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Wyniki wyszukiwania dla: MACHINE LEARNING (ML)
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Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
PublikacjaCurrent computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning,...
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Analysis and evaluation of grouping methods for effective cutting tool operation
PublikacjaThis article presents the possibilities for using cluster analysis in the assignment of machine tools in automated manufacturing systems. Based on the similarity of manufacturing processes in the system, cutting tools have been grouped. The objective was to obtain groups of similar objects, which could potentially ensure the reduction of the frequency and time of setups, optimizing the maintenance of tool resources and improving...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublikacjaTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams
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E-learning przez Internet w szkolnictwie wyższym. Doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej.
PublikacjaOpisano cztery podstawowe rodzaje e-learningu, przedstawiono strukturę funkcjonalną systemów zarządzania nauczaniem na odległość i zarządzania treścią nauczania (ang. LMS, LCMS) oraz zaprezentowano doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej w nauczaniu na odległość.
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment 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)...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublikacjaThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Prevention of resonance oscillations in gear mechanisms using non-circular gears
PublikacjaOne of the main disadvantages of gear mechanisms is the occurrence of noise and vibrations. This study investigated the applicability of non-circular gears for preventing resonance oscillations in gear mechanisms. The influence of a small deviation of the gear centrodes from the nominal circles on kinematic and oscillatory characteristics was analysed. It was shown that a larger deviation results in a smaller resonance amplitude...
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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...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublikacjaResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Wykorzystanie metody FMEA w kształtowaniu umiejętności projektowania technologii części maszyn = application of the FMEA method for skills development of machine parts technology desing
PublikacjaPrzedstawiono sposób wykorzystania metody FMEA w kształtowaniu umiejętności projektowania technologii części maszyn. Podano wytyczne ogólne i etapy analizy procesu i konstrukcji. Zamieszczono przykład analizy technologii dwustronnej dźwigni spawanej w produkcji małoseryjnej.
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Socioeconomic and gender inequalities in home learning during the COVID-19 pandemic: examining the roles of the home environment, parent supervision, and educational provisions
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Comparative Analysis of Text Representation Methods Using Classification
PublikacjaIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Book Review
PublikacjaActing over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...
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E-Learning as a Factor Optimizing the Amount of Work Time Devoted to Preparing an Exam for Medical Program Students during the COVID-19 Epidemic Situation
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THE EFFECT OF ALTERNATIVE CUTTER PATHS ON FLATNESS DEVIATIONS IN THE FACE MILLING OF ALUMINUM PLATE PARTS
PublikacjaIn this paper the relationships between the alternative machining paths and flatness deviations of the aluminum plate part, were presented. The flatness tolerance of the main surface of the plate part has crucial meaning due to the assembly requirement of piezoelectric elements on the radiator. The aluminum bodies under investigation are the base part of the radiators with crimped feathers for the train industry. The surface of...
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The Neural Knowledge DNA Based Smart Internet of Things
PublikacjaABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Koncepcja poprawy jakości docierania elementów cienkościennych na docierarce jednotarczowej = Conception of quality improvement of thin-walled elements lapping done on single-disk lapping machine
PublikacjaPrzedstawiono problem zapewnienia prawidłowych warunków współpracy przedmiotu obrabianego i narzędzia tarczowego w czasie docierania płaskich elementów cienkościennych. Omówiono sposób dociążania elementów podczas obróbki oraz wytrzymałościowy model układu.
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublikacjaABSTRACT 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...
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublikacjaPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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Wpływ falistości pierścienia ślizgowego na rozpływ prądu w zestyku ślizgowym maszyny synchronicznej = Influence of slip-ring waviness on current distribution in the sliding contact of a synchronous machine
PublikacjaZestyk ślizgowy maszyny synchronicznej średniej i dużej mocy zawiera na ogół szereg równolegle pracujących szczotek na każdym z pierścieni. Szczotki znajdują się w oprawkach szczotkowych rozmieszczonych przestrzennie wzdłuż obwodu pierścienia. To sprawia, że pracują one w tej samej chwili czasowej na różnych fragmentach pierścienia ślizgowego. Nierównomierny rozpływ prądu może spowodować nadmierne obciążenie niektórych szczotek....
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Experience-Oriented Knowledge Management for Internet of Things
PublikacjaIn this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional...
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Using Moodle as a Solution to Interdisciplinary E-collaboration Issues
PublikacjaRapid technological development in recent years has contributed to numerous changes in many areas of life, including education and communication. Establishing interdisciplinary collaboration brings many benefits, however, it is often associated with numerous problems and inconveniences, as well as the need of constant improvement, lifelong learning, professional development (CPD) and finding an effective way of information transferring....
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublikacjaMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublikacjaSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends
PublikacjaIllegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....
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Are Pair Trading Strategies Profitable During COVID-19 Period?
PublikacjaPair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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Webquest- dobra praktyka w e-Learningu
PublikacjaW dobie informatyzacji i pokonywania barier wdrażania e-technologii na uczelniach wyższych uważa się, że jedną z najczęściej stosowanych aktywizujących technik nauczania wśród nauczycieli akademickich jest metoda projektu (ang. project-based learning). W niniejszym opracowaniu proponuje się zastosowanie w procesie edukacji na wyższej uczelni, metody webquest. Jest ona dużo rzadziej stosowana w praktyce. Opracowano ją w oparciu...
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Selectivity of amperometric gas sensors in multicomponent gas mixtures
PublikacjaIn recent years smog and poor air quality became a growing environmental problem. There is a need to continuously monitor the quality of air. The lack of selectivity is one of the most important problems limiting the use of gas sensors for this purpose. In this study, a selectivity of the six amperometric gas sensors is being investigated. Calibration of sensors has been performed in order to find a correlation between concentration...
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Introduction to the ONDM 2022 special issue
PublikacjaThis JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...
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Granulometric analysis of dry sawdust from the sawing process on the frame sawing machine PRW15M = Granulometrická analýza suchej piliny z procesu pílenia borovicového dreva na rámovej píle PRW-15M
PublikacjaW artykule przedstawiono wyniki analizy granulometrycznej trocin otrzymanych podczas procesu przecinania drewna sosnowego na pilarce ramowej PRW15M. Wielkość otrzymanych trocin miesciła się w zakresie od 84,7 µm do 15,2 mm. Z punktu widzenia kształtu trociny średniej wielkości d>125µm są swym kształtem zbliżone do włókien drzewnych. Z kolei, drobne frakcje d<125µm mają kształt sześcienny. Ponadto, wzrost prędkości posuwu powoduje...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis 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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TRWAŁOŚĆ PROJEKTU ERASMUS+ SP4CE - STUDIUM PRZYPADKU
PublikacjaProjekt ERASMUS+ Partnerstwo Strategiczne na Rzecz Kreatywności i Przedsiębiorczości (ang. Strategic Partnership for Creativity and Entrepreneurship - SP4CE) dotyczył wdrażania i upowszechniania innowacyjnych rozwiązań wzmacniających współpracę europejską w dziedzinie kształcenia i szkolenia zawodowego. Działania projektowe były związane z promowaniem innowacyjnych praktyk w edukacji oraz szkoleniach poprzez wspieranie spersonalizowanych...
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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublikacjaIn this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublikacjaKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Categorization of Cloud Workload Types with Clustering
PublikacjaThe paper presents a new classification schema of IaaS cloud workloads types, based on the functional characteristics. We show the results of an experiment of automatic categorization performed with different benchmarks that represent particular workload types. Monitoring of resource utilization allowed us to construct workload models that can be processed with machine learning algorithms. The direct connection between the functional...
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublikacjaMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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Optimal spindle speed determination for vibration reduction during ball-end milling of flexible details
PublikacjaIn the paper a method of optimal spindle speed determination for vibration reduction during ball-end milling of flexible details is proposed. In order to reduce vibration level, an original procedure of the spindle speed optimisation, based on the Liao–Young criterion, is suggested. As the result, an optimal, constant spindle speed value is determined. For this purpose, on-stationary computational model of machining process is...
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AffecTube — Chrome extension for YouTube video affective annotations
PublikacjaThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublikacjaBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Asking Data in a Controlled Way with Ask Data Anything NQL
PublikacjaWhile to collect data, it is necessary to store it, to understand its structure it is necessary to do data-mining. Business Intelligence (BI) enables us to make intelligent, data-driven decisions by the mean of a set of tools that allows the creation of a potentially unlimited number of machine-generated, data-driven reports, which are calculated by a machine as a response to queries specified by humans. Natural Query Languages...
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Improving all-reduce collective operations for imbalanced process arrival patterns
PublikacjaTwo new algorithms for the all-reduce operation optimized for imbalanced process arrival patterns (PAPs) are presented: (1) sorted linear tree, (2) pre-reduced ring as well as a new way of online PAP detection, including process arrival time estimations, and their distribution between cooperating processes was introduced. The idea, pseudo-code, implementation details, benchmark for performance evaluation and a real case example...
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Augmenting digital documents with negotiation capability
PublikacjaActive digital documents are not only capable of performing various operations using their internal functionality and external services, accessible in the environment in which they operate, but can also migrate on their own over a network of mobile devices that provide dynamically changing execution contexts. They may imply conflicts between preferences of the active document and the device the former wishes to execute on. In the...
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Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublikacjaWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
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Simultaneous Determination of Indolic Compounds in Plant Extracts by Solid-Phase Extraction and High-Performance Liquid Chromatography with UV and Fluorescence Detection
PublikacjaA high-performance liquid chromatographic method with UV and fluorescence detection (HPLC-DAD-FLD) was developed for simultaneous determination of indolic compounds in plant material. Indole-3-carbinol (I3C), indole-3-acetic acid (I3AA), indole-3-acetonitrile (I3ACN), and 3,3′-diindolylmethane (DIM) were used as representative compounds that cover a wide spectrum of indole structures occurring in nature. For concentration and purification...
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From Knowledge based Vision Systems to Cognitive Vision Systems: A Review
PublikacjaComputer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...