Search
Filters
total: 463
filtered: 401
Search results for: AUTOMATED PRONUNCIATION ASSESSMENT, SPEECH PROCESSING, SECOND-LANGUAGE LEARNING, DEEP LEARNING
-
Advantageous conditions of saccharification of lignocellulosic biomass for biofuels generation via fermentation processes
PublicationProcessing of lignocellulosic biomass includes four major unit operations: pre-treatment, hydrolysis, fermentation and product purifcation prior to biofuel generation via anaerobic digestion. The microorganisms involved in the fermentation metabolize only simple molecules, i.e., monosugars which can be obtained by carrying out the degradation of complex polymers, the main component of lignocellulosic biomass. The object of this...
-
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...
-
Application of artificial intelligence into/for control of flexible manufacturing cell
PublicationThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
-
Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
-
The Knowledge Transfer From Headquarter to Local Subsidiaries Through Expatriates - Local Employees’ Perspective
PublicationBackground. Knowledge transfer between the HQ and subsidiary has recently been targets of increasing research interest. However, the role of expatriate managers and local staff perspective on this process has not been examined enough. Research aims. This paper has two main objectives: first to develop a conceptual framework (model) of knowledge transfer between the headquarters and local subsidiary, and second to empirically evaluate...
-
High frequency oscillations are associated with cognitive processing in human recognition memory
PublicationHigh frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations...
-
Paid work activity and entrepreneurial cognitions of students – evidence from European emerging economies
PublicationPurpose – This paper aims to investigate whether paid work activity (PWA) experience of students from five emerging economies is related to academic results and self-assessment of possessed entrepreneurial traits. Additionally, the authors verify the relationship between obtaining work experience and the willingness to start own business among students. Design/methodology/approach – Participants included 3,631 students of the first...
-
An automated, low-latency environment for studying the neural basis of behavior in freely moving rats
PublicationBackground Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes). Results To overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding...
-
Buzz-based honeybee colony fingerprint
PublicationNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
-
Adaptacyjny system sterowania ruchem drogowym
PublicationAdaptacyjny system sterowania ruchem drogowym to rodzaj systemu sterowania, który dynamicznie, w czasie rzeczywistym, dostosowuje swoje parametry w oparciu o bieżące warunki ruchu drogowego. Celem niniejszej rozprawy jest sprawdzenie wpływu wybranych cech systemu, zbudowanego w oparciu o zaprojektowane i zbudowane z udziałem autora inteligentne znaki drogowe, na wybrane parametry mające wpływ na bezpieczeństwo i płynność ruchu....
-
Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
-
Application of autoencoder to traffic noise analysis
PublicationThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
-
Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
-
Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublicationIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
-
Impact of AlphaFold on structure prediction of protein complexes: The CASP15‐CAPRI experiment
PublicationWe present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody–antigen complexes, and 7 large assemblies. On average 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups...
-
ARIMA vs LSTM on NASDAQ stock exchange data
PublicationThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
-
Deep eutectic solvents microbial toxicity: Current state of art and critical evaluation of testing methods
PublicationDeep eutectic solvents (DESs) were described at the beginning of 21st century and they consist of a mixture of two or more solid components, which gives rise to a lower melting point compared to the starting materials. Over the years, DESs have proved to be a promising alternative to traditional organic solvents and ionic liquids (ILs) due to their low volatility, low inflammability, easy preparation, and usually low cost of compounds...
-
Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
-
Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
-
Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
-
Do clusters help companies to "go green"? Experience of Polish National Key Clusters
PublicationThis study aims to explore cluster activity in the field of green transformation, taking into account the green, low-carbon and circular economy. Our intention was to identify the main green practices used by cluster organizations, which we showed through the lens of the attributes of both the cluster and the cluster organization. Through our study, we sought to answer the question: what is the role of cluster organizations in...
-
A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublicationPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
-
Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublicationThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
-
Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
-
Moduł Warsztaty - narzędzie w procesie edukacji na uczelni wyższej
PublicationObecnie istnieje bardzo szeroka gama narzędzi informatycznych, które wspierają proces edukacji przy wykorzystaniu internetu na uczelniach wyższych. Wśród nieodpłatnych narzędzi powszechnie znana jest platforma Moodle. W artykule zaprezentowano jeden z jej modułów – Warsztaty. Przedstawiono jego funkcjonalność. Opisano jego zalety i wady w nauczaniu łączącym techniki online i tradycyjne na uczelni wyższej (blended-learning). W artykule...
-
Experimental and numerical identification of corrosion degradation of ageing structural components
PublicationThe study presents experimental and numerical identification of corrosion degradation of thin-walled structural components employing guided wave propagation. The steel structural components are subjected to through-thickness varying corrosion degradation levels. The developed approach using the non-destructive guided wave-propagation quantifies the equivalent average corrosion degradation level by exploring a limited number of...
-
Cooperation areas between universities and industry - case studies in the area of civil engineering
PublicationThe paper describes the areas of cooperation between universities and industry in the area of civil engineering. Presented examples are related to didactics, research grants and commissioned works. On the basis of the authors own experiences the mutual benefits of cooperation in different areas are described. As well as the assessment criteria of the areas of cooperation by the scientific community. The first area of cooperation...
-
Vision Zero in Poland
PublicationPoland’s experience of road safety work is relatively short. In the early 1990s road deaths soared to a staggering 8000 a year. A diagnosis found that Poland’s lack of systemic road safety action was to blame for those figures. In response, the state set up road safety bodies and commissioned road safety programs. In 2005, Poland followed the example of Sweden and adopted Vision Zero as a far-reaching concept of changes in road...
-
Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease
PublicationIn this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...
-
Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
PublicationHypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. Instead, those systems concentrated on collecting features from many retinopathy-related...
-
Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
-
Wyróżniki modelu biznesu przedsiębiorstwa inteligentnego
PublicationBurzliwa zmiana środowiska biznesowego wpływa na ludzi tak, że generują oczekiwania na wyroby i usługi zaspokajające ich dotychczasowe i nowe potrzeby w coraz większym stopniu. W ten sposób przed menedżerami powstają wciąż nowe, bardziej skomplikowane i wysublimowane wymagania. W takich uwarunkowaniach prowadzenia biznesu sukces osiąga to przedsiębiorstwo, które jest inteligentne. W takiej perspektywie celem badań było wyłonienie...
-
Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
-
Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures
PublicationAbstract Background In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments...
-
An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
PublicationAn innovative tool for modeling the specific flood volume was presented that can be applied to assess the need for stormwater network modernization as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland, were used to apply the model and demonstrate its usefulness. This model extends the capability of recently developed statistical and machine learning hydrodynamic models developed...
-
Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
-
Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
-
Soft skills among academics: Five theoretically informed lessons for current times
PublicationRESEARCH OBJECTIVE: The aim of this article is to provide a comprehensive examination of the role of soft skills among academics in the context of the evolving higher-education landscape. THE RESEARCH PROBLEM AND METHODS: We use a scoping review of existing literature to discuss the importance of soft skills in academia. Through critical analysis and synthesis, we identify patterns and gaps in current knowledge and develop five...
-
Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility
PublicationSolubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived...
-
Is data management a new “digitisation”? A change of the role of librarians in the context of changing academic libraries’ tasks
PublicationAcademic libraries’ tasks have been evolving over the years. The changes have been stimulated by appearing of electronic resources, automated library systems, digital libraries and Open Access (OA) repositories. Librarians’ tasks and responsibilities in the academic environment have been evolving in accordance with new tasks they were expected to assume. A few years ago there was a discussion during which an attempt was made to...
-
Intelligent Knowledge-Base Model for IT Support Organization Evolution
PublicationThe goal of the paper is building the knowledge-based model for predicting the state of the IT support organization. These organizations, critical for development of various business sectors, are facing the problem of their transformation. It is the result of the fundamental change in the role of the IT organizations in the current economy. The complexity of the processes, the difficulty adjusting the operations and limited ability...
-
Intercultural interactions at multinational corporations' workplace: Grounded theory.
Publicationenvironments is a new challenge for employees and managers. The aim of the paper is to analyze the social interactions in multicultural environments of multinational corporations (MNCs) as well as to propose a model of intercultural social interactions in MNCs’ specifi c context. Design/methodology/approach: The grounded theory approach was applied to create a model of intercultural interactions in MNCs. The data was obtained during...
-
Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublicationDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
-
Simulation analysis of a production process with selected six sigma ratios
PublicationComputer technologies allow more and more to model as well as to perform simulation experiments of various processes. The simulation analysis provides a better understanding of the interdependencies between various stages of production processes.The results of simulation studies were presented, the aim of them was to show the opportunities of the analysis of the process according to the scenarios and variants developed in connection...
-
Chitosan-coated coconut shell composite: A solution for treatment of Cr(III)-contaminated tannery wastewater
PublicationTannery industry generates a large amount of Cr(III)-contaminated wastewater daily. Unless properly treated, not only this effluent contaminates the water body, but also damages the environment and threatens public health. This batch study investigates the feasibility of chitosan-coated coconut shells as a low-cost material for removing Cr(III) from tannery wastewater. Both chitosan and coconut shell (CS) waste are abundantly available...
-
High-Performance Machine-Learning-Based Calibration of Low-Cost Nitrogen Dioxide Sensor Using Environmental Parameter Differentials and Global Data Scaling
PublicationAccurate tracking of harmful gas concentrations is essential to swiftly and effectively execute measures that mitigate the risks linked to air pollution, specifically in reducing its impact on living conditions, the environment, and the economy. One such prevalent pollutant in urban settings is nitrogen dioxide (NO2), generated from the combustion of fossil fuels in car engines, commercial manufacturing, and food processing. Its...
-
Method of selective fading as a educational tool to study the behaviour of prestressed concrete elements under excess loading
PublicationPrestressed structures are a key to realization of the boldest architectural ideas, characteristic feature of prestressed structure is better use of concrete material properties by insertion of internal forces. Learning about pre-stressed reinforced concrete structures is an integral part of Graduate Studies Program in construction engineering. Know-how of geometry change patterns in prestressed concrete elements under certain...
-
Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
-
Topology recognition and leader election in colored networks
PublicationTopology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with...
-
Silent Signals The Covert Network Shaping the Future
PublicationSilent Signals The Covert Network Shaping the Future In a world dominated by information flow and rapid technological advancements, the existence of hidden networks and unseen influences has never been more relevant. "Silent Signals: The Covert Network Shaping the Future" delves deep into the mysterious and often opaque world of covert communication networks. This influential work sheds light on the silent...