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Search results for: AUTOMATED ENVIRONMENT
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Soxhlet Extraction and New Developments Such as Soxtec in: Comprehansive Sampling and Sample Preparation
PublicationSoxhlet extraction is one of the most popular techniques for extraction of analytes from solid materials. Since its discovery in 1879, the standard Soxhlet technique has been routinely applied in almost every analytical laboratory. Up to this day, Soxhlet extraction technique remains a standard technique to which the performance of modern extraction techniques is compared.Over the years, an intensive research on different modifications...
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Studying road restraint systems to develop new guidelines
PublicationThe paper will present a proposed approach to such work along with preliminary results of numerical studies for selected problems using road safety devices such as safety barriers on horizontal curves, the effect of kerbs on bridges or the location of obstacles within the barrier’s working width. The paper will discuss assumptions to a methodology of numerical models, calculations and automated processing of data to help with assessing...
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A structure and design optimization of novel compact microscrip dual-band rat-race coupler with enhanced bandwidth
PublicationIn the letter, a topology of a novel compact wideband dual-band rat-race coupler has been presented along with its computationally efficient design optimization procedure. Reduction of the circuit size has been achieved by meandering transmission lines of the conventional circuit. At the same time, the number of independent geometry parameters has been increased so as to secure sufficient flexibility of the circuit, necessary in...
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Rough Sets Applied to Mood of Music Recognition
PublicationWith the growth of accessible digital music libraries over the past decade, there is a need for research into automated systems for searching, organizing and recommending music. Mood of music is considered as one of the most intuitive criteria for listeners, thus this work is focused on the emotional content of music and its automatic recognition. The research study presented in this work contains an attempt to music emotion recognition...
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Behaviometrics of Digital Games for Children with Autism Spectrum Disorder
PublicationTe paper reports current stage of the project Automated Terapy Monitoring for Children with Developmental Disorders of Autism Spectrum (AUTMON), that aims at development of methods and tools to allow for the automatic evaluation of the therapy progress among children with autism. Finding objective measures suitable for evaluating therapy progress would let create a system supporting those who diagnose autism and the therapists...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublicationOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
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How to Sort Them? A Network for LEGO Bricks Classification
PublicationLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
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Automated Classifier Development Process for Recognizing Book Pages from Video Frames
PublicationOne of the latest developments made by publishing companies is introducing mixed and augmented reality to their printed media (e.g. to produce augmented books). An important computer vision problem that they are facing is classification of book pages from video frames. The problem is non-trivial, especially considering that typical training data is limited to only one digital original per book page, while the trained classifier...
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Intraday price reaction to filing bankruptcy and restructuring proceedings – the evidence from Poland
PublicationThis chapter presents the results of research on the price reaction of shares listed on the Warsaw Stock Exchange to filing bankruptcy and/or restructuring applications. Event study was adopted as the research method, and it was performed at 10, 5, and 1-minute intervals. It was found that the reaction is rapid, as it takes 1–2 minutes after the information on bankruptcy and restructuring applications was made public. Significantly...
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The Concept of Using the Decision-Robustness Function in Integrated Navigation Systems
PublicationThe diversity and non-uniformity of the positioning systems available in maritime navigation systems often impede the watchkeeping officer in the selection of the appropriate positioning system, in particular, in restricted basins. Thus, it is necessary to introduce a mathematical apparatus to suggest, in an automated manner, which of the available systems should be used at the given moment of a sea trip. Proper selection of the...
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Assessment of the Steering Precision of a Hydrographic Unmanned Surface Vessel (USV) along Sounding Profiles Using a Low-Cost Multi-Global Navigation Satellite System (GNSS) Receiver Supported Autopilot
Publicationhe performance of bathymetric measurements by traditional methods (using manned vessels) in ultra-shallow waters, i.e., lakes, rivers, and sea beaches with a depth of less than 1 m, is often difficult or, in many cases, impossible due to problems related to safe vessel maneuvering. For this reason, the use of shallow draft hydrographic Unmanned Surface Vessels (USV) appears to provide a promising alternative method for performing...
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Biometryczna kontrola dostępu
PublicationOpisano szczegółowo algorytm detekcji oraz identyfikacji człowieka na podstawie punktów nodalnych twarzy. Zdefiniowano pojęcia: biometria, proces pomiaru biometrycznego, metody biometrycznej identyfikacji oraz kontrola dostępu. Przedstawiono opis opracowanego systemu biometrycznej identyfikacji wykorzystującego sztuczne sieci neuronowe. Podano wyniki badań oraz przeprowadzono ich wnikliwą dyskusję.Biometrics is the study of automated...
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Influence of finishing colour on the efficiency of automated production line for wooden doors
PublicationPorta KMI Poland S.A. company has implemented a fully automated intelligent technological line TechnoPORTA for customized mass-production of technical door leaves. Each door leaf is provided with a unique QR code. It allows the line modules to individually adjust the machining parameters to the currently processed element according to the IT controlling system. Before en-tering the TechnoPorta line, the door leaves are not sorted,...
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The Proposition of an Automated Honing Cell with Advanced Monitoring
PublicationHoning of holes allows for small shape deviation and a low value of a roughness profile parameter, e.g., Ra parameter. The honing process heats the workpiece and raises its temperature. The increase in temperature causes thermal deformations of the honed holes. The article proposes the construction of a honing cell, containing in addition to CNC honing machine: thermographic camera, sound intensity meter, and software for collecting...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublicationBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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The Use of Liquid Crystal Thermography in Selected Technical and Medical Applications—Recent Development
PublicationThermochromic liquid crystals (TLC) and true-colour digital image processing have been successfully used in non-intrusive technical, industrial and biomedical studies and applications. Thin coatings of TLC at surfaces are utilized to obtain detailed temperature distributions and heat transfer rates for steady or transient processes. Liquid crystals also can be used to make the temperature and velocity fields in liquids visible...
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Comprehensive comparison of compact UWB antenna performance by means of multi-objective optimization
PublicationAn optimization-based procedure for comprehensive performance comparison of alternative compact UWB antenna topologies is discussed. The assessment of the antenna performance is conducted with respect to the structure size and its reflection response. More specifically, the best possible tradeoffs between these two figures of merit are identified through multiobjective optimization at the level...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublicationHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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THE EFFECT OF LOG SORTING STRATEGY ON THE FORECASTED LUMBER VALUE AFTER SAWING PINE WOOD
PublicationThe optimal transformation path for the resource is determined by the quality of a log combined with its dimension. The commercial value of derived products is also closely connected with the size and extent of containing wood deficiencies. The results of studies with three diverse strategies for log sorting are presented in the paper. Resource assessment by a worker without extensive experience in sorting logs, the certified grading...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Pawlak's flow graph extensions for video surveillance systems
PublicationThe idea of the Pawlak's flow graphs is applicable to many problems in various fields related to decision algorithms or data mining. The flow graphs can be used also in the video surveillance systems. Especially in distributed multi-camera systems which are problematic to be handled by human operators because of their limited perception. In such systems automated video analysis needs to be implemented. Important part of this analysis...
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Identification of acoustic event of selected noise sources in a long-term environmental monitoring systems
PublicationABSTRACT Undertaking long-term acoustic measurements on sites located near an airport is related to a problem of large quantities of recorded data, which very often represents information not related to flight operations. In such areas, usually defined as zone of limited use, often other sources of noise exist, such as roads or railway lines treated is such context as acoustic background. Manual verification of such recorded data...
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Process Control and Investigation of Oxidation Kinetics of Postoxidative Effluents Using Gas Chromatography with Pulsed Flame Photometric Detection (GC-PFPD)
PublicationThis article presents the results of investigations on the use of headspace analysis and gas chromatography with pulsed flame photometric detection (HSA-GC-PFPD) to evaluate the effectiveness of oxidation of postoxidative effluents from the production of bitumens. Samples of effluents from the bitumen oxidation unit were used in the experiments. In addition, the kinetics of effluent oxidation was also investigated. The content...
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Selection of circuit geometry for miniaturized microwave components based on concurrent optimization of performance and layout area
PublicationThe paper presents a framework for automated EM-driven circuit geometry selection of miniaturized microwave components. Selection of a particular layout is based directly on miniaturization rates achieved for a set of candidate circuit geometries. Size reduction of the considered structures is obtained by replacing their main building blocks (i.e., conventional transmission lines) with slow-wave composite cells and meander lines....
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Design specification management with automated decision-making for reliable optimization of miniaturized microwave components
PublicationThe employment of numerical optimization techniques for parameter tuning of microwave components has nowadays become a commonplace. In pursuit of reliability, it is most often carried out at the level of full-wave electromagnetic (EM) simulation models, incurring considerable computational expenses. In the case of miniaturized microstrip circuits, densely arranged layouts with strong cross-coupling effects make EM-driven tuning...
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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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Fast EM-Driven Parameter Tuning of Microwave Circuits with Sparse Sensitivity Updates via Principal Directions
PublicationNumerical optimization has become more important than ever in the design of microwave components and systems, primarily as a consequence of increasing performance demands and growing complexity of the circuits. As the parameter tuning is more and more often executed using full-wave electromagnetic (EM) models, the CPU cost of the overall process tends to be excessive even for local optimization. Some ways of alleviating these issues...
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A Development of a Capacitive Voltage Divider for High Voltage Measurement as Part of a Combined Current and Voltage Sensor
PublicationThis article deals with the development of capacitive voltage divider for high voltage measurements and presents a method of analysis and optimization of its parameters. This divider is a part of a combined voltage and current sensor for measurements in high voltage power networks. The sensor allows continuous monitoring of the network distribution status and performs a quick diagnosis and location of possible network failures....
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Rapid Characterization of the Human Breast Milk Lipidome Using a Solid-Phase Microextraction and Liquid Chromatography-Mass Spectrometry-Based Approach.
PublicationHuman breast milk (HBM) is a biofluid consisting of various biomolecules such as proteins, lipids, carbohydrates, minerals and bioactive substances. Due to its unique and complex composition, HBM provides not only nutritional components required for the growth of the infant, but also additional protection against infections. Global insight into the composition of HBM is crucial to understanding the health benefits infants receive...
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Music Information Retrieval – Soft Computing versus Statistics . Wyszukiwanie informacji muzycznej - algorytmy uczące versus metody statystyczne
PublicationMusic Information Retrieval (MIR) is an interdisciplinary research area that covers automated extraction of information from audio signals, music databases and services enabling the indexed information searching. In the early stages the primary focus of MIR was on music information through Query-by-Humming (QBH) applications, i.e. on identifying a piece of music by singing (singing/whistling), while more advanced implementations...
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Explicit Size-Reduction of Circularly Polarized Antennas through Constrained Optimization with Penalty Factor Adjustment
PublicationModern communication systems of high data capacity incorporate circular polarization (CP) as the preferred antenna radiation field configuration. In many applications, integration of the system circuitry with antennas imposes size limitations on CP radiators, which makes their development process a challenging endeavor. This can be mitigated by means of simulation-driven design, specifically, constrained numerical optimization....
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Improved Design Closure of Compact Microwave Circuits by Means of Performance Requirement Adaptation
PublicationNumerical optimization procedures have been widely used in the design of microwave components and systems. Most often, optimization algorithms are applied at the later stages of the design process to tune the geometry and/or material parameter values. To ensure sufficient accuracy, parameter adjustment is realized at the level of full-wave electromagnetic (EM) analysis, which creates perhaps the most important bottleneck due to...
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Optimization-based antenna miniaturization using adaptively-adjusted penalty factors
PublicationThe continuing trend for miniaturization of electronic devices necessitates size reduction of the comprising components and circuitry. Specifically, integrated circuit-antenna modules therein require compact radiators in applications such as 5G communications, implantable and on-body devices, or internet of things (IoT). The conflict between the demands for compact size and elec-trical and field performance can be mitigated by...
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Automated measurement method for assessing thermal-dependent electronic characteristics of thin boron-doped diamond-graphene nanowall structures
PublicationThis paper investigates the electrical properties of boron-doped diamond-graphene (B:DG) nanostructures, focusing on their semiconductor characteristics. These nanostructures are synthesized on fused silica glass and Si wafer substrates to compare their behaviour on different surfaces. A specialized measurement system, incorporating Python-automated code, was developed for an in-depth analysis of electronic properties under various...
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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The In-House Method of Manufacturing a Low-Cost Heat Pipe with Specified Thermophysical Properties and Geometry
PublicationVarious types of heat pipes are available to purchase off the shelf, from various manufacturers, but most of them have strictly defined geometry and technical parameters. However, when there is a need to use a heat pipe (HP) with an unusual size and shape or working conditions other than the standard ones, it becomes very costly to order them from manufacturers, especially in small quantities, and only a few producers are willing...
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Neural Architecture Search for Skin Lesion Classification
PublicationDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Surrogate-Assisted Design of Checkerboard Metasurface for Broadband Radar Cross-Section Reduction
PublicationMetasurfaces have been extensively exploited in stealth applications to reduce radar cross section (RCS). They rely on the manipulation of backward scattering of electromagnetic (EM) waves into various oblique angles. However, arbitrary control of the scattering properties poses a significant challenge as a design task. Yet it is a principal requirement for making RCS reduction possible. This article introduces a surrogate-based...
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Low-Cost Automated Design of Compact Branch-Line Couplers
PublicationBranch-line couplers (BLCs) are important components of wireless communication systems. Conventional BLCs are often characterized by large footprints which make miniaturization an important prerequisite for their application in modern devices. State-of-the-art approaches to design of compact BLCs are largely based on the use of high-permittivity substrates and multi-layer topologies. Alternative methods involve replacement of transmission-line...
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Novel analysis methods of dynamic properties for vehicle pantographs
PublicationTransmission of electrical energy from a catenary system to traction units must be safe and reliable especially for high speed trains. Modern pantographs have to meet these requirements. Pantographs are subjected to several forces acting on their structural elements. These forces come from pantograph drive, inertia forces, aerodynamic effects, vibration of traction units etc. Modern approach to static and dynamic analysis should...
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Pathological and physiological high-frequency oscillations in focal human epilepsy
PublicationHigh-frequency oscillations (HFO; gamma: 40-100 Hz, ripples: 100-200 Hz, and fast ripples: 250-500 Hz) have been widely studied in health and disease. These phenomena may serve as biomarkers for epileptic brain; however, a means of differentiating between pathological and normal physiological HFO is essential. We categorized task-induced physiological HFO during periods of HFO induced by a visual or motor task by measuring frequency,...
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Evaluating the Catastrophic Rainfall of 14 July 2016 in the Catchment Basin of the Urbanized Strzyza Stream in Gdańsk, Poland
PublicationWe analyzed the causes, the course, and consequences of the extreme precipitation events that occurred 14 July 2016 in the watershed of Strzyza Creek in Gdańsk, Poland. Automated rain gauges located in Strzyża catchment registered a total precipitation lasting about 16 hours – from 129 to 160 mm of rain depth. More in-depth analysis based on rain data collected by Gdańsk University of Technology (GUT) rain station was done. The...
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Diversity of fecal coliforms and their antimicrobial resistance patterns in wastewater treatment model plant.
PublicationThe occurrence of resistance patterns among wastewater fecal coliforms was determined in the study. Susceptibility of the isolates was tested against 19 antimicrobial agents: aminoglycosides, aztreonam, carbapenems, cephalosporines, b-lactam/b-lactamase inhibitors, penicillines, tetracycline, trimethoprim/sulfamethoxazole, and fluoroquinolones. Additionally the removal of resistant isolates was evaluated in the laboratory-scale...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublicationSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...