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Wyszukujesz frazę "artificial artificial intelligence" wg kryterium: Temat


Wyświetlanie 1-11 z 11
Tytuł:
Application of evolutionary algorithm to design minimal phase digital filters with non-standard amplitude characteristics and finite bit word length
Autorzy:
Słowik, A.
Powiązania:
https://bibliotekanauki.pl/articles/202324.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
evolutionary algorithms
digital filters
minimal phase
finite bits word length
Opis:
In this paper an application of evolutionary algorithm to design minimal phase digital filters with non-standard amplitude characteristics and with finite bit word length is presented. Four digital filters with infinite impulse response were designed using the proposed method. These digital filters possess: linearly falling characteristics, linearly growing characteristics, nonlinearly falling characteristics, and nonlinearly growing characteristics, and they are designed using bit words with an assumed length. This bit word length is connected with a processing register size. This register size depends on hardware possibilities where digital filter is to be implemented. In this paper, a modification of the mutation operator is introduced too. Due to this modification, better results were obtained in relation to the results obtained using the evolutionary algorithm with other mutation operators. The digital filters designed using the proposed method can be directly implemented in the hardware (DSP system) without any additional modifications.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2011, 59, 2; 125-135
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Residual life estimation of fabricated humidity sensors using different artificial intelligence techniques
Autorzy:
Bhargava, C.
Aggarwal, J.
Sharma, P. K.
Powiązania:
https://bibliotekanauki.pl/articles/201564.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
composite material
artificial intelligence
humidity sensor
accelerated life testing
SEM
materiał kompozytowy
sztuczna inteligencja
czujnik wilgotności
Opis:
Background: a humidity sensor is used to sense and measure the relative humidity of air. A new composite system has been fabricated using environmental pollutants such as carbon black and low-cost zinc oxide, and it acts as a humidity sensor. Residual life of the sensor is calculated and an expert system is modelled. For properties and nature confirmation, characterization is performed, and a sensing material is fabricated. Methodology: characterization is performed on the fabricated material. Complex impedance spectroscopy (CIS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) are all used to confirm the surface roughness, its composite nature as well as the morphology of the composite. The residual lifetime of the fabricated humidity sensor is calculated by means of accelerated life testing. An intelligent model is designed using artificial intelligence techniques, including the artificial neural network (ANN), fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS). Results: maximum conductivity obtained is 6.4£10−3 S/cm when zinc oxide is doped with 80% of carbon black. Conclusion: the solid composite obtained possesses good humidity-sensing capability in the range of 30–95%. ANFIS exhibits the maximum prediction accuracy, with an error rate of just 1.1%.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 1; 147-154
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Early detection of major diseases in turmeric plant using improved deep learning algorithm
Autorzy:
Devisurya, V.
Devi Priya, R.
Anitha, N.
Powiązania:
https://bibliotekanauki.pl/articles/2173642.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
computer vision
turmeric leaf diseases detection
sztuczna inteligencja
wizja komputerowa
wykrywanie chorób liści kurkumy
Opis:
Turmeric is affected by various diseases during its growth process. Not finding its diseases at early stages may lead to a loss in production and even crop failure. The most important thing is to accurately identify diseases of the turmeric plant. Instead of using multiple steps such as image pre-processing, feature extraction, and feature classification in the conventional method, the single-phase detection model is adopted to simplify recognizing turmeric plant leaf diseases. To enhance the detection accuracy of turmeric diseases, a deep learning-based technique called the Improved YOLOV3-Tiny model is proposed. To improve detection accuracy than YOLOV3-tiny, this method uses residual network structure based on the convolutional neural network in particular layers. The results show that the detection accuracy is improved in the proposed model compared to the YOLOV3-Tiny model. It enables anyone to perform fast and accurate turmeric leaf diseases detection. In this paper, major turmeric diseases like leaf spot, leaf blotch, and rhizome rot are identified using the Improved YOLOV3-Tiny algorithm. Training and testing images are captured during both day and night and compared with various YOLO methods and Faster R-CNN with the VGG16 model. Moreover, the experimental results show that the Cycle-GAN augmentation process on turmeric leaf dataset supports much for improving detection accuracy for smaller datasets and the proposed model has an advantage of high detection accuracy and fast recognition speed compared with existing traditional models.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 2; art. no. e140689
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent system supporting technological process planning for machining and 3D printing
Autorzy:
Rojek, Izabela
Mikołajewski, Dariusz
Kotlarz, Piotr
Macko, Marek
Kopowski, Jakub
Powiązania:
https://bibliotekanauki.pl/articles/2090703.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
AI
intelligent system
technological process
machining
3D printing
sztuczna inteligencja
system inteligentny
proces technologiczny
obróbka skrawaniem
druk 3D
Opis:
The study aimed to develop a system supporting technological process planning for machining and 3D printing. Such a system should function similarly to the way human experts act in their fields of expertise and should be capable of gathering the necessary knowledge, analysing data, and drawing conclusions to solve problems. This could be done by utilising artificial intelligence (AI) methods available within such systems. The study proved the usefulness of AI methods and their significant effectiveness in supporting technological process planning. The purpose of this article is to show an intelligent system that includes knowledge, models, and procedures supporting the company’s employees as part of machining and 3D printing. Few works are combining these two types of processing. Nowadays, however, these two types of processing overlap each other into a common concept of hybrid processing. Therefore, in the opinion of the authors, such a comprehensive system is necessary. The system-embedded knowledge takes the form of neural networks, decision trees, and facts. The system is presented using the example of a real enterprise. The intelligent expert system is intended for process engineers who have not yet gathered sufficient experience in technological-process planning, or who have just begun their work in a given production enterprise and are not very familiar with its machinery and other means of production.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; e136722, 1--8
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent system supporting technological process planning for machining and 3D printing
Autorzy:
Rojek, Izabela
Mikołajewski, Dariusz
Kotlarz, Piotr
Macko, Marek
Kopowski, Jakub
Powiązania:
https://bibliotekanauki.pl/articles/2173593.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
AI
intelligent system
technological process
machining
3D printing
sztuczna inteligencja
system inteligentny
proces technologiczny
obróbka skrawaniem
druk 3D
Opis:
The study aimed to develop a system supporting technological process planning for machining and 3D printing. Such a system should function similarly to the way human experts act in their fields of expertise and should be capable of gathering the necessary knowledge, analysing data, and drawing conclusions to solve problems. This could be done by utilising artificial intelligence (AI) methods available within such systems. The study proved the usefulness of AI methods and their significant effectiveness in supporting technological process planning. The purpose of this article is to show an intelligent system that includes knowledge, models, and procedures supporting the company’s employees as part of machining and 3D printing. Few works are combining these two types of processing. Nowadays, however, these two types of processing overlap each other into a common concept of hybrid processing. Therefore, in the opinion of the authors, such a comprehensive system is necessary. The system-embedded knowledge takes the form of neural networks, decision trees, and facts. The system is presented using the example of a real enterprise. The intelligent expert system is intended for process engineers who have not yet gathered sufficient experience in technological-process planning, or who have just begun their work in a given production enterprise and are not very familiar with its machinery and other means of production.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; art. no. e136722
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modern methods in the field of machine modelling and simulation as a research and practical issue related to Industry 4.0
Autorzy:
Rojek, Izabela
Macko, Marek
Mikołajewski, Dariusz
Sága, Milan
Burczyński, Tadeusz
Powiązania:
https://bibliotekanauki.pl/articles/2086825.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Industry 4.0
Internet of Things
artificial intelligence
models
AI
simulation
IoT
Przemysł 4.0
internet rzeczy
internet przedmiotów
sztuczna inteligencja
modele
symulacja
Opis:
Artificial intelligence (AI) is changing many areas of technology in the public and private spheres, including the economy. This report reviews issues related to machine modelling and simulations concerning further development of mechanical devices and their control systems as part of novel projects under the Industry 4.0 paradigm. The challenges faced by the industry have generated novel technologies used in the construction of dynamic, intelligent, flexible and open applications, capable of working in real time environments. Thus, in an Industry 4.0 environment, the data generated by sensor networks requires AI/CI to apply close-to-real-time data analysis techniques. In this way industry can face both fresh opportunities and challenges, including predictive analysis using computer tools capable of detecting patterns in the data based on the same rules that can be used to formulate the prediction.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; e136717, 1--12
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Power quality analysis in electrical drives and a case study of artificial intelligence prediction algorithm for fault deterrent electrical drives
Autorzy:
Kumarasamy, Vishnu Murthy
Loganathan, Ashok Kumar
Powiązania:
https://bibliotekanauki.pl/articles/2173673.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
voltage sag
voltage swell
voltage imbalance
machine learning
inverter drives
artificial intelligence
wzrost napięcia
spadek napięcia
asymetria napięcia
uczenie maszynowe
napędy falownikowe
sztuczna inteligencja
Opis:
Since electrical drives have become an integral element of any industrial sector, power quality difficulties have been well expected, and delivering genuine quality of the same has proven to be a difficult challenge. Since power quality relies on load side non-linearity and high semiconductor technology consumption, it is a serious concern. The efficiency of the drive segment employed in the sector is increasingly becoming a topic of discussion in today’s market. Numerous reviews of available literature have found problems with the load side as well as with electrical drive proficiency, as a result of the issues listed above. A high level of power quality vulnerability is simply too much. Even the most advanced technology has its limits when it comes to drive operation. Research on the grid-side quality issues of electrical drives is the focus of this article. After field testing of grid power quality, each parametric analysis is performed to identify crucial parameters that can cause industrial drives to fail. Based on this discovery, a machine learning strategy was developed and an artificial intelligence technique was proposed to administer the fault deterrent prediction algorithm. An accurate forecast of anomalous behavior on the grid side ensures safe and dependable grid operation such that shutdown or failure probability is minimized to a greater extent by the results. Additional information gleaned from historical data will prove useful to equipment manufacturers in the future, providing a solution to this problem.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e141180
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modern methods in the field of machine modelling and simulation as a research and practical issue related to Industry 4.0
Autorzy:
Rojek, Izabela
Macko, Marek
Mikołajewski, Dariusz
Sága, Milan
Burczyński, Tadeusz
Powiązania:
https://bibliotekanauki.pl/articles/2090720.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Industry 4.0
Internet of Things
artificial intelligence
models
AI
simulation
IoT
Przemysł 4.0
czwarta rewolucja przemysłowa
internet rzeczy
internet przedmiotów
sztuczna inteligencja
modele
symulacja
Opis:
Artificial intelligence (AI) is changing many areas of technology in the public and private spheres, including the economy. This report reviews issues related to machine modelling and simulations concerning further development of mechanical devices and their control systems as part of novel projects under the Industry 4.0 paradigm. The challenges faced by the industry have generated novel technologies used in the construction of dynamic, intelligent, flexible and open applications, capable of working in real time environments. Thus, in an Industry 4.0 environment, the data generated by sensor networks requires AI/CI to apply close-to-real-time data analysis techniques. In this way industry can face both fresh opportunities and challenges, including predictive analysis using computer tools capable of detecting patterns in the data based on the same rules that can be used to formulate the prediction.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; e136717, 1--12
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Environmental analysis of a product manufactured with the use of an additive technology – AI-based vs. traditional approaches
Autorzy:
Dostatni, Ewa
Dudkowiak, Anna
Rojek, Izabela
Mikołajewski, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/2204511.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
additive manufacturing
AM
eco-design
life cycle assessment
LCA
artificial intelligence
AI
neural networks model
produkcja dodatkowa
zielony design
szacowanie cyklu życia
sztuczna inteligencja
model sieci neuronowej
Opis:
This paper attempts to conduct a comparative life cycle environmental analysis of alternative versions of a product that was manufactured with the use of additive technologies. The aim of the paper was to compare the environmental assessment of an additive-manufactured product using two approaches: a traditional one, based on the use of SimaPro software, and the authors’ own concept of a newly developed artificial intelligence (AI) based approach. The structure of the product was identical and the research experiments consisted in changing the materials used in additive manufacturing (from polylactic acid (PLA) to acrylonitrile butadiene styrene (ABS)). The effects of these changes on the environmental factors were observed and a direct comparison of the effects in the different factors was made. SimaPro software with implemented databases was used for the analysis. Missing information on the environmental impact of additive manufacturing of PLA and ABS parts was taken from the literature for the purpose of the study. The novelty of the work lies in the results of a developing concurrent approach based on AI. The results showed that the artificial intelligence approach can be an effective way to analyze life cycle assessment (LCA) even in such complex cases as a 3D printed medical exoskeleton. This approach, which is becoming increasingly useful as the complexity of manufactured products increases, will be developed in future studies.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 1; art. no. e144478
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Solar chargers based on new dye-based photovoltaic modules and new supercapacitors
Autorzy:
Plebankiewicz, Ireneusz
Bogdanowicz, Krzysztof. A.
Kwaśnicki, Paweł
Skunik-Nuckowska, Magdalena
Rączka, Patryk M.
Kulesza, Paweł
Iwan, Agnieszka
Przybył, Wojciech
Powiązania:
https://bibliotekanauki.pl/articles/27311422.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
dye-sensitized solar cell
supercapacitor
redox-active electrolyte
current source
energy storage system
Artificial Intelligence
superkondensator
elektrolit o działaniu redoks
system magazynowania energii
sztuczna inteligencja
barwnikowe ogniwo słoneczne
aktywne źródło
Opis:
Electricity storage is one of the best-known methods of balancing the energy supply and demand at a given moment. The article presents an innovative solution for the construction of an electric energy storage device obtained from an innovative photovoltaic panel made of new dye-based photovoltaic modules and newly developed supercapacitors – which can be used as an emergency power source. In the paper, for the first time, we focused on the successful paring of new dye-sensitized solar cell (DSSC) with novel supercapacitors. In the first step, a microprocessor stand was constructed using Artificial Intelligence algorithms to control the parameters of the environment, as well as the solar charger composed of six DSSC cells with the dimensions of 100_100 mm and 126 CR2032 coin cells with a total capacitance of 60 F containing redox-active aqueous electrolyte. It was proven that the solar charger store enough energy to power, i.e. SOS transmitter or igniters, using a 5 V signal.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 4; art. no. e146452
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Coherent structures and flow control: genesis and prospect
Autorzy:
Gad-El-Hak, M.
Powiązania:
https://bibliotekanauki.pl/articles/201471.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
smart wings
coherent structures
reactive flow control
adaptive control
machine-learning control
futuristic control systems
microsensors
microactuators
artificial intelligence
turbulent shear flows
history of flow control
history of coherent structures
inteligentne skrzydła
kontrola adaptacyjna
mikroczujniki
sztuczna inteligencja
Opis:
The genesis of both coherent structures and reactive flow control strategies is explored. Futuristic control systems that utilize microsensors and microactuators together with artificial intelligence to target specific coherent structures in a transitional or turbulent flow are considered. Of possible interest to the readers of this journal is the concept of smart wings, to be briefly discussed early in the article.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 3; 411-444
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-11 z 11

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