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Search results for: PROBLEM-BASED LEARNING
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublicationShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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Influence of statistical errors on damage detection based on structuralflexibility and mode shape curvature
PublicationDamage detection procedures based on measured natural frequencies and building structure mode shapes are discussed in this paper. Modal curvature and structural flexibility approaches are tested. Attention is paid to the modal identification errors that influence damage detection. This problem is studied using a computer simulation of a simple supported beam. For practical cases, the peak picking methodand its statistical errors...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublicationLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Bimodal Emotion Recognition Based on Vocal and Facial Features
PublicationEmotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Online Interactivity – Shift Towards E-textbook-based Medical Education
PublicationTextbooks have played the leading role in academic education for centuries and their form has evolved, adapting to the needs of students, teachers and technological possibilities. Advances in technology have caused educators to look for new sources of knowledge development, which students could use inside and outside the classroom. Today’s sophisticated learning tools range from virtual environments to interactive multimedia resources,...
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On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublicationNitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred...
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Ladder-Based Synthesis and Design of Low-Frequency Buffer-Based CMOS Filters
PublicationBuffer-based CMOS filters are maximally simplified circuits containing as few transistors as possible. Their applications, among others, include nano to micro watt biomedical sensors that process physiological signals of frequencies from 0.01 Hz to about 3 kHz. The order of a buffer-based filter is not greater than two. Hence, to obtain higher-order filters, a cascade of second-order filters is constructed. In this paper, a more...
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Parametric impulsive noise detector for corrupted audio signals based on hidden Markow model
PublicationThe paper addresses the problem of impulsive noise detection for audio signals. A structure of threshold parameter detectors using modelingof signals was introduced. the algorithm of the noise detection, based on discrete-time hidden Markow model (HMM)of whitened audio signal is elaborated
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Decoupled Kalman filter based identification of time-varying FIR systems
PublicationWhen system parameters vary at a fast rate, identification schemes based on model-free local estimation approaches do not yield satisfactory results. In cases like this, more sophisticated parameter tracking procedures must be used, based on explicit models of parameter variation (often referred to as hypermodels), either deterministic or stochastic. Kalman filter trackers, which belong to the second category, are seldom used in...
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Impact of low-temperature sintering on the Fe-based amorphous coatings
PublicationBulk metallic glasses (BMGs) have gained a lot of attention in recent years due to their outstanding properties such as high hardness and excellent wear and corrosion resistance. However, they are restricted in industrial applications due to their extreme brittleness. Iron based amorphous coatings from BMGs are the best solution to use them by overcoming the problem of extreme brittleness. The coatings can be sprayed by various...
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Exploring perceptions of pro environmental educational mobile applications based on semantic field analysis
PublicationThe paper aims to identify multidimensional perceptions of mobile apps by their users. Special attention has been paid to pro-environmental educational apps. Semantic field analysis and measurement of emotional temperatures were performed to achieve this goal. Transcripts from seven focus group interviews were used as research material. The results indicate that functionality based on a reward or benefit system reinforces environmentally...
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Desirability-based optimization of dual-fuel diesel engine using acetylene as an alternative fuel
Publicationhe study examined the dual-fuel engine performance employing acetylene gas as primary fuel and diesel as pilot fuel. The engine's operational parameters were adjusted using the Box-Behnken design, and the results were recorded. The best operating settings were yielded as 81.25 % engine load, 4.48 lpm acetylene gas flow rate and the compression ratio were 18. At this optimized setting the BTE was 27.1 % and the engine emitted 360...
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Wikipedia and WordNet integration based on words co-occurrences
PublicationThe article presents a method for automatic integration of two lexical resources: semantic dictionary WordNet and electronic encyclopaedia Wikipedia. Our goal is to add automatically an semantic tags - a WordNet synset identifier to the title of the Wikipedia article. We've analyze several different ap-proaches to these problem and implement our own solution, based on word occurrences in synsets descriptions and the article body....
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Multimodal human-computer interfaces based on advanced video and audio analysis
PublicationMultimodal interfaces development history is reviewed briefly in the introduction. Some applications of multimodal interfaces to education software for disabled people are presented. One of them, the LipMouse is a novel, vision-based human-computer interface that tracks user’s lip movements and detect lips gestures. A new approach to diagnosing Parkinson’s disease is also shown. The progression of the disease can be measured employing...
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Multimodal human-computer interfaces based on advanced video and audio analysis
PublicationMultimodal interfaces development history is reviewed briefly in the introduction. Examples of applications of multimodal interfaces to education software and for the disabled people are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with mouth gestures and the audio interface for speech stretching for hearing impaired and stuttering people. The Smart...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Marking the Allophones Boundaries Based on the DTW Algorithm
PublicationThe paper presents an approach to marking the boundaries of allophones in the speech signal based on the Dynamic Time Warping (DTW) algorithm. Setting and marking of allophones boundaries in continuous speech is a difficult issue due to the mutual influence of adjacent phonemes on each other. It is this neighborhood on the one hand that creates variants of phonemes that is allophones, and on the other hand it affects that the border...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Simulation Method for Scheduling Linear Construction Projects Using the Learning– Forgetting Effect
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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
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Machine Learning and data mining tools applied for databases of low number of records
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Effects of mutual learning in physical education to improve health indicators of Ukrainian students
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Classification of submandibular salivary stones based on ultrastructural studies
PublicationIntroduction: Sialolithiasis remains a clinical problem with unclear etiopathogenesis, lack of prevention methods, and only surgical treatment. Materials and methods: An ultrastructure examination of submandibular sialoliths obtained from patients with chronic sialolithiasis was conducted using a scanning electron microscope and X‐ray photoelectron spectroscopy. Results: Based on the results, we divided sialoliths into three types:...
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Current based Normalized Triple Covariance as a bearings diagnostic feature in induction motor
PublicationDiagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides...
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Open shop problem with zero-one time operations and integer release date/deadline intervals
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Analysis of the Multiple Attribute Decision Making Problem with Incomplete Information about Preferences among the Criteria
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Problem of optimal load distribution between generators minimizing risk of enegretic ship system overload.
PublicationOmówiono system rozdziału mocy czynnych pomiędzy generatorami w systemie energetycznym statku. Minimalizuje się ryzyko przeciążeń systemu przy jednoczesnej minimalizacji kosztów wytwarzania energii w systemie.
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Symulacje komputerowe w geotechnice. Problem szacowania parametrów materiałowych i ważności rozwiązań numerycznych
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Problem wyboru bezsmarowego materiału ślizgowego dla łożysk pracujących w warunkach małych oscylacji
PublicationOmówiono przyczyny przyspieszonego zużywania się elementów węzłów łożyskowych, w których zastosowano ekologiczne materiały bezsmarowe. Wykazano szczególny wpływ oscylacji o małej amplitudzie - najczęściej występujących w sposób niezamierzony w pracy łożyska - na zużywanie się materiałów.
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Problem tożsamości jednostki w obliczu współczesnych zmian cywilizacyjnych i społecznych. Przegląd stanowisk
PublicationW tekście zawarty jest krótki przegląd stanowisk teoretycznych odnoszących się do pojęcia tożsamości w kontekście współczesności.
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A General Scheme of a Branch-and-Bound Approach for the Sensor Selection Problem in Near-Field Broadband Beamforming
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Alkohol-społeczny problem XXI wieku. Zastosowanie biowskaźników spożywania alkoholu w diagnostyce medycznej.
PublicationAlkohol etylowy jest legalną i ogólnodostępną substancją o działaniu psychoaktywnym. Spożywany w niewielkich ilościach może pozytywnie wpływać na zdrowie, ale jego nadmierna konsumpcja powoduje silne uzależnienie. Może być to przyczyną agresywnych zachowań, przemocy w rodzinie, problemów w kontaktach z ludźmi, problemów z prawem, samobójstw, wypadków samochodowych oraz problemów finansowych. Dlatego też, szybka i jednoznaczna diagnostyka...
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublicationBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Preference-based evolutionary multi-objective optimization in ship weather routing
PublicationIn evolutionary multi-objective optimization (EMO) the aim is to find a set of Pareto-optimal solutions. Such approach may be applied to multiple real-life problems, including weather routing (WR) of ships. The route should be optimal in terms of passage time, fuel consumption and safety of crew and cargo while taking into account dynamically changing weather conditions. Additionally it must not violate any navigational constraints...
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Evaluation of position estimation based on accelerometer data
PublicationThe paper concerns the problem of integrating data from accelerometers. A suitable model of a MEMS accelerometer is presented which is a part of inertial measurement units (IMU). Such units allow to measure orientation as well as to localize systems. They also appear to be applicable for systems positioning. The main purpose of the paper is to discuss conditions that must be satisfied to calculate the location of the sensor by...
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DYNAMIC POSITIONING CAPABILITY ASSESSMENT BASED ON OPTIMAL THRUST ALLOCATION
PublicationThe article presents an efficient method of optimal thrust allocation over the actuators in a dynamically positioned ship, according to the DNV-ST-0111 standard, Level 1. The optimisation task is approximated to a convex problem with linear constraints and mathematically formulated as quadratic programming. The case study is being used to illustrate the use of the proposed approach in assessing the DP capability of a rescue ship....
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Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering
PublicationContext-aware Recommender Systems aim to provide users with better recommendations for their current situation. Although evaluations of recommender systems often focus on accuracy, it is not the only important aspect. Often recommendations are overspecialized, i.e. all of the same kind. To deal with this problem, other properties can be considered, such as serendipity. In this paper, we study how an ontology-based and context-aware...
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From Knowledge based Vision Systems to Cognitive Vision Systems: A Review
PublicationComputer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...
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Implementation and performance evaluation of the agent-based algorithm for ANN training
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Towards 5G — Cloud-based Radio Access Networks
PublicationIn the paper a general concept of the 5G network architecture is presented as well as system requirements having impact on innovative solutions in the 5G network are highlighted. A major part of the paper is both presentation and discussion of the problem of Cloud Radio Access Network introduction for public networks in which the cell and resource virtualisation will be implemented. On the other hand, the problem of resource virtualization...