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Wyniki wyszukiwania dla: EVALUATION OF E-LEARNING METHODS
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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COVID-19 and digital deprivation in Poland
PublikacjaResearch background: The problem of digital deprivation is already known, but the COVID-19 pandemic has highlighted its negative consequences. A global change in the way of life, work and socialisation resulting from the epidemic has indicated that a basic level of digital integration is becoming necessary. During the lockdown, people were forced to use ICTs to adapt to a rapidly changing reality. Current experience with coronavirus...
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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublikacjaThis work presents a method of forecasting the level of PM10 with the use of artificial neural networks. Current level of particulate matter and meteorological data was taken into account in the construction of the model (checked the correlation of each variable and the future level of PM10), and unidirectional networks were used to implement it due to their ease of learning. Then, the configuration of the network (built on the...
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Obrony prac doktorskich na Wydziale Chemicznym
WydarzeniaDn. 12.10.2022 r. o godz. 13.00 w Audytorium 1.4 Wydziału Chemicznego PG (budynek nr 5) odbędzie się w trybie hybrydowym publiczna obrona pracy doktorskiej mgr inż. Patrycji Jakubek.
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Phong B. Dao D.Sc., Ph.D.
OsobyPhong B. Dao received the Engineer degree in Cybernetics in 2001, the M.Sc. degree in Instrumentation and Control in 2004, both from Hanoi University of Science and Technology in Vietnam, and the Ph.D. degree in Control Engineering in 2011 from the University of Twente, the Netherlands. In May 2020, Dr. Dao received the degree of D.Sc. (Habilitation) in Mechanical Engineering from the AGH University of Science and Technology, Poland....
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Olgun Aydin Dr
OsobyOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Senior Data Scientist in PwC Poland, gives lectures in Gdansk University of Technology in Poland and member of WhyR? Foundation. Olgun is a very big fan of R and author of the book called “R Web Scraping Quick Start Guide” , two video courses are called “Deep Dive into Statistical Modelling using R” and “Applied Machine Learning and Deep...
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Zastosowanie systemów e-learningu w szkolnictwie wyższym
PublikacjaWzrost dostępności internetu oraz rozwój systemów informatycznych przyczyniły się do zmian w zakresie edukacji. Poprzez wykorzystanie narzędzi informatycznych coraz popularniejszą formą nauczania stał się e-learning. Obecnie większość uczelni wyższych stosuje wybrany przez siebie system e-learningowy, którego głównym zadaniem jest wsparcie procesu dydaktycznego. Celem pracy jest analiza zastosowania kilku przykładowych systemów...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublikacjaDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Methods of Assessing Degradation of Supercapacitors by Using Various Measurement Techniques
PublikacjaThis article presents the qualitative analyses of the construction of supercapacitor samples. The analyses are based on the suggested thermographic measurements as well as the technique of testing the inherent noise of the investigated element. The indicated assessment methods have been referred to the currently used parameters for the qualitative evaluation of supercapacitors. The approach described in this paper, which introduces...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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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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Wydajność przetwarzania żądań usług uwarunkowanych czasowo realizowanych w sieci IMS/NGN
PublikacjaW rozprawie dokonano przeglądu stanu implementacji koncepcji IMS/NGN, a także modeli systemów obsługi z oczekiwaniem pod kątem zastosowania dla serwerów i łączy w modelu analitycznym wielodomenowej sieci IMS/NGN. Przedstawiono założenia dla tego modelu oraz metodologię obliczeń i analizy wyników: średnich czasów E(CSD) zestawiania i E(CDD) rozłączenia połączenia dla scenariuszy połączeń zakończonych sukcesem. Opisano założenia,...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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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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Performance Models of a Multidomain IMS/NGN Service Stratum
PublikacjaThis paper quantifies call processing performance (CPP) of a multidomain IMS/NGN architecture, which was proposed to deliver current and future telecommunication services with strict quality requirements, independently of the transport network technologies. A realistic simulation model is used as a reference for evaluation of the analytical results, in which vari-ous types of queuing systems are applied to model the opera-tion...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Analysis and Evaluation of the Working Cycle of the Diesel Engine
PublikacjaThe paper presents a proposal to apply a quantitative evaluation of the diesel engine with regard to the phenomena occurring during of a working cycle. The proposed procedure when analyzing test results from diesel engine is an attempt to transfer an engine activity evaluation methods in the operational time scale (exploit time), eg. in hours, to the micro-scale (dynamic time) relating only to the execution time of one (several)...
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Towards systemic functional safety and security management in hazardous plants
PublikacjaThe aim of this article is to identify and discuss some issues related to functional safety and security management in hazardous industrial plants. The safety functions are to be realised using the electric / electronic / programmable electronic systems (E/E/PESs) or the safety instrumented systems (SISs) that are designed and operated respectively according to IEC 61508 and IEC 61511 requirements in life cycle. Although the role...
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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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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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Metal-Organic Frameworks in Green Analytical Chemistry
PublikacjaTaking into consideration the rapid expansion of MOFs applications in the analytical chemistry area, it is important to evaluate the existing and future analytical MOF-based methods according to GAC principles. From this point of view, eco-friendly MOFs-based methods should include features such as: green design and synthesis of MOF, evaluation of toxicity issues of MOFs, and incorporation of MOFs in GAC methods. This Chapter will...
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An application of blended and collaborative learning in spatial planning course
PublikacjaSpatial Planning is a master course for graduate students of Environmental Engineering. The course is based on assumptions that students’ future work will be connected with spatial planning, and spatial issues will have an influence on their everyday lives. To familiarize students with environmental issues in planning, the teams of students get an assignment to design an urban space, waterfront along a stream. The whole project...
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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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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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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Od zajęć tradycyjnych do MOOCów – role nauczyciela języków obcych
PublikacjaE-learning może stać się skutecznym środowiskiem uczenia się i nauczania przede wszystkim dzięki wytężonej pracy kompetentnego nauczyciela. Różne role, jakie musi on wypełniać, związane są z naturą procesu edukacyjnego prowadzonego online, na który ma wpływ przyjęta koncepcja metodyczna, instruktywistyczna lub konstruktywistyczna, liczba uczestników, struktura kursu, typy zasobów i aktywności oraz tematyka całego programu lub modułu....
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Use of Sensory Analysis Methods to Evaluate the Odor of Food and Outside Air
PublikacjaSensory 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...
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Performance evaulation of video object tracking algorithm in autonomous surveillance system
PublikacjaResults of performance evaluation of a video object tracking algorithm are presented. The method of moving objects detection and tracking is based on background modelling with mixtures of Gaussians and Kalman filters. An emphasis is put on algorithm's efficiency with regards to its settings. Utilized methods of performance evaluation based on comparison of algorithm output to manually prepared reference data are introduced. The...
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Performance evaluation of video object tracking algorithm in autonomous surveillance system
PublikacjaResults of performance evaluation of a video object tracking algorithm are presented. The method of moving objects detection and tracking is based on background modelling with mixtures of Gaussians and Kalman filters. An emphasis is put on algorithm's efficiency with regards to its settings. Utilized methods of performance evaluation based on comparison of algorithm output to manually prepared reference data are introduced. The...
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Romanika Okraszewska dr inż. arch.
Osobydr inż. arch. Romanika Okraszewska jest adiunktem w Katedrze Inżynierii Drogowej i Transportowej Wydziału Inżynierii Lądowej i Środowiska Politechniki Gdańskiej. W 1996 ukończyła klasę matematyczno-informatyczną w VIII Liceum Ogólnokształcącym im. Komisji Edukacji Narodowej w Gdańsku. Absolwentka dwóch wydziałów Politechiki Gdańksiej, w roku 2002 ukończyła studia architektury i urbanistyki a w 2004 zarządzania i ekonomii. W latach...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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MOOCs in SP4CE - case studies (Strategic Partnership for Creativity and Entrepreneurship)
PublikacjaSP4CE stands for Strategic Partnership for Creativity and Entrepreneurship project which has been funded with support from the European Commission under the ERASMUS+ Programme in the period 1st September 2014 - 31st August 2017. The main purpose of SP4CE project is to design innovative e-learning tools for collaboration between students, enterprises and teachers. It concentrates on identifying users’ needs and supports the development...
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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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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublikacjaModern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Machine Learning Techniques in Concrete Mix Design
PublikacjaConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
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Occurrence of antimicrobial resistant bacteria in environment and the statistical analysis of this phenomenon
PublikacjaIntroduction: In this study the occurrence of antimicrobial resistance patterns among fecal indicators (Escherichia coli and Enterococcus spp.) was analyzed in water and wastewater samples. The trends in antimicrobial resistance were analyzed using basic statistical methods. Methods: Samples were obtained from two local watercourses (Oliwski Stream and Reda River) as well as from the wastewater treatment plant (WWTP) Gdansk - Wschod....
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Low-power device simulator for micro-energy measurement methods testing
PublikacjaThe paper presents low-power device simulator designed for testing of micro-energy measurement methods. Such kind methods can be used for evaluation of power systems based on Energy Harvesting. The device allows to set the current consumption characteristic over the time, thus making possible playing the role of different types of low-power devices e.g. simulating sensor network node.
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Przegląd metod oceny struktur przestrzennych w warunkach zrównoważonego rozwoju
Publikacjathe article "the assessment methods' review of urban structures in the sustainable development context" presents various methods along with tools and ways how to apply them. mainly it is based on methods' descriptions contained in bequest programme (building environmental quality evaluation sustainability through time). the assessment should improve formation of the built environment and practical realization of the idea of sustainable...
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Visual and auditory attention stimulator for assisting pedagogical therapy . Stymulator uwagi wzrokowej i słuchowej do wspomagania terapii pedagogicznej
PublikacjaVisual and auditory attention stimulator provides a system developed in order to improve reading skills using simultaneous presentation of text in its visual form and in transformed auditory form accompanied by related movie material. The described research employed 40 children at the age of 8 13 years having difficulties in learning of reading, who were diagnosed as having developmental dyslexia. It was shown that application...
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Visual and Auditory Attention Stimulator for Assisting Pedagogical Therapy
PublikacjaVisual and auditory attention stimulator provides a system developed in order to improve reading skills using simultaneous presentation of text in its visual form and in transformed auditory form accompanied by related movie material. The described research employed 40 children at the age of 8 13 years having difficulties in learning of reading, who were diagnosed as having developmental dyslexia. It was shown that application...
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Performance of ASON/GMPLS architecture in condition of wavelength conversion and without wavelength conversion
PublikacjaThe paper regards the problem of ASON/GMPLS performance in condition of wavelength and without wavelength conversion. The authors present influence analysis in condition of wavelength and non-wavelength conversion on the ASON/GMPLS control plane performance represented by mean Connection Set-up Time E (CST) and request loss probabilities. The offered traffic to the transport layer and request intensity have been changed for evaluation...
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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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Machine Learning and Electronic Noses for Medical Diagnostics
PublikacjaThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublikacjaThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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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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Smart Knowledge Engineering for Cognitive Systems: A Brief Overview
PublikacjaCognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...