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Search results for: automated pronunciation error detection
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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...
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Shoreline Extraction Based on LiDAR Data Obtained Using an USV
PublicationThis article explores the use of Light Detection And Ranging (LiDAR) derived point clouds to extract the shoreline of the Lake Kłodno (Poland), based on their geometry properties. The data collection was performed using the Velodyne VLP‐16 laser scanner, which was mounted on the HydroDron Unmanned Surface Vehicle (USV). A modified version of the shoreline extraction method proposed by Xu et al. was employed, comprising of the following...
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Application of Maximum Lenght Sequence in Silent Sonar
PublicationSilent sonars are designed to reduce the distance over which their sounding pulses can be detected by intercept sonars. In order to meet this objective, we can use periodical sounding signals that have low power, a very long duration and wide spectrum. If used in the silent sonar's receiver, matched filtration ensures very good detection of motionless or slow moving targets. However, it is more difficult to detect echo signals...
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Impact of Shifting Time-Window Post-Processing on the Quality of Face Detection Algorithms
PublicationWe consider binary classification algorithms, which operate on single frames from video sequences. Such a class of algorithms is named OFA (One Frame Analyzed). Two such algorithms for facial detection are compared in terms of their susceptibility to the FSA (Frame Sequence Analysis) method. It introduces a shifting time-window improvement, which includes the temporal context of frames in a post-processing step that improves the...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Improving methods for detecting people in video recordings using shifting time-windows
PublicationWe propose a novel method for improving algorithms which detect the presence of people in video sequences. Our focus is on algorithms for applications which require reporting and analyzing all scenes with detected people in long recordings. Therefore one of the target qualities of the classification result is its stability, understood as a low number of invalid scene boundaries. Many existing methods process images in the recording...
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Biometryczna kontrola dostępu
PublicationOpisano szczegółowo algorytm detekcji oraz identyfikacji człowieka na podstawie punktów nodalnych twarzy. Zdefiniowano pojęcia: biometria, proces pomiaru biometrycznego, metody biometrycznej identyfikacji oraz kontrola dostępu. Przedstawiono opis opracowanego systemu biometrycznej identyfikacji wykorzystującego sztuczne sieci neuronowe. Podano wyniki badań oraz przeprowadzono ich wnikliwą dyskusję.Biometrics is the study of automated...
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New First - Path Detector for LTE Positioning Reference Signals
PublicationIn today's world, where positioning applications reached a huge popularity and became virtually ubiquitous, there is a strong need for determining a device location as accurately as possible. A particularly important role in positioning play cellular networks, such as Long Term Evolution (LTE). In the LTE Observed Time Difference of Arrival (OTDOA) positioning method, precision of device location estimation depends on accuracy...
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Current harmonic controller in multiple reference frames for series active power filter integrated with 18-pulse diode rectifier
PublicationThe paper presents the control system and selected results of experimental tests of the AC/DC power converter consisting of an 18-pulse diode rectifier based on coupled reactors and a serial active power filter. Proportional integral controllers with decoupling components are implemented in multiple reference frames for selective line current harmonic suppression. The regulator is provided with a backtracking anti-windup mechanism...
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Process Control and Investigation of Oxidation Kinetics of Postoxidative Effluents Using Gas Chromatography with Pulsed Flame Photometric Detection (GC-PFPD)
PublicationThis article presents the results of investigations on the use of headspace analysis and gas chromatography with pulsed flame photometric detection (HSA-GC-PFPD) to evaluate the effectiveness of oxidation of postoxidative effluents from the production of bitumens. Samples of effluents from the bitumen oxidation unit were used in the experiments. In addition, the kinetics of effluent oxidation was also investigated. The content...
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Integration Data Model of the Bathymetric Monitoring System for Shallow Waterbodies Using UAV and USV Platforms
PublicationChanges in the seafloor relief are particularly noticeable in shallow waterbodies (at depths up to several metres), where they are of significance for human safety and environmental protection, as well as for which the highest measurement accuracy is required. The aim of this publication is to present the integration data model of the bathymetric monitoring system for shallow waterbodies using Unmanned Aerial Vehicles (UAV) and...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublicationDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublicationDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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The Use of Wavelet Analysis to Denoising of Electrocardiography Signal
PublicationThe electrocardiography examination, due to its accessibility and simplicity, has an important role in diagnostics of the heart ailments. It enables quick detection of various heart defects, undetectable by other kinds of diagnostic tools, so it is very popular. Nevertheless, the measured signal is exposed to a different disturbances. Among them, the electromagnetic interferences, drift of reference electrode and high frequency...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublicationSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Neural Architecture Search for Skin Lesion Classification
PublicationDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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AUTOMATED SYSTEM FOR FLUCTUATION ENHANCED GAS SENSING
PublicationResistance gas sensors exhibit random phenomena (resistance noise) which can be utilized to improve gas sensitivity and selectivity. That new emerging technique has to be investigated to recognize optimal parameters for gas detection. It means that a measurement system has to have ability of numerous parameters adjustment (e.g., sampling frequency, heater voltage, polarization current, voltage noise amplification). That fact induced...
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Precise Identification of Different Cervical Intraepithelial Neoplasia (CIN) Stages, Using Biomedical Engineering Combined with Data Mining and Machine Learning
PublicationCervical cancer (CC) is one of the most common female cancers worldwide. It remains a significant global health challenge, particularly affecting women in diverse regions. The pivotal role of human papillomavirus (HPV) infection in cervical carcinogenesis underscores the critical importance of diagnostic strategies targeting both HPV infection and cervical...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Double Bias of Mistakes: Essence, Consequences, and Measurement Method
PublicationThere is no learning without mistakes. However, there is a clash between‘positive attitudes and beliefs’regarding learning processes and the ‘negative attitudes and beliefs’towardthese being accompanied bymistakes. Thisclash exposesa cognitive bias towardmistakesthat might block personal and organizational learning. This study presents an advanced measurement method to assess thebias of mistakes. The essence of it is the...
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The Application of Satellite Image Analysis in Oil Spill Detection
PublicationIn recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublicationVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...