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Wyniki wyszukiwania dla: deep learning, genetic algorithm, artificial neural networks, predictive maintenance, cost efficient maintenance
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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Efficient methods for radio location service in cellular communication networks
PublikacjaW artykule przedstawiono dwie oryginalne metody lokalizowania terminala ruchomego w sieciach komórkowych trzeciej generacji. Metody te podczas estymacji położenia terminala nie wymagają znajomości różnicy czasów w synchronizacji poszczególnych stacji bazowych, przez co są tanie w implementacji. Przedstawiono wyniki badań symulacyjnych zaproponowanych metod.
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical 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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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublikacjaWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis 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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A new approach to design of weather disruption-tolerant wireless mesh networks
PublikacjaWireless Mesh Networks, offering transmission rates of 1–10 Gb/s per a millimeter-wave link (utilizing the 71–86 GHz band) seem to be a promising alternative to fiber optic backbone metropolitan area networks because of significantly lower costs of deployment and maintenance. However, despite providing high transmission rates in good weather conditions, high-frequency wireless links are very susceptible to weather disruptions....
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Efficient analysis of waveguide componets using a hybrid PEE-FDFD algorithm.
PublikacjaZaproponowano przyspieszenie analizy podzespołów falowodowych poprzez połączenie metody różnic skończonych w dziedzinie częstotliwości FDFD oraz rozwinięcia w funkcje własne PEE. Proponowane sformułowanie pozwala jawnie zdefiniować operator macierzowy dla zadanego problemu. Proponowana technika została zaprezentowana zarówno dla problemów własnych jak i układów z pobudzeniem.
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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Complex Predictive Solution for Computerized Processes in Tire Industry
PublikacjaFollowing increasing market needs of productivity, cost reduction and safety requirements, computerized industry are faced to finding optimum between economic aspects of business and safety-related risk management. Modern factories equipped with computerized processes and extended diagnostic tools to support operator do not often use of all information’s which comes from the equipment. Some of the relations between the events are...
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublikacjaThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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On minimum cost edge searching
PublikacjaWe consider the problem of finding edge search strategies of minimum cost. The cost of a search strategy is the sum of searchers used in the clearing steps of the search. One of the natural questions is whether it is possible to find a search strategy that minimizes both the cost and the number of searchers used to clear a given graph G. We call such a strategy ideal. We prove, by an example, that ideal search strategies do not...
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BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublikacjaDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
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Genetic Positioning of Fire Stations Utilizing Grid-computing Platform
PublikacjaA chapter presents a model for determining near-optimal locations of fire stations based on topography of a given area and location of forests, rivers, lakes and other elements of the site. The model is based on principals of genetic algorithms and utilizes the power of the grid to distribute and execute in parallel most performance-demanding computations involved in the algorithm.
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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5G/6G optical fronthaul modeling: cost and energy consumption assessment
PublikacjaIn fifth generation (5G) and the future beyond 5G (6G) radio access networks (RANs), the cost of fronthaul deployment is a main challenge for mobile network operators. Depending on different constraints, there are various solutions to deploy an efficient fronthaul. Fiber-optic-based fronthaul offers long-term support with regard to a rapid increase in capacity demands. When fiber connections, either point-to-point (P2P) or point-to-multipoint...
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Cost-Efficient EM-Driven Size Reduction of Antenna Structures by Multi-Fidelity Simulation Models
PublikacjaDesign of antenna systems for emerging application areas such as the Internet of Things (IoT), fifth generation wireless communications (5G), or remote sensing, is a challenging endeavor. In addition to meeting stringent performance specifications concerning electrical and field properties, the structure has to maintain small physical dimensions. The latter normally requires searching for trade-off solutions because miniaturization...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublikacjaNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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Localization of impulsive disturbances in archive audio signals using predictive matched filtering
PublikacjaThe problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated...
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Efficient sampling of high-energy states by machine learning force fields
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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Modeling and optimizing the removal of cadmium by Sinapis alba L. from contaminated soil via Response Surface Methodology and Artificial Neural Networks during assisted phytoremediation with sewage sludge
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Neural Networks in the Diagnostics Process of Low-Power Solar Plant Devices
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
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Extended Hopfield models of neural networks for combinatorial multiobjective optimization problems
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Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
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Automatic singing voice recognition employing neural networks and rough sets
PublikacjaCelem prac opisanych w referacie jest automatyczne rozpoznawanie głosów śpiewaczych. Do tego celu utworzona została baza nagrań próbek śpiewu profesjonalnego i amatorskiego. Próbki poddane zostały parametryzacji parametrami zaproponowanymi przez autorów ściśle do tego celu. Sposób wyznaczenia parametrów i ich interpretacja fizyczna przedstawione są w referacie. Parametry wprowadzane są do systemów decyzyjnych, klasyfikatorów opartych...
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Musical phrase representation and recognition by means of neural networks and rough sets.
PublikacjaW artykule przedstawiono podstawowe definicje dotyczące frazy muzycznej. W eksperymentach posłużono się zapisem parametrycznym. W celu wzmocnienia procesu rozpoznawania wykorzystano kodowanie entropijne muzyki. W eksperymentach klasyfikacji oparto się o sztuczne sieci neuronowe i metodę zbiorów przybliżonych. Słowa kluczowe: fraza muzyczna, klasyfikacja, sztuczne sieci neuronowe, metoda zbiorów przybliżonych
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Comparison of effectiveness of musical sound separation algorithms employing neural networks.
PublikacjaNiniejszy referat przedstawia kilka algorytmów służących do separacji dźwięków instrumentów muzycznych. Zaproponowane podejście do dekompozycji miksów dźwiękowych opiera się na założeniu, że wysokość dźwięków w miksie jest znana, tzn. wejściem dla algorytmów jest przebieg zmian wysokości dźwięków składowych miksu. Proces estymacji fazy i amplitudy składowych harmonicznych wykorzystuje dopasowywanie zespolonych przebiegów harmonicznych...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublikacjaLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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Taking decisions in the diagnostic intelligent systems on the basis information from an artificial neural network
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Artificial Neural Network (ANN)-Based Voltage Stability Prediction of Test Microgrid Grid
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Estimation of Synchronous Generator and AVR Parameters Based on Gradient and Genetic Methods
PublikacjaThe author present a method for the estimation of selected synchronous generator model and AVR parameters using a gradient and a genetic algorithm. The paper shows an example of model parameter estimation for a turbogenerator, based on the generator voltage time responses obtained during an active and reactive power rejection test
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether 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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Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice
PublikacjaThe vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron,...
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Magnetic deep eutectic solvents as efficient media for extraction of furfural and 5-hydroxymethylfurfural from aqueous samples
PublikacjaThe extraction of furfural (FF) and 5-hydroxymethylfurfural (HMF) from hydrolysates is currently one of the main challenges in bio-refinery. In this work, the separation of FF and HMF from the aqueous phase was carried out using a new type of green solvents – Magnetic Deep Eutectic Solvents (MDES). A conductor-like screening model for realistic solvents (COSMO-RS) was used for the preselection of 400 MDES. MDES which exhibit the...
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Design of dimensionally stable composites using efficient global optimization method
PublikacjaDimensionally stable material design is an important issue for space structures such as space laser communication systems, telescopes, and satellites. Suitably designed composite materials for this purpose can meet the functional and structural requirements. In this paper, it is aimed to design the dimensionally stable laminated composites by using efficient global optimization method. For this purpose, the composite plate optimization...
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Measures of region failure survivability for wireless mesh networks
PublikacjaWireless mesh networks (WMNs) are considered as a promising alternative to wired local, or metropolitan area networks. However, owing to their exposure to various disruptive events, including natural disasters, or human threats, many WMN network elements located close to the failure epicentre are frequently in danger of a simultaneous failure, referred to as a region failure. Therefore, network survivability, being the ability...
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Supervised model predictive control of wastewater treatment plant
PublikacjaAn optimizing control of a wastewater treatment plant (WWTP), allowing for cost savings over long time period and fulfilling effluent discharge limits at the same time, requires application of advanced control techniques. Model Predictive Control (MPC) is a very suitable control technology for a synthesis of such a truly multivariable controller that can handle constraints and accommodate model-based knowledge combined with hard...
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Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry
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Efficient calculation of the resonant frequencies of a SIW resonator with FDFD-based macromodel algorithm
PublikacjaW pracy przedstawiono efektywną metodę do analizy struktur ze integrowanym podłożem (SIW). W celu szybkiego obliczenia częstotliwości rezonansowych używany jest algorytm FDFD z zaimplementowanymi makromodelami.
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Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network
PublikacjaArtificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper pesents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to...
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Federated Learning in Healthcare Industry: Mammography Case Study
PublikacjaThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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Concurrent DNA Copy-Number Alterations and Mutations in Genes Related to Maintenance of Genome Stability in Uninvolved Mammary Glandular Tissue from Breast Cancer Patients
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ZASTOSOWANIE OPROGRAMOWANIA ERP Z ZAKRESU „PLANT MAINTENANCE” NA PRZYKŁADZIE SAP PM JAKO NARZĘDZIA DLA SŁUŻB UTRZYMANIA RUCHU OBIEKTU OFFSHORE
PublikacjaW artykule poruszono kwestię planowania zasobów przedsiębiorstwa z wykorzystaniem oprogramowania ERP. Efektywne planowanie zarządzania całością zasobów przedsiębiorstwa polega głównie na: - zapewnieniu wysokiej jakości produktów, - maksymalizacji ekonomicznego okresu użytkowania parku maszynowego, -maksymalizacji zdolności produkcyjnych, - minimalizacji kosztów utrzymania sprzętu w sprawności operacyjnej, - zapewnieniu bezpiecznych...
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Hierarchical predictive control of integrated wastewater treatment systems
PublikacjaThe paper proposes an approach to designing the control structure and algorithms for optimising control of integrated wastewater treatment plant-sewer systems (IWWTS) under a full range of disturbance inputs. The optimised control of IWWTS allows for significant cost savings, fulfilling the effluent discharge limits over a long period and maintaining the system in sustainable operation. Due to the specific features of a wastewater...
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Artificial Intelligence-Based Weighting Factor Autotuning for Model Predictive Control of Grid-Tied Packed U-Cell Inverter
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Brain-Inspired Deep Networks for Facial Expression Recognition. Frontiers in Biomedical Technologies
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