample autocorrelation matrix. The second approach is based on careful waveform design which guarantees that the signal sample autocorrelation matrix has Toeplitz structure. This enables...
-
Improving Clairvoyant: reduction algorithm resilient to imbalanced process arrival patterns
PublikacjaThe Clairvoyant algorithm proposed in “A novel MPI reduction algorithm resilient to imbalances in process arrival times” was analyzed, commented and improved. The comments concern handling certain edge cases in the original pseudocode and description, i.e., adding another state of a process, improved cache friendliness more precise complexity estimations and some other issues improving the robustness of the algorithm implementation....
-
Single-phase power electronics transformer with active functions for smart grid
PublikacjaThis paper presents the control of one cell of a modular single-phase power electronics transformer with active functions for meeting the smart grid concept. In this way, the converter could be used not only as a conventional transformer but also for grid such as reactive power, harmonic elimination and energy storage. The topology of the cell is composed by a bidirectional converter with three stages: a half bridge in the input...
-
Spatial Calibration of a Dual PTZ-Fixed Camera System for Tracking Moving Objects in Video
PublikacjaA dual camera setup is proposed, consisting of a fixed (stationary) camera and a pan-tilt-zoom (PTZ) camera, employed in an automatic video surveillance system. The PTZ camera is zoomed in on a selected point in the fixed camera view and it may automatically track a moving object. For this purpose, two camera spatial calibration procedures are proposed. The PTZ camera is calibrated in relation to the fixed camera image, using interpolated...
-
Measurements of transmission properties of Acoustic Communication Channels
PublikacjaTough transmission properties of shallow water acoustic channels (SWAC) highly limit the use of underwater acoustic communication (UAC) systems. An adaptive matching of modulation and signaling schemes to instantaneous channel conditions is needed for reliabledata communications. This creates, however, unique challenges for designers when compared to radio transmission systems. When communication system elements are in move, the...
-
Highly Precised and Efficient Robot-Based ESPAR Antenna Measurements in Realistic Environments
PublikacjaIn this paper, we present a novel approach utilizing a small Unmanned Surface Vehicle (USV) equipped with Global Navigation Satellite System (GNSS) technology to facilitate large-scale outdoor automated measurements. The system employs dedicated software and measurement scripts to autonomously navigate the robot along predefined routes, stopping at multiple points for data collection. This method minimizes observational error and...
-
Metoda diagnostyki cieplno-przepływowej turbin parowych wykorzystująca elementy algorytmów genetycznych
PublikacjaRozprawa doktorska poświęcona jest opisowi budowania metody diagnostyki cieplno-przepływowej z wykorzystaniem elementów algorytmów genetycznych. Do tworzenia założeń i algorytmów metody posłużono się przykładem funkcjonowania bloku elektrowni kondensacyjnej ze szczególnym uwzględnieniem układu łopatkowego turbiny parowej. Celem pracy jest zbudowanie metody diagnostyki cieplno-przepływowej. Zadaniem metody jest przeprowadzenie procesu...
-
Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublikacjaIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
-
Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
-
Reduced-cost design closure of antennas by means of gradient search with restricted sensitivity update
PublikacjaDesign closure, i.e., adjustment of geometry parameters to boost the performance, is a challenging stage of antenna design process. Given complexity of contemporary structures, reliable parameter tuning requires numerical optimization and can be executed using local algorithms. Yet, EM-driven optimization is a computationally expensive endeavour and reducing its cost is highly desirable. In this paper, a modification of the trust-region...
-
Real-Time Gastrointestinal Tract Video Analysis on a Cluster Supercomputer
PublikacjaThe article presents a novel approach to medical video data analysis and recognition. Emphasis has been put on adapting existing algorithms detecting le- sions and bleedings for real time usage in a medical doctor's office during an en- doscopic examination. A system for diagnosis recommendation and disease detec- tion has been designed taking into account the limited mobility of the endoscope and the doctor's requirements. The...
-
On evolutionary computing in multi-ship trajectory planning, Applied Intelligence
PublikacjaThe paper presents the updated version of Evolutionary Sets of Safe Ship Trajectories: a method which applies evolutionary algorithms and some of the assumptions of game theory to solving ship encounter situations. For given positions and motion parameters of the ships,the method finds a near optimal set of safe trajectories of all ships involved in an encounter. The method works in real time and the solutions must be returned...
-
Productivity Enhancement by Prediction of Liquid Steel Breakout during Continuous Casting Process in Manufacturing of Steel Slabs in Steel Plant Using Artificial Neural Network with Backpropagation Algorithms
Publikacja -
Computationally Efficient Design Optimization of Compact Microwave and Antenna Structures
PublikacjaMiniaturization is one of the important concerns of contemporary wireless communication systems, especially regarding their passive microwave components, such as filters, couplers, power dividers, etc., as well as antennas. It is also very challenging, because adequate performance evaluation of such components requires full-wave electromagnetic (EM) simulation, which is computationally expensive. Although high-fidelity EM analysis...
-
Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...