Chao Li¹, Fan Li^1,2, Wei Du³, Lihua Yin^1,*, Bin Wang⁴, Chonghua Wang⁵, Tianjie Luo¹

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3383-3397, 2021, DOI:10.32604/cmc.2021.020765

Abstract Material identification is a technology that can help to identify the type of target material. Existing approaches depend on expensive instruments, complicated pre-treatments and professional users. It is difficult to find a substantial yet effective material identification method to meet the daily use demands. In this paper, we introduce a Wi-Fi-signal based material identification approach by measuring the amplitude ratio and phase difference as the key features in the material classifier, which can significantly reduce the cost and guarantee a high level accuracy. In practical measurement of Wi-Fi based material identification, these two features are commonly interrupted by the software/hardware… More >

P. Vinayagam^1,*, P. Anandan², N. Kumaratharan³

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 869-879, 2021, DOI:10.32604/iasc.2021.016761

Abstract Recent advances in the development of image denoising applications for eliminating the various sources of noise in digital images have employed hardware platforms based on field programmable gate arrays for attaining speed and efficiency, which are essential factors in real-time applications. However, image denoising providing for maximum denoising performance, speed, and efficiency on these platforms is subject to constant innovation. To this end, the present work proposes a high-throughput fixed-point adaptive edge noise filter architecture to denoise digital images with additive white Gaussian noise in realtime using a nonlinear modified pixel-likeness weighted-frame technique. The proposed architecture works in two stages.… More >

Simy Mary Kurian¹, Sujitha Juliet Devaraj^1,*, Vinodh P. Vijayan²

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2093-2109, 2021, DOI:10.32604/cmc.2021.018090

Abstract Magnetic resonance imaging (MRI) is an essential tool for detecting brain tumours. However, identification of brain tumours in the early stages is a very complex task since MRI images are susceptible to noise and other environmental obstructions. In order to overcome these problems, a Gamma MAP denoised Strömberg wavelet segmentation based on a maximum entropy classifier (GMDSWS-MEC) model is developed for efficient tumour detection with high accuracy and low time consumption. The GMDSWS-MEC model performs three steps, namely pre-processing, segmentation, and classification. Within the GMDSWS-MEC model, the Gamma MAP filter performs the pre-processing task and achieves a significant increase in… More >

S. Narayan^1,*, M. U. Kaisan², Shitu Abubakar², Faisal O. Mahroogi³, Vipul Gupta⁴

Sound & Vibration, Vol.55, No.3, pp. 221-234, 2021, DOI:10.32604/sv.2021.016539

Abstract The health monitoring has been studied to ensure integrity of design of engine structure by detection, quantification, and prediction of damages. Early detection of faults may allow the downtime of maintenance to be rescheduled, thus preventing sudden shutdown of machines. In cylinder pressure developed, vibrations and noise emissions data provide a rich source of information about condition of engines. Monitoring of vibrations and noise emissions are novel non-intrusive methodologies for which positioning of various transducers are important issue. The presented work shows applicability of these diagnosis methodologies adopted in case of diesel engines. The effects of changing various fuel injection… More >

Guanpeng Li¹, Lihui Sun², Zhaoyang Wang¹, Chunguo An¹, Chang Guo^3,*, Shen Cheng³, Ming Gao^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.5, pp. 989-1001, 2021, DOI:10.32604/fdmp.2021.016507

Abstract Centrifugal pumps are widely used in engineering for a variety of applications. A known drawback of these devices is the high-level noise generated during operations, which can affect their stability and adversely influence the entire working environment. By combining the Powell vortex sound theory, numerical simulations and experimental measurements, this research explores the trends of variation and the corresponding underlying mechanisms for the flow-induced noise at various locations and under different operating conditions. It is shown that the total sound source intensity (TSSI) and total sound pressure level (TSPL) in the impeller, in the region between the inlet to the… More >

Radek Martinek¹, Rene Jaros¹, Jan Baros¹, Lukas Danys¹, Aleksandra Kawala-Sterniuk², Jan Nedoma^3,*, Zdenek Machacek¹, Jiri Koziorek¹

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1073-1096, 2021, DOI:10.32604/cmc.2021.017568

Abstract This paper discusses the reduction of background noise in an industrial environment to extend human-machine-interaction. In the Industry 4.0 era, the mass development of voice control (speech recognition) in various industrial applications is possible, especially as related to augmented reality (such as hands-free control via voice commands). As Industry 4.0 relies heavily on radiofrequency technologies, some brief insight into this problem is provided, including the Internet of things (IoT) and 5G deployment. This study was carried out in cooperation with the industrial partner Brose CZ spol. s.r.o., where sound recordings were made to produce a dataset. The experimental environment comprised… More >

Memoona Malik^*, Iftikhar Azim, Amir Hanif Dar, Sohail Asghar

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 165-182, 2021, DOI:10.32604/iasc.2021.017437

Abstract Despeckling of SAR imagery is a crucial step prior to their automated interpretation as information extraction from noisy images is a challenging task. Though a huge despeckling literature exists in this regard, there is still a room for improvement in existing techniques. The contemporary despeckling techniques adversely affect image edges during the noise reduction process and are thus responsible for losing the significant image features. Therefore, to preserve important features during the speckle reduction process, a two phase hybrid despeckling filter is proposed in this study. The first phase of the hybrid filter focuses on edge preservation by employing a… More >

Pushpendra Kumar^1,2,*, Ramjeevan Singh Thakur³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3513-3529, 2021, DOI:10.32604/cmc.2021.016957

Abstract The aim of this research is to develop a mechanism to help medical practitioners predict and diagnose liver disease. Several systems have been proposed to help medical experts by diminishing error and increasing accuracy in diagnosing and predicting diseases. Among many existing methods, a few have considered the class imbalance issues of liver disorder datasets. As all the samples of liver disorder datasets are not useful, they do not contribute to learning about classifiers. A few samples might be redundant, which can increase the computational cost and affect the performance of the classifier. In this paper, a model has been… More >

Song Gao^1,*, Xin Jin¹, Qiaohong Liu²

FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.3, pp. 511-529, 2021, DOI:10.32604/fdmp.2021.012741

Abstract The signals generated by electromagnetic flow sensors used for slurry fluids are often affected by noise interference produced by interaction with the slurry itself. In this study, the power spectrum characteristics of the signal are studied, and an attempt is made to determine the relationship between the characteristics of the related noise and the velocity and concentration of the slurry fluid. Dedicated experiments are conducted and the related power spectrum curve is obtained processing the signal measured by the sensor with Matlab. Numerical simulations are also carried out in the frame of an Eulerian approach in order get additional insights… More >

Sajad Zare¹, Rasoul Hemmatjo², Hossein ElahiShirvan^3,*, Ashkan Jafari Malekabad³, Mansour Ziaei⁴, Farshad Nadri⁵

Sound & Vibration, Vol.55, No.2, pp. 163-171, 2021, DOI:10.32604/sv.2021.09114

Abstract Noise pollution is one of the common physical harmful factors in many work environments. The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of the Razavi Khorasan Paste manufacture using Surfer V.14 and Noise at work V.5.0. This cross-sectional, descriptive study is analytical that was conducted in 2018 in the Paste factory that contains Canister, production and Brewing unit. Following ISO 9612:2009, Casella Cel-320 was used to measure personal sound pressure level, while CEL-450 sound level meter (manufactured by Casella-Cel, the UK) was employed to assess environmental sound pressure level.… More >