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Search results for: EDGE INTELLIGENCE ACCELERATORS
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Fracture Toughness and Shear Yield Strength Determination for Two Selected Species of Central European Provenance
PublicationWhen offcut of wood is formed by shearing, Atkins’s analyses of sawing processes can be applied. Using this modern approach, it is possible to determine the fracture toughness and shear yield strength of wood. This model is only applicable for the axial-perpendicular cutting direction because both of these parameters are suitable for the given direction of cutting edge movement and cannot be considered material constants. Alternatively,...
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The convex domination subdivision number of a graph
PublicationLet G = (V;E) be a simple graph. A set D\subset V is a dominating set of G if every vertex in V - D has at least one neighbor in D. The distance d_G(u, v) between two vertices u and v is the length of a shortest (u, v)-path in G. An (u, v)-path of length d_G(u; v) is called an (u, v)-geodesic. A set X\subset V is convex in G if vertices from all (a, b)-geodesics belong to X for any two vertices a, b \in X. A set X is a convex dominating...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublicationElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Adjusting the Stiffness of Supports during Milling of a Large-Size Workpiece Using the Salp Swarm Algorithm
PublicationThis paper concerns the problem of vibration reduction during milling. For this purpose, it is proposed that the standard supports of the workpiece be replaced with adjustable stiffness supports. This affects the modal parameters of the whole system, i.e., object and its supports, which is essential from the point of view of the relative tool–workpiece vibrations. To reduce the vibration level during milling, it is necessary to...
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Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology
PublicationLignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization...
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Ontology-Aided Software Engineering
PublicationThis thesis is located between the fields of research on Artificial Intelligence (AI), Knowledge Representation and Reasoning (KRR), Computer-Aided Software Engineering (CASE) and Model Driven Engineering (MDE). The modern offspring of KRR - Description Logic (DL) [Baad03] is considered here as a formalization of the software engineering Methods & Tools. The bridge between the world of formal specification (governed by the mathematics)...
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Asking Data in a Controlled Way with Ask Data Anything NQL
PublicationWhile 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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Analyzing and Visualizing Government-Citizen Interactions on Twitter to Support Public Policy-making
PublicationTwitter is widely adopted by governments to communicate with citizens. It has become a major source of data for analyzing how governments communicate with citizens and how citizens respond to such communication, uncovering important insights about government-citizen interactions that could be used to support public policy-making. This article presents research that aims at developing a software tool called Twitter Analytics for...
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Digital Innovations and Smart Solutions for Society And Economy: Pros and Cons
PublicationRecent developments in artificial intelligence (AI) may involve significant potential threats to personal data privacy, national security, and social and economic stability. AI-based solutions are often promoted as “intelligent” or “smart” because they are autonomous in optimizing various processes. Be-cause they can modify their behavior without human supervision by analyzing data from the environ-ment, AI-based systems may be...
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Timed rolling and rising tests in Duchenne muscular dystrophy ambulant boys: a feasibility study
PublicationBACKGROUND: Functional activities are extensively used in motor assessments of patients with Duchenne muscular dystrophy. The role of timed items has been reported as an early prognostic factor for disease progression. However, there are two functional activities that are not widely assessed in clinical practice among Duchenne muscular dystrophy patients: rolling and bed rising. This study aimed to investigate whether the 360-degree...
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Multifunctional Bandpass Filter/Displacement Sensor Component
PublicationThis paper presents the design and realization of a multifunctional bandpassfilter/displacement-sensor using an edge-coupled microstrip bandpass filter loaded by a pair of split ring resonators (SRRs). It is shown that while the structure acts as a bandpass filter at its operating frequency, the phase of the reflection coefficient from a movable loading resonator at the resonance frequency of the resonator can be used for displacement...
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Constant-Factor Approximation Algorithm for Binary Search in Trees with Monotonic Query Times
PublicationWe consider a generalization of binary search in linear orders to the domain of weighted trees. The goal is to design an adaptive search strategy whose aim is to locate an unknown target vertex of a given tree. Each query to a vertex v incurs a non-negative cost ω(v) (that can be interpreted as the duration of the query) and returns a feedback that either v is the target or the edge incident to v is given that is on the path towards...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublicationSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Contour Analysis of Bleeding Regions in Endoscopic Images
PublicationThis paper investigates the problem of detecting bleeding regions in images acquired from endoscopic examinations of gastrointestinal tract. The purpose is to identify the characteristic features of bleeding areas' contours in order to develop an accurate method for discriminating between true bleeding regions and missed detections, which could lead to a significant reduction of the false alarm rate of existing blood-detection...
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Low-Dimensional Magnetic Semimetal Cr0.65Al1.35Se3
PublicationWhile exploring novel magnetic semiconductors, the new phase Cr0.65Al1.35Se3 was discovered and characterized by both structural and physical properties. Cr0.65Al1.35Se3 was found to crystallize into orthorhombic CrGeTe3-type structure with space group Pnma (no. 62). Vacancies and mixed occupancies were tested, and the results show that one of the 4c sites accommodates a mixture of Cr and Al atoms, while the other 4c site is fully...
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Proposal of New Tracer Concentration Model in Lung PCT Study Comparison with Commonly Used Gamma-variate Model
PublicationPerfusion computed tomography (pCT) is one of the methods that enable non-invasive imaging of the hemodynamics of organs and tissues. On the basis of pCT measurements, perfusion parameters such as blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface (PS) are calculated and then used for quantitative evaluation of the tissue condition. To calculate perfusion parameters it is necessary to approximate...
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Changes of microbiological quality of water in distribution system. Zmiany mikrobiologicznej jakości wody w sieci dystrybucyjnej.
PublicationW artykule przedstawiono mikrobiologiczną jakość wody podziemnej uzdatnianej w dwóch stacjach oczyszczania wody (WTP I i WTP II), w sieci dystrybucyjnej. Obie stacje uzdatniania stosują dezynfekcję za pomocą dwutlenku chloru. Badania wykazały wzrost ogólnej liczby bakterii w miarę zwiększania się odległości od stacji uzdatniania.In the paper microbiological quality of water in distribution system produced in two ground water treatment...
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Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover
PublicationThe process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus)...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublicationThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublicationThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Infographics in Educational Settings: A Literature Review
PublicationInfographics are visual representations of data that utilize various graphic elements, including pie charts, bar graphs, line graphs, and histograms. Educators and designers can maximize the potential of infographics as powerful educational tools by carefully addressing challenges and capitalizing on emerging technologies. However, current education systems showcase the need for development guidelines and the best practices targeted...
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A novel (Ti/Ce)UiO-X MOFs@TiO2 heterojunction for enhanced photocatalytic performance: Boosting via Ce4+/Ce3+ and Ti4+/Ti3+ redox mediators
PublicationTitanium-substituted cerium-oxo-based UiO MOFs with terephthalate linkers modified by various groups (–Br, –NH2, –NO2) or their derivatives (N-heterocyclic or biphenyl groups) were combined with titanium dioxide in a multistep route to obtain a core-shell-like architecture. DFT simulations showed that Ce- and bimetallic Ti/Ce- MOFs exhibited different charge compensation. Extended characterization revealed the formation of heterojunctions between...
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Concentration‐Induced Hetero‐Valent Partial‐Inverse Occupation of Infrared Phosphor
PublicationInfrared luminescent materials have evoked much attention from chemists and material scientists. Although substantial progress is made in materials design, the luminescent mechanism remains ambiguous in the complex structures, presenting major barriers to developing novel infrared luminescent materials. Herein, this study aims to deliberate a complete discussion on infrared phosphors with concentration-induced hetero-valent partial-inverse...
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angielski
PublicationA subset D of V (G) is a dominating set of a graph G if every vertex of V (G) − D has at least one neighbour in D; let the domination number γ(G) be the minimum cardinality among all dominating sets in G. We say that a graph G is γ-q-critical if subdividing any q edges results in a graph with domination number greater than γ(G) and there exists a set of q − 1 edges such that subdividing these edges results in a graph with domination...
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Elucidating photoluminescent properties of Eu‐doped Ca–Al–Si–O(–N) glasses and the local structures of Eu ions
PublicationEuropium (Eu) ion–doped luminescent materials have attracted considerable attention for their numerous optical applications. Eu-doped Ca–Al–Si–O(–N) glasses were synthesized from a mixture of oxynitride glasses and Eu2O3 powder using a standard melt-quenching technique in a radiofrequency furnace. The source Eu trivalent ions primarily changed to Eu2+ during melting, and the ratio of Eu2+ ions increased with an increase in Eu content...
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Enhancement of lift and drag performances of a NACA0012 airfoil by multi-DBD plasma actuator with additional floating interelectrodes
PublicationIt is clear that the improvement of aircraft aerodynamic performances is currently and will continue to be a significant area of research for the aeronautical industry. The current study is focused on theenhancement of aerodynamic airfoil performances by using a multi-DBD plasma actuator mounted around the model leading-edge. Experiments have been conducted at the University of Orleans, in the 2 m x 2 m test section of a large...
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Experimental ORC micro-power plant for CHP application Part B: Radial and Multi-stage axial turbines
PublicationThe co-generative micro-power plant with the HFE7100 applied as a working medium was designed and built for experimental investigations. Special attention is paid to a micro-turbine which was built and tested in two variants: a radial turbine and an axial turbine. A concept of a radial turbine with 2 centripetal and 2 centrifugal stages is shown. This prototype was equipped with an aerostatic gas bearing and, alternatively, with...
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Scheduling with Complete Multipartite Incompatibility Graph on Parallel Machines
PublicationIn this paper we consider a problem of job scheduling on parallel machines with a presence of incompatibilities between jobs. The incompatibility relation can be modeled as a complete multipartite graph in which each edge denotes a pair of jobs that cannot be scheduled on the same machine. Our research stems from the works of Bodlaender, Jansen, and Woeginger (1994) and Bodlaender and Jansen (1993). In particular, we pursue the...
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Independent Domination Subdivision in Graphs
PublicationA set $S$ of vertices in a graph $G$ is a dominating set if every vertex not in $S$ is adjacent to a vertex in~$S$. If, in addition, $S$ is an independent set, then $S$ is an independent dominating set. The independent domination number $i(G)$ of $G$ is the minimum cardinality of an independent dominating set in $G$. The independent domination subdivision number $\sdi(G)$ is the minimum number of edges that must be subdivided (each...
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Curing epoxy resin with anhydride in the presence of halloysite nanotubes: the contradictory effects of filler concentration
PublicationEpoxy resins can be cured with a wide variety of curing agents such as amines and anhydrides, but anhydride curing would be more favorable for research purpose because of epoxy-anhydride curing taking place slowly at room temperature. Incorporation of natural nanosized minerals into epoxy is of environmental importance. Halloysite nanotubes (HNTs) display chemical properties similar to those of silica and alumina, and hydroxyl...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublicationIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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Software development methodologies and practices in start-ups
PublicationSoftware start-ups are aiming to develop cutting-edge software products under highly uncertain conditions, overcoming fast-growing markets under multiple influences. This study aims to identify and analyse the existing scientific literature regarding software development methodologies and practices in software start-ups published between January 2006 and December 2017 using the systematic mapping study. The results identified 37...
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Enhanced Photoelectrocatalytical Performance of Inorganic-Inorganic Hybrid Consisting BiVO4, V2O5, and Cobalt Hexacyanocobaltate as a Perspective Photoanode for Water Splitting
PublicationThin layers of BiVO4/V2O5 were prepared on FTO substrates using pulsed laser deposition technique. The method of cobalt hexacyanocobaltate (Cohcc) synthesis on the BiVO4/V2O5 photoanodes consists of cobalt deposition followed by electrochemical oxidation of metallic Co in K3[Co(CN)6] aqueous electrolyte. The modified electrodes were tested as photoanodes for water oxidation under simulated sunlight irradiation. Deposited films...
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Collaborative Delivery by Energy-Sharing Low-Power Mobile Robots
PublicationWe study two variants of delivery problems for mobile robots sharing energy. Each mobile robot can store at any given moment at most two units of energy, and whenever two robots are at the same location, they can transfer energy between each other, respecting the maximum capacity. The robots operate in a simple graph and initially each robot has two units of energy. A single edge traversal by an robot reduces its energy by one...
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The study on the appearance of deformation defects in the yacht lamination process using an AI algorithm and expert knowledge
PublicationThis article describes the application of the A-priori algorithm for defining the rule-based relationships between individual defects caused during the lamination process, affecting the deformation defect of the yacht shell. The data from 542 yachts were collected and evaluated. For the proper development of the algorithm, a technological process of the yacht lamination supported by expert decisions was described. The laminating...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublicationFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Application of unmanned USV surface and AUV underwater maritime platforms for the monitoring of offshore structures at sea
PublicationThe operation of offshore structures at sea requires the implementation of advanced systems for their permanent monitoring. There is a set of novel technologies that could be implemented to deliver a higher level of effective and safe operation of these systems. A possible novel solution may be the application of a new maritime unmanned (USV) surface and underwater vehicles/platforms (AUV). Application of such vehicles/platforms...
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How Machine Learning Contributes to Solve Acoustical Problems
PublicationMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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A Survey on the Datasets and Algorithms for Satellite Data Applications
PublicationThis survey compiles insights and describes datasets and algorithms for applications based on remote sensing. The goal of this review is twofold: datasets review for particular groups of tasks and high-level steps of data flow between satellite instruments and end applications from an implementation and development perspective. The article outlines the generalized data processing pipelines, taking into account the variations in...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...