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Wyniki wyszukiwania dla: sztuczna inteligencja
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublikacjaMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublikacjaThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Digital Innovations and Smart Solutions for Society And Economy: Pros and Cons
PublikacjaRecent developments in artificial intelligence (AI) may involve significant potential threats to personal data privacy, national security, and social and economic stability. AI-based solutions are often promoted as “intelligent” or “smart” because they are autonomous in optimizing various processes. Be-cause they can modify their behavior without human supervision by analyzing data from the environ-ment, AI-based systems may be...
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Adjusting the Stiffness of Supports during Milling of a Large-Size Workpiece Using the Salp Swarm Algorithm
PublikacjaThis paper concerns the problem of vibration reduction during milling. For this purpose, it is proposed that the standard supports of the workpiece be replaced with adjustable stiffness supports. This affects the modal parameters of the whole system, i.e., object and its supports, which is essential from the point of view of the relative tool–workpiece vibrations. To reduce the vibration level during milling, it is necessary to...
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Klasyfikator SVM w zastosowaniu do synchronizacji sygnału OFDM zniekształconego przez kanał wielodrogowy
PublikacjaW pracy przedstawiono analizę przydatności klasyfikatora SVM bazującego na uczeniu maszynowym do estymacji przesunięcia czasowego odebranego symbolu OFDM. Przedstawione wyniki wykazują, że ten klasyfikator potrafi zapewnić synchronizację dla różnych kanałów wielodrogowych o wysokim poziomie szumu. Eksperymenty przeprowadzone w Matlabie z użyciem modeli modulatora i demodulatora wykazały, że w większości przypadków klasyfikator...
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Zastosowanie sztucznej inteligencji do identyfikacji groźnych wypadków samochodowych
PublikacjaOgromna liczba ofiar wypadków drogowych i ofiar śmiertelnych z tym związanych jest powodem priorytetowego podejścia organizacji światowych do problemu bezpieczeństwa pojazdów samochodowych. Pomimo dużych nakładów finansowych nadal nie powstał system globalnego zarządzania wypadkami. Celem tej pracy jest inteligentny system pokładowy, który na podstawie sygnałów pomiarowych będzie wnioskować o występujących zagrożeniach. W dalszej...
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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IFE: NN-aided Instantaneous Pitch Estimation
PublikacjaPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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Bartosz Szostak mgr inż.
OsobyBartosz Szostak w 2019 r. ukończył studia inżynierskie na Politechnice Gdańskiej na kierunku Geodezja i Kartografia. W 2021 r. ukończył studia magisterskie również w dziedzinie Geodezji i Kartografii na Politechnice Gdańskiej. Tematyka jego prac dyplomowych dotyczyła uczenia maszynowego i detekcji obiektów.
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Educational Data Mining
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System for automatic singing voice recognition
PublikacjaW artykule przedstawiono system automatycznego rozpoznawania jakości i typu głosu śpiewaczego. Przedstawiono bazę danych oraz zaimplementowane parametry. Algorytmem decyzyjnym jest algorytm sztucznych sieci neuronowych. Wytrenowany system decyzyjny osiąga skuteczność ok. 90% w obydwu kategoriach rozpoznawania. Dodatkowo wykazano przy pomocy metod statystycznych, że wyniki działania systemu automatycznej oceny jakości technicznej...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublikacjaSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal
Czasopisma -
Spatial Visualization Based on Geodata Fusion Using an Autonomous Unmanned Vessel
PublikacjaThe visualization of riverbeds and surface facilities on the banks is crucial for systems that analyze conditions, safety, and changes in this environment. Hence, in this paper, we propose collecting, and processing data from a variety of sensors—sonar, LiDAR, multibeam echosounder (MBES), and camera—to create a visualization for further analysis. For this purpose, we took measurements from sensors installed on an autonomous, unmanned...
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Viability of decisional DNA in robotics
PublikacjaThe Decisional DNA is an artificial intelligence system that uses prior experiences to shape future decisions. Decisional DNA is written in the Set Of Experience Knowledge Structure (SOEKS) and is capable of capturing and reusing a broad range of data. Decisional DNA has been implemented in several fields including Alzheimer’s diagnosis, geothermal energy and smart TV. Decisional DNA is well suited to use in robotics due to the...
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APPLICATION OF APRIORI ALGORITHM IN THE LAMINATION PROCESS IN YACHT PRODUCTION
PublikacjaThe article specifies the dependence of defects occurring in the lamination process in the production of yachts. Despite great knowledge about their genesis, they cannot be completely eliminated. Authentic data obtained through cooperation with one of the Polish yacht shipyards during the years 2013–2017 were used for the analysis. To perform a simulation, the sample size was observed in 1450 samples, consisting of 6 models of...
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A Concept of Automatic Film Color Grading Based on Music Recognition and Evoked Emotions
PublikacjaThe article presents the aspects of the final selection of the color of shots in film production based on the psychology of color. First of all, the elements of color processing, contrast, saturation or white balance in the film shots were presented and the definition of color grading was given. In the second part of the article the analysis of film music was conducted in the context of stimulating appropriate emotions while watching...