Search
Filters
total: 6145
filtered: 747
Search results for: SEAFLOOR CLASSIFICATION
-
External Validation Measures for Nested Clustering of Text Documents
PublicationAbstract. This article handles the problem of validating the results of nested (as opposed to "flat") clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to...
-
Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublicationThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
-
Vibroflotation Control of Sandy Soils using DMT and CPTU
PublicationVibroflotation is a typical improvement method for the cohesionless deposits of high thickness. The compaction method was applied to densify sandy deposits in Gdynia Port. Compaction control was verified with CPTU and DMT tests. Some examples of interpretation of soundings in pre-treated and compacted sands are shown. The classification diagrams are given for pre-treated and compacted sand. The stress history of the deposits is...
-
Recognizing emotions on the basis of keystroke dynamics
PublicationThe article describes a research on recognizing emotional states on the basis of keystroke dynamics. An overview of various studies and applications of emotion recognition based on data coming from keyboard is presented. Then, the idea of an experiment is presented, i.e. the way of collecting and labeling training data, extracting features and finally training classifiers. Different classification approaches are proposed to be...
-
An Analysis of the Relationship between the Architecture and the Structure of a Vessel on the Example of the Reconstruction Design Process of the Historical Sailing Yacht "General Zaruski" Carried Out between 2009 and 2012
PublicationThe article analyzes the relation between architecture and structure of a vessel on the example of the reconstruction design of a wooden sailing yacht "General Zaruski" built in Ekanӓs, Sweden in 1939. Based on the documentation of "Kaparen" (sister yacht), "Mloda Gwardia" (ex "General Zaruski") and the reconstruction classification project made by the authors, the impact of functional, spatial and aesthetic design objectives (e.g....
-
Rynek inwestowania w sztukę jako przykład inwestycji alternatywnej
PublicationW opracowaniu przedstawiono klasyfikację inwestycji emocjonalnych jako jednej z kategorii inwestycji alternatywnych. Ocenie poddano wpływ inwestorów chińskich na kondycję rynku sztuki. Zbadano zmienność stopy zwrotu dla wybranych krajowych rynków sztuki. Obliczono podstawowe miary statystyczne dla analizowanych inwestycji alternatywnych. Wskazano na potencjalne możliwości obniżenia ryzyka portfela inwestycyjnego poprzez odpowiednią...
-
Mercury in the Polish part of the Baltic Sea: A response to decreased atmospheric deposition and changing environment
PublicationOur review of the literature showed that since the beginning of the socio-economic transformation in Poland in the 1990s, the downward trend in Hg emissions and its deposition in the southern Baltic Sea was followed by a simultaneous decrease in Hg levels in water and marine plants and animals. Hg concentrations in the biota lowered to values that pose no or low risk to wildlife and seafood consumers. However, in the first decade...
-
Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
-
Mathematical Models in Design Process of Ship Bow Thrusters
PublicationThe paper describes an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an expert...
-
Mathematical Models in Design Process of Ship Bow Thrusters
PublicationThe presentation is about an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an...
-
When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
-
Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
-
Rheology of liquid crystalline polymers
PublicationLiquid crystallinity was invented in the 19th century. It was sometimes called the fourth state of matter because of the ability of macromolecules to generate liquid crystal phases. The main classification divided liquid crystalline polymers (LCPs) into lyotropic and thermotropic types. Interpretation of the rheological behavior of LCP is more complicated than for other polymers. Ordinary polymers are characterized by a normal...
-
LSTM-based method for LOS/NLOS identification in an indoor environment
PublicationDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
-
Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications
PublicationIn this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...
-
Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
-
An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
-
Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
-
Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
-
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...
-
Tools for road infrastructure safety management – Polish experiences
PublicationThe objective of road safety infrastructure management is to ensure that when roads are planned, designed, built and used road risks can be systematically identified, assessed, removed and mitigated. There are a number of approaches to road safety management. European Union Directive 2008/96/EC requires EU member states to use four basic tools of road safety infrastructure management. An overview of the methods in these countries...
-
Bringing Bathymetry LiDAR to Coastal Zone Assessment: A Case Study in the Southern Baltic
PublicationOne of the major tasks in environmental protection is monitoring the coast for negative impacts due to climate change and anthropopressure. Remote sensing techniques are often used in studies of impact assessment. Topographic and bathymetric procedures are treated as separate measurement methods, while methods that combine coastal zone analysis with underwater impacts are rarely used in geotechnical analyses. This study presents...
-
Improving Effectiveness of SVM Classifier for Large Scale Data
PublicationThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
-
Use of Sensory Analysis Methods to Evaluate the Odor of Food and Outside Air
PublicationSensory analysis is applied in many areas of daily life. It is used to carry out the sensory evaluation of foodstuffs or other products and to evaluate the properties of odors present in the environment. The authors attempt to summarize the knowledge on the classification and application of sensory analysis methods to evaluate the odor nuisance of air, which allows the identification of sensory impressions and determination of...
-
Music Genre Recognition in the Rough Set-Based Environment
PublicationThe aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...
-
Multi-Stage Video Analysis Framework
PublicationThe chapter is organized as follows. Section 2 presents the general structure of the proposed framework and a method of data exchange between system elements. Section 3 is describing the low-level analysis modules for detection and tracking of moving objects. In Section 4 we present the object classification module. Sections 5 and 6 describe specialized modules for detection and recognition of faces and license plates, respectively....
-
Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublicationIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
-
Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
-
ECG-based prediction of ventricular fibrillation by means of the PCA
PublicationA Sudden Cardiac Death (SCD) is a death resulting from cardiac failure with no significant symptoms earlier than one hour before occurrence. It is the cause of for approximately 400000 deaths per year in United States and millions of deaths worldwide. The proposed system, including two-stage algorithm and wearable diagnostic device allows for SCD risk estimation and continuous monitoring of high risk patients. A single channel...
-
Efficiency comparison of selected endoscopic video analysis algorithms
PublicationIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
-
The structure of the control system for a dynamically positioned ship
PublicationThe article discusses functions and tasks of dynamic positioning (DP) systems for ships. The analysed issues include ship steering, in particular stabilisation of ship position and direction of motion (real course) at low manoeuvring speeds, and commonly used DP ship models. Requirements imposed by classification societies on DP ships are quoted. A multi-layer structure of the DP control system is presented, with special attention...
-
Method of Decision-Making Logic Discovery in the Business Process Textual Data
PublicationGrowing amount of complexity and enterprise data creates a need for novel business process (BP) analysis methods to assess the process optimization opportunities. This paper proposes a method of BP analysis while extracting the knowledge about Decision-Making Logic (DML) in a form of taxonomy. In this taxonomy, researchers consider the routine, semi-cognitive and cognitive DML levels as functions of BP conceptual aspects of Resources,...
-
Związki biologicznie aktywne w żywności i napojach
PublicationJuż od dłuższego czasu daje się zauważyć wzrost zainteresownia związkami biologicznie aktywnymi w żywności (szczególnie pochodzenia roślinnego) oraz napojach i sokach. W wielu ośrodkach naukowych trwają badania ukierunkowane na określenie aktywności przeciwutleniającej badanych próbek oraz oznaczenie zawartości polifenoli i innych związków o właściwościach przeciwutleniających (m.in. witaminy C oraz tokoferoli). W pracy przedstawiono...
-
Generowanie modeli symulacyjnych na potrzeby systemu ekspertowego wspomagającego projektowanie układów automatyki statku
PublicationOmówiono automatyczne generowanie modeli symulacyjnych na potrzeby systemu ekspertowego wspomagającego projektowanie układów automatyki statków. Na podstawie przyjętych założeń projektowych system ekspertowy zleca badania wybranych struktur podsystemów elektroenergetycznych statków. Aplikacja symulacyjna pobiera z biblioteki modele matematyczne elementów składowych struktur, a następnie zestawia modele symulacyjne, wykonuje badania...
-
Quasi-controlled Experimentations on the Impact of AOP on Software Comprehensibility
PublicationAspect-oriented programming (AOP) emerged as a paradigm to modularize the concerns that lead to interwoven code if implemented using traditional programming techniques. Unfortunately, the new constructs introduced by aspect-oriented (AO) languages result in both: (1) obstacles in modular reasoning, and (2) high coupling between aspects and the augmented modules. There have been numerous attempts to tackle these issues, but none...
-
Non-Nutritive Bioactive Compounds in Food of Plant Origin
PublicationThe increasing knowledge on the health benefits of certain food ingredients, in particular, those of plant origin, opened the discussion of the possibility of using edible plants or their active components in the prevention of non-communicable diseases. The health-promoting properties of plant foods are related to the presence of non-nutritive compounds, mainly plant secondary metabolites, which can affect many biological mechanisms...
-
Classifying Emotions in Film Music - A Deep Learning Approach
PublicationThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
-
Comparison of Lithuanian and Polish Consonant Phonemes Based on Acoustic Analysis – Preliminary Results
PublicationThe goal of this research is to find a set of acoustic parameters that are related to differences between Polish and Lithuanian language consonants. In order to identify these differences, an acoustic analysis is performed, and the phoneme sounds are described as the vectors of acoustic parameters. Parameters known from the speech domain as well as those from the music information retrieval area are employed. These parameters are...
-
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...
-
Improving automatic surveillance by sound analysis
PublicationAn automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...
-
Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
-
An influence of the ship's block coefficient implementation on the evaluation of it's hull girder bending
PublicationAn influence of the three different ways of implementation ship's block coefficient δ (three geometrical models) on the stresses due to wave bending moment have been investigated. Two models have been applied and compared: beam one (description of the shape usingparameters) and FEM shell model (direct representation of the shape). The outcomes have been compared to Polish Register of Shipping (PRS) rules. The results show that...
-
Content-Based Approach to Automatic Recommendation of Music
PublicationThis paper presents a content-based approach to music recommendation. For this purpose, a database which contains more than 50000 music excerpts acquired from public repositories was built. Datasets contain tracks of distinct performers within several music genres. All music pieces were converted to mp3 format and then parameterized based on MPEG-7, mel-cepstral and time-related dedicated parameters. All feature vectors are stored...
-
Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
-
Quantitative risk assessment of new ship designs in damage conditions
PublicationThe paper is devoted to safety of ships in damage conditions. The novel contribution of the paper is connected with a new Multi-Task ship (MT-ship) design at the preliminary stage of design. There are a few problems at the preliminary stage that should be considered. One problem is connected with if the quantitative risk-based method is a reliable and formal method for safety assessment of such the new design (MT-ship) in damage...
-
TOTAL SHIP OPERABILITY – REVIEW, CONCEPT AND CRITERIA
PublicationThe ship operability can be understood and analysed in different manners, and its quality is described using different indexes by different authors. Practically, there is no general and widely accepted description of total ship operability in the literature, nor in the rules of classification societies, which would include both seakeeping and manoeuvrability characteristics of a ship, and simultaneously take into account all ship...
-
System for monitoring road slippery based on CCTV cameras and convolutional neural networks
PublicationThe slipperiness of the surface is essential for road safety. The growing number of CCTV cameras opens the possibility of using them to automatically detect the slippery surface and inform road users about it. This paper presents a system of developed intelligent road signs, including a detector based on convolutional neural networks (CNNs) and the transferlearning method employed to the processing of images acquired with video...
-
Sample preparation and recent trends in volatolomics for diagnosing gastrointestinal diseases
PublicationThe analysis of the human volatilome can be successfully used for rapid and non-invasive diagnostics of gastrointestinal diseases. However, the introduction of techniques based on detection of volatiles is limited, among other factors, by difficulties which arise during the sampling stage and instrumental analysis. The aim of this article was to review and discuss medical and analytical literature on the analysis of volatiles in...
-
POTENCJALNE MOŻLIWOŚCI APLIKACJ TECHNIKI E-NOS W DIAGNOSTYCE MEDYCZNEJ=APPLICATION POTENTIALITIES OF E-NOSE TECHNIQUE IN MEDICAL DIAGNOSTICS
PublicationW pracy przedstawiono i omówiono zasadę działania instrumentu analitycznego - elektronicznego nosa (e-nos) zdolnego rozróżnić i sklasyfikować intensywność zapachu. Urządzenia te służą do automatycznej analizy i rozróżniania próbek zapachowych o złożonym składzie, do rozpoznawania ich charakterystycznych właściwości i najczęściej przeznaczone są do szybkiej analizy jakościowej. Dzięki unikatowym właściwościom technika ta znalazła...
-
The complexity of minimum-length path decompositions
PublicationWe consider a bi-criteria generalization of the pathwidth problem, where, for given integers k, l and a graph G, we ask whether there exists a path decomposition P of G such that the width of P is at most k and the number of bags in P, i.e., the length of P, is at most l. We provide a complete complexity classification of the problem in terms of k and l for general graphs. Contrary to the original pathwidth problem, which is fixed-parameter...