Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (182)
  • Open Access

    ARTICLE

    Noise Control of a Domestic Refrigerator Using a Natural Material Based Composite

    A. R. Mohanty1,*, S. Fatima2

    Sound & Vibration, Vol.54, No.4, pp. 247-256, 2020, DOI:10.32604/sv.2020.011011

    Abstract This paper studies the acoustics of a frost free three door domestic refrigerator. Then, as a case study, the radiated noise reduction in the refrigerator using a natural material base composite is presented. Composites manufactured out of Jute, which is a plant fiber abundantly and cheaply available in India and Bangladesh are used in the noise reduction in the refrigerator. Mostly in this work, composites made out of felts of jute were used as barriers for noise control of the refrigerator. Measured acoustical, thermal and physical properties of various jute composites are reported. Noise sources in the refrigerator were characterized… More >

  • Open Access

    ARTICLE

    Detection of the Spectrum Hole from N-number of Primary Users Using the Gencluster Algorithm

    U. Venkateshkumar1,*, S. Ramakrishnan2

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 817-830, 2020, DOI:10.32604/iasc.2020.010116

    Abstract A hybrid form of the genetic algorithm and the modified K-Means cluster algorithm forms as a Gencluster to detect a spectrum hole among n-number of primary users (PUs) is present in the cooperative spectrum sensing model. The fusion center (FC), applies the genetic algorithm to identify the best chromosome, which contains many PUs cluster centers and by applying the modified K-Means cluster algorithm identifies the cluster with the PU vacant spectrum showing high accuracy, and maximum probability of detection with minimum false alarm rates are achieved. The graphical representation of the performance metric of the system model shows 95% accuracy… More >

  • Open Access

    ARTICLE

    A Novel Edge Computing Based Area Navigation Scheme

    Jianzhong Qi1, 2, *, Qingping Song3, Jim Feng4

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2385-2396, 2020, DOI:10.32604/cmc.2020.011651

    Abstract The area navigation system, discussed in this paper, is composed of ground responders and a navigation terminal and can position a high-velocity aircraft and measure its velocity. This navigation system is silent at ordinary times. It sends out a request signal when positioning is required for an aircraft, and then the ground responders send a signal for resolving the aircraft. Combining the direct sequence spread spectrum and frequency hopping, the concealed communication mode is used in the whole communication process, with short communication pulses as much as possible, so the system has strong concealment and anti-interference characteristics. As the transmission… More >

  • Open Access

    ARTICLE

    Weighing and Prioritizing Noise Control Methods Using the Delphi Technique and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in an Iranian Tire Manufacturing Factory

    Mohammad Reza Ghotbi-Ravandi1, Davoud Hassanvand2, Sajad Zare3,*, Milad Beytollahi4

    Sound & Vibration, Vol.54, No.3, pp. 201-213, 2020, DOI:10.32604/sv.2020.08651

    Abstract Undoubtedly, noise has become a major hazardous issue in today’s industrial world, with a lot of people suffering from exposure to excessive noise in their work environments. This study was conducted to weigh and prioritize noise control methods in an Iranian tire manufacturing complex in Iran. The Delphi method and the Technique for Order Preference by Similarity and an Ideal Solution (TOPSIS) were utilized for this purpose. This cross-sectional, descriptive study was conducted in the baking hall of an Iranian tire manufacturing factory in 2016. To weigh and prioritize noise control methods, Analytic Hierarchy Process (AHP) and TOPSIS were applied.… More >

  • Open Access

    ARTICLE

    Cochlear Synaptopathy Following Noise Exposure in Guinea Pigs: Its Electrophysiological and Histological Assessments

    Parvane Mahdi1, Akram Pourbakht1,*, Vahid Pirhajati Mahabadi2, Alireza Karimi Yazdi3, Mahtab Rabbani Anari3, Mohammad Kamali4

    Sound & Vibration, Vol.54, No.3, pp. 163-177, 2020, DOI:10.32604/sv.2020.09880

    Abstract Exposure to high level of noise, may cause the permanent cochlear synaptic degeneration. In present study, a model of noise induced cochlear synaptopathy was established and the electrophysiological and histological metrics for its assessment was designed. 6 guinea pigs were subjected to a synaptopathic noise (octave band of 4 kHz at 104 dB SPL, for 2-h). The amplitude growth curve of Auditory Brainstem Response (ABR) wave-I and wave-III latency shift in presence of noise were calculated. These indexes were considered in pre-exposure, 1 day post exposure (1DPE), 1 week post exposure (1WPE) and 1 month post exposure (1MPE) to noise.… More >

  • Open Access

    ARTICLE

    Enhanced GPU-Based Anti-Noise Hybrid Edge Detection Method

    Sa’ed Abed, Mohammed H. Ali, Mohammad Al-Shayeji

    Computer Systems Science and Engineering, Vol.35, No.1, pp. 21-37, 2020, DOI:10.32604/csse.2020.35.021

    Abstract Today, there is a growing demand for computer vision and image processing in different areas and applications such as military surveillance, and biological and medical imaging. Edge detection is a vital image processing technique used as a pre-processing step in many computer vision algorithms. However, the presence of noise makes the edge detection task more challenging; therefore, an image restoration technique is needed to tackle this obstacle by presenting an adaptive solution. As the complexity of processing is rising due to recent high-definition technologies, the expanse of data attained by the image is increasing dramatically. Thus, increased processing power is… More >

  • Open Access

    ARTICLE

    Noise Cancellation Based on Voice Activity Detection Using Spectral Variation for Speech Recognition in Smart Home Devices

    Jeong-Sik Park1, Seok-Hoon Kim2,*

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 149-159, 2020, DOI:10.31209/2019.100000136

    Abstract Variety types of smart home devices have a main function of a human-machine interaction by speech recognition. Speech recognition system may be vulnerable to rapidly changing noises in home environments. This study proposes an efficient noise cancellation approach to eliminate the noises directly on the devices in real time. Firstly, we propose an advanced voice activity detection (VAD) technique to efficiently detect speech and non-speech regions on the basis of spectral property of speech signals. The VAD is then employed to enhance the conventional spectral subtraction method by steadily estimating noise signals in non-speech regions. On several experiments, our approach… More >

  • Open Access

    ARTICLE

    Mixed Noise Removal by Residual Learning of Deep CNN

    Kang Yang1, Jielin Jiang1,2,*, Zhaoqing Pan1,2

    Journal of New Media, Vol.2, No.1, pp. 1-10, 2020, DOI:10.32604/jnm.2020.09356

    Abstract Due to the huge difference of noise distribution, the result of a mixture of multiple noises becomes very complicated. Under normal circumstances, the most common type of mixed noise is to add impulse noise (IN) and then white Gaussian noise (AWGN). From the reduction of cascaded IN and AWGN to the latest sparse representation, a great deal of methods has been proposed to reduce this form of mixed noise. However, when the mixed noise is very strong, most methods often produce a lot of artifacts. In order to solve the above problems, we propose a method based on residual learning… More >

  • Open Access

    ARTICLE

    Statistical Analysis and Multimodal Classification on Noisy Eye Tracker and Application Log Data of Children with Autism and ADHD

    Mahiye Uluyagmur Ozturka, Ayse Rodopman Armanb, Gresa Carkaxhiu Bulutc, Onur Tugce Poyraz Findikb, Sultan Seval Yilmazd, Herdem Aslan Gencb, M. Yanki Yazgane,f, Umut Tekera, Zehra Cataltepea

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 891-905, 2018, DOI:10.31209/2018.100000058

    Abstract Emotion recognition behavior and performance may vary between people with major neurodevelopmental disorders such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and control groups. It is crucial to identify these differences for early diagnosis and individual treatment purposes. This study represents a methodology by using statistical data analysis and machine learning to provide help to psychiatrists and therapists on the diagnosis and individualized treatment of participants with ASD and ADHD. In this paper we propose an emotion recognition experiment environment and collect eye tracker fixation data together with the application log data (APL). In order to detect… More >

  • Open Access

    ARTICLE

    Improving Performance Prediction on Education Data with Noise and Class Imbalance

    Akram M. Radwana,b, Zehra Cataltepea,c

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 777-783, 2018, DOI:10.1080/10798587.2017.1337673

    Abstract This paper proposes to apply machine learning techniques to predict students’ performance on two real-world educational data-sets. The first data-set is used to predict the response of students with autism while they learn a specific task, whereas the second one is used to predict students’ failure at a secondary school. The two data-sets suffer from two major problems that can negatively impact the ability of classification models to predict the correct label; class imbalance and class noise. A series of experiments have been carried out to improve the quality of training data, and hence improve prediction results. In this paper,… More >

Displaying 121-130 on page 13 of 182. Per Page