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Search results for: machine learning algorithm soil-structure interaction seismic risk assessment residual interstory drift seismic demand seismic failure probability
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Speech Analytics Based on Machine Learning
PublicationIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Data Reduction Algorithm for Machine Learning and Data Mining
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Seismic Response of High-Rise Buildings Equipped with Base Isolation and Non-Traditional Tuned Mass Dampers
PublicationOne of the methods in structural control is the application of combinational control systems in order to reduce the response of structures during earthquakes. The aim of the present paper is to verify the effectiveness of a hybrid control strategy, combining base isolation and non-traditional tuned mass dampers (TMDs) (i.e., TMDs with dashpots directly connected to the ground) in suppressing structural vibrations of high-rise buildings....
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Shaking table experimental study on pounding between adjacent structures founded on different soil types
PublicationThe aim of this study is to extensively investigate the effect of the soil type on the response of colliding structures based on shaking table experimental tests. Two single-storey models of steel buildings with different dynamic parameters were considered in this study. Three pounding scenarios were taken into account by applying different seismic gaps (0.5 cm, 1 cm and 1.5 cm as well as the no pounding case). First, the effect...
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The structure of demand and its economic consequences for urban transport
PublicationThe structure of demand for urban transport services, determined by the share of passengers entitled to free and reduced fares, is an important factor influencing its economic condition. The aim of this article is to present the results of research into the structure of demand for urban transport as well as its economic consequences. The article begins by considering the nature of the determinants and consequences of the public...
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Consequences of neglecting the appropriate safety conditions of structures exposed to seismic excitations - damage examples after the Kaliningrad earthquake
PublicationW artykule przedstawiono przykłady uszkodzeń budowli znajdujących się w złym stanie technicznym, które powstały w wyniku trzęsienia ziemi o epicentrum w Obwodzie Kaliningradzkim. Przykłady te jednoznacznie pokazują, iż zaniedbywanie stanu technicznego konstrukcji narażonych na wstrząsy sejsmiczne może prowadzić do poważnych konsekwencji powodując znaczne straty materialne lub ofiary śmiertelne.
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Machine Learning Techniques in Concrete Mix Design
PublicationConcrete 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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Effect of soil on the capacity of viscous dampers between adjacent buildings
PublicationThis study investigated the seismic pounding of two adjacent buildings considering soil–structure interaction (SSI). A comprehensive parametric study of buildings with different heights was performed to reveal the pounding-involved behaviour considering the soil effect. Wavelet transform has been conducted to gain insight into the differences in the frequency contents of the impact forces between fixed- and flexible-base adjacent...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis 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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Risk of power cables insulation failure due to the thermal effect of solar radiation
PublicationLow-voltage, as well as high-voltage power cable lines, are usually buried in the ground. The ampacity of the power cables in the ground mainly depends on the thermal resistivity of the soil, which may vary in a wide range. A common practice in power cable systems performance is to supply them from a pole of an overhead line. If so, a section of the line is located in free air and can be directly exposed to solar radiation. In...
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An investigation on residual stress and fatigue life assessment of T-shape welded joints
PublicationThis paper aims to quantitatively evaluate the residual stress and fatigue life of T-type welded joints with a multi-pass weld in different direction. The main research objectives of the experimental test were to test the residual stress by changing direction along with multiple wielding passes and determine the fatigue life of the welded joints. The result shows that compressive residual stress increases in the sample gradually...
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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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Usefulness of the voltamperometric method for assessment of the purity of soil
PublicationThis paper presents a voltammetric analysis of soil. It shows that the voltammetry is a useful method for the assessment of soil contaminated with heavy metal ions. There are two major problems with voltammetry analysis: the diffusion coefficient and the measurement system. The paper contains a short literature study of mathematical equations and a study of differences between soil and water measurements. Suggestions of the solution...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Introduction to the special issue on machine learning in acoustics
PublicationWhen we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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FIRE RISK ASSESSMENT IN INDUSTRIAL PREMISES
PublicationChapter presents different aspects of fire risk assessment in industrial sites
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Assessment of unusual failure in crankshaft of heavy-duty truck engine
PublicationThe unusual premature failure of a heavy-duty truck engine crankshaft has been the subject of a rigorous study, and this manuscript describes it in detail. The failure was happened to begin with the growth of the crack from the surface defects, in the form of the clusters of non-metallic inclusions, in the lubrication hole zone of the first main journal, which was the stress concentration zone. A series of experiments including...
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Machine Learning and Electronic Noses for Medical Diagnostics
PublicationThe 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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Designing acoustic scattering elements using machine learning methods
PublicationIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Non-linear behaviour of base-isolated building supported on flexible soil under damaging earthquakes
PublicationSeismic isolation is a strategy to reduce damage of structures exposed to devastating earthquake excitations. Isolation systems, applied at the base of buildings, lower the fundamental frequency of the structure below the range of dominant frequencies of the ground motion as well as allow to dissipate more energy during structural vibrations. The effectiveness of the base-isolated buildings in damage reduction has been confirmed...
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Ship Collision Risk Assessment Based on Collision Detection Algorithm
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APPLICATION OF QUANTITATIVE RISK ASSESSMENT TO SHIPS IN EMERGENCY CONDITIONS
PublicationThe paper is devoted to safety of ships in emergency conditions. The currently valid prescriptive method of safety assessment of ships in damage conditions is included in the SOLAS 2009 Part B-2 Ch.II-1 regulations. It is devoted to the design stage and difficult to apply in operation. A possible alternative described in this paper is a method based on assessment of performance of ships and risk assessment. Type of risk evaluation...
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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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Assessment of student language skills in an e-learning environment
PublicationThis article presents the role of various assessment structures that can be used in a VLE. e-Learning language courses offer tutors a wide range of traditional and computer-generated formative and summative assessment procedures and tools. They help to evaluate each student’s progress, monitor their activities and provide varied support, which comes from the tutor, the course structure and materials as well as other participants....
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublicationThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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FEM simulations applied to the failure analysis of RC structure under the influence of municipal sewage pressure
PublicationThe paper discusses a failure mechanism of reinforced concrete (RC) structure with steel cover that failed under the influence of municipal sewage pressure. To explain the reasons of failure, in-situ measurements, laboratory experiments and comprehensive Finite Element Method (FEM) computations were performed. Non-destructive in-situ scanning tests were carried out to determine quantity and cover thickness of embedded reinforcement...
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Concrete mix design using machine learning
PublicationDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Computer-assisted assessment of learning outcomes in the laboratory of metrology
PublicationIn the paper, didactic experience with broad and rapid continuous assessment of students’ knowledge, skills and competencies in the Laboratory of Metrology, which is an example of utilisation of assessment for learning, is presented. A learning management system was designed for manage, tracking, reporting of learning program and assessing learning outcomes. It has ability to provide with immediate feedback, which is used by the...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublicationThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Thermal and Electrodynamic Risk of Residual Current Devices in the Case of Back-Up Protection by Overcurrent Circuit Breakers
PublicationResidual current operated circuit breakers without integral overcurrent protection should be back-up protected. As back-up protection devices, overcurrent circuit breakers are used. The maximum let-through energy and let-through current of the overcurrent devices were evaluated under laboratory conditions. The thermal and electrodynamic risk of residual current devices was analyzed.
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Reducing the Probability of Failure in Manufacturing Equipment by Quantitative FTA Analysis
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Dynamic risk assessment in autonomous vehicles motion planning
PublicationArguing that an autonomous mobile system is sufficiently safe to operate in presence of other vehicles and objects is an important element in development of such systems. Traditional approach to assure safety is to distinguish between safe and unsafe area and prevent the autonomous vehicle from entering the unsafe area. The paper presents a model of autonomous vehicle control system which uses risk assessment...
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Multimedia industrial and medical applications supported by machine learning
PublicationThis article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...
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A novel architecture for e-learning knowledge assessment systems
PublicationIn this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge assessment products....
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A novel architecture for e-learning knowledge assessment systems
PublicationIn this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge assessment products....
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn 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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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...