Wyniki wyszukiwania - BazTech

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Wysoko wydajny system natryskiwania na zimno do reperowania elementów ze stali nierdzewnej

Jemielniak Krzysztof

Mechanik

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2021

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R. 94, nr 5-6

24

PL

Natryskiwanie na zimno (cold spray – CS) jest stosowane do wzmacniania strukturalnego, powlekania i naprawy elementów metalowych. Osadzanie następuje w wyniku uderzania małych cząstek, przyspieszanych do prędkości ponaddźwiękowych, w powierzchnię osadzania. Zastosowanie CS pod wysokim ciśnieniem – koniecznym w przypadku materiałów ze stali nierdzewnej – jest in situ ryzykowne i nieopłacalne. Tu opisano nowatorską metodę osadzania CS z wykorzystaniem kompaktowego i łatwego w transporcie urządzenia.

2

Modified Block Sparse Bayesian Learning-Based Compressive Sensing Scheme For EEG Signals

Upadhyaya Vivek, Salim Mohammad

International Journal of Electronics and Telecommunications

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2021

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Vol. 67, No. 3

331--336

EN

Advancement in medical technology creates some issues related to data transmission as well as storage. In real-time processing, it is too tedious to limit the flow of data as it may reduce the meaningful information too. So, an efficient technique is required to compress the data. This problem arises in Magnetic Resonance Imaging (MRI), Electrocardiogram (ECG), Electroencephalogram (EEG), and other medical signal processing domains. In this paper, we demonstrate Block Sparse Bayesian Learning (BSBL) based compressive sensing technique on an Electroencephalogram (EEG) signal. The efficiency of the algorithm is described using the Mean Square Error (MSE) and Structural Similarity Index Measure (SSIM) value. Apart from this analysis we also use different combinations of sensing matrices too, to demonstrate the effect of sensing matrices on MSE and SSIM value. And here we got that the exponential and chi-square random matrices as a sensing matrix are showing a significant change in the value of MSE and SSIM. So, in real-time body sensor networks, this scheme will contribute a significant reduction in power requirement due to its data compression ability as well as it will reduce the cost and the size of the device used for real-time monitoring.

3

Damped Zero-Pseudorandom Noise OFDM Systems

Esmaiel H.

International Journal of Electronics and Telecommunications

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2018

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Vol. 64, No. 4

433--438

EN

This paper proposed a new OFDM scheme called damped zero-pseudorandom noise orthogonal frequency division multiplexing (DZPN-OFDM) scheme. In the proposed scheme, ZPN-OFDM non-zero part is damped to reduce its energy, thus the mutual interference power in-between the data and training blocks with conservative the pseudo-noise conventional properties required for channel estimation or synchronization. The motivation of this paper is the OFDM long guard interval working in wide dispersion channels, whereas a significant energy is wasted when the conventional ZPN-OFDM is used as well as the BER performance is also degraded. Moreover, the proposed scheme doesn’t duplicate the guard interval to solve the ZPN-OFDM spectrum efficiency loss problem. Both detailed performance analysis and simulation results show that the proposed DZPNOFDM scheme can, indeed, offer significant bit error rate, spectrum efficiency and energy efficiency improvement.

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A comparison of Differential Evolution, Particle Swarm Optimization, Artificial Bee Colony and Cuckoo Search for Multilevel thresholding

Kumar S., Pant M., Kumar R., Amiya A.

Computer Methods in Materials Science

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2013

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Vol. 13, No. 1

135--140

EN

The present study deals with the image segmentation of waste wood material using some popular nature inspired metaheuristics like: Differential Evolution (DE), Particle Swarm Optimization(PSO) Artificial bee Colony (ABC) and Cuckoo Search (CS). Otsu’s between class-variance and Kapur’s maximum entropy techniques are used as fitness functions. Experiments have been performed on various images and numerical results are compared. It is observed that in some cases Otsu method is giving the same performance as DE, PSO, ABC and CS. But when class size increases DE shows better results in comparison to others.

PL

Przedstawione badania dotyczą segmentacji obrazów odpadów drewna przy użyciu popularnych algorytmów inspirowanych naturą, takich jak: metoda ewolucji różnicowej (DE), metoda roju cząstek (PSO), algorytmu pszczelego (ABC) oraz algorytmu kukułki (CS). Jako funkcję celu wykorzystano wariancję międzyklasową Otsu oraz zasadę maksymalnej entropii. Porównując wyniki otrzymane dla różnych obrazów, zaobserwowano, że w niektórych przypadkach metoda Otsu wykazuje taką samą wydajność jak DE, PSO, ABC i CS. Jednak przy wzroście liczby klas wyniki otrzymane metodą DE są lepsze niż otrzymane pozostałymi metodami.