Journals / SV / Vol.54, No.1

  • ARTICLE

    Implementation of a Biometric Interface in Voice Controlled Wheelchairs

    Lamia Bouafif1, Noureddine Ellouze2,*
    Sound & Vibration, Vol.54, No.1, pp. 1-15, 2020, DOI:10.32604/sv.2020.08665
    Abstract In order to assist physically handicapped persons in their movements, we developed an embedded isolated word speech recognition system (ASR) applied to voice control of smart wheelchairs. However, in spite of the existence in the industrial market of several kinds of electric wheelchairs, the problem remains the need to manually control this device by hand via joystick; which limits their use especially by people with severe disabilities. Thus, a significant number of disabled people cannot use a standard electric wheelchair or drive it with difficulty. The proposed solution is to use the voice to control and drive the wheelchair instead… More >

  • ARTICLE

    Presenting a Signal to Noise Ratio Model Based on the Combined Effect of Sound Pressure Level/frequency, Exposure Time and Oral Potassium: Experimental Study in Rats

    Parvin Nassiri1, Sajad Zare2,*, Mohammad Reza Monazzam1, Akram Pourbakht3, Rasoul Hemmatjo4, Hossein ElahiShirvan2
    Sound & Vibration, Vol.54, No.1, pp. 17-25, 2020, DOI:10.32604/sv.2020.08395
    Abstract Exposure to noise can lead to anatomical, nonauditory, and auditory impacts. The auditory influence of noise exposure is manifested in the form of Noise-induced hearing loss (NIHL). The current study aimed at present a signal to noise ratio model of otoacoustic emission of rats’ ears in the light of the combined effect of sound pressure level, sound frequency, exposure time, and potassium concentration of the used water. In total, 36 adult male rates, whose age varied from 3 to 4 months and had a weight of 200 ± 50 g, were randomly divided into 12 groups, with each group consisting… More >

  • ARTICLE

    Assessment of Traffic Noise Pollution in Burla Town, India; An Inclusive Annoyance Study

    A. K. Sahu1, M. Pradhan1, C. R. Mohanty2, P. K. Pradhan1,*
    Sound & Vibration, Vol.54, No.1, pp. 27-42, 2020, DOI:10.32604/sv.2020.08586
    Abstract Noise pollution is one of the major public health problems in urban areas throughout the world. Noise is unwanted sound which produces undesirable problems in day to day life of human being (e.g., physiological and psychological problems). Rapid increase of the industrialization, urbanization, infrastructure, volume of motor vehicles, and increase in the road networks brought noise pollution to the highest level of disaster in a current situation. In urban areas, road traffic noise plays commanding role among all noise sources and affects the exposed inhabitants. The present work is done to evaluate and assess the traffic noise and its effects… More >

  • ARTICLE

    The Acoustic Performance of 3D Printed Multiple Jet Nozzles with Different Configurations

    Ali Safari Variani1, Ali Dastamoz1, Sajad Zare2, Ahmad Nikpey1, Saeid Ahmadi1,*
    Sound & Vibration, Vol.54, No.1, pp. 43-55, 2020, DOI:10.32604/sv.2020.08636
    Abstract This work investigated multiple jet nozzles with various geometrical shape, number of exits, and material on reducing noise radiated from jet flows. Nozzles are categorized in two groups with few and many exit numbers, each with various exit shapes, slot and circular, and geometry. Firstly, nozzles are designed and then fabricated by a 3D printer, Form Labs, Form2USA, with polymeric resin. Also, the nozzle with the most noise reduction made of stainless steel. Noise and air thrust were measured at three air pressure gauges, 3, 5, 7 BAR and directions from nozzle apex, 30°, 90°, 135°. Nozzles with slot exit… More >

  • ARTICLE

    Sound Signal Based Fault Classification System in Motorcycles Using Hybrid Feature Sets and Extreme Learning Machine Classifiers

    T. Jayasree1,*, R. Prem Ananth2
    Sound & Vibration, Vol.54, No.1, pp. 57-74, 2020, DOI:10.32604/sv.2020.08573
    Abstract Vehicles generate dissimilar sound patterns under different working environments. These generated sound patterns signify the condition of the engines, which in turn is used for diagnosing various faults. In this paper, the sound signals produced by motorcycles are analyzed to locate various faults. The important attributes are extracted from the generated sound signals based on time, frequency and wavelet domains which clearly describe the statistical behavior of the signals. Further, various types of faults are classified using the Extreme Learning Machine (ELM) classifier from the extracted features. Moreover, the improved classification performance is obtained by the combination of feature sets… More >

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