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  • Open Access


    Obtaining Crisp Priorities for Triangular and Trapezoidal Fuzzy Judgments

    Raman Kumar Goyal1, Jaskirat Singh1, Nidhi Kalra1, Anshu Parashar1,*, Gagan Singla2, Sakshi Kaushal2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 157-170, 2022, DOI:10.32604/csse.2022.018962

    Abstract This paper proposes anoptimal fuzzy-based model for obtaining crisp priorities for Fuzzy-AHP comparison matrices. Crisp judgments cannot be given for real-life situations, as most of these include some level of fuzziness and complexity. In these situations, judgments are represented by the set of fuzzy numbers. Most of the fuzzy optimization models derive crisp priorities for judgments represented with Triangular Fuzzy Numbers (TFNs) only. They do not work for other types of Triangular Shaped Fuzzy Numbers (TSFNs) and Trapezoidal Fuzzy Numbers (TrFNs). To overcome this problem, a sum of squared error (SSE) based optimization model is proposed. Unlike some other methods,… More >

  • Open Access


    Yellow Vein Mosaic Disease in Okra (Abelmoschus esculentus L.): An Overview on Causal Agent, Vector and Management

    Mustansar Mubeen1, Yasir Iftikhar1,*, Aqleem Abbas2, Mazhar Abbas3, Muhammad Zafar-ul-Hye4, Ashara Sajid1, Faheema Bakhtawar1

    Phyton-International Journal of Experimental Botany, Vol.90, No.6, pp. 1573-1587, 2021, DOI:10.32604/phyton.2021.016664

    Abstract Okra (Abelmoschus esculentus L.) belongs to the Malvaceae family and is one of the most essential and popular vegetables globally. It is rich in proteins, carbohydrates, and vitamins. Abiotic and biotic factors threaten okra productivity. Okra yellow vein mosaic disease (OYVMD) is the most destructive disease of okra. The causal agent, [(i.e., Okra yellow vein mosaic virus (OYVMV)] of this disease belongs to the family Geminiviridae and genus Begomovirus. OYVMV is a monopartite with additional ssDNA molecule. This virus has two components DNA-A for protein coding and DNA-B for symptoms induction. Whitefly transmits OYVMV in persistent manner. Characteristic symptoms of… More >

  • Open Access


    Position Vectors Based Efficient Indoor Positioning System

    Ayesha Javed1, Mir Yasir Umair1,*, Alina Mirza1, Abdul Wakeel1, Fazli Subhan2, Wazir Zada Khan3

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1781-1799, 2021, DOI:10.32604/cmc.2021.015229

    Abstract With the advent and advancements in the wireless technologies, Wi-Fi fingerprinting-based Indoor Positioning System (IPS) has become one of the most promising solutions for localization in indoor environments. Unlike the outdoor environment, the lack of line-of-sight propagation in an indoor environment keeps the interest of the researchers to develop efficient and precise positioning systems that can later be incorporated in numerous applications involving Internet of Things (IoTs) and green computing. In this paper, we have proposed a technique that combines the capabilities of multiple algorithms to overcome the complexities experienced indoors. Initially, in the database development phase, Motley Kennan propagation… More >

  • Open Access


    Mobile Robots Navigation Modeling in Known 2D Environment Based on Petri Nets

    S. Bartkeviciusa, O. Fiodorovab, A. Knysc, A. Derviniened, G. Dervinisc, V. Raudonisc, A. Lipnickasc, V. Baranauskasc, K. Sarkauskasc, L. Balaseviciusc

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 241-248, 2018, DOI:10.1080/10798587.2016.1264695

    Abstract The paper deals with supervised robot navigation in known environments. The navigation task is divided into two parts, where one part of the navigation is done by the supervisor system i.e. the system sets the vector marks on the salient edges of the virtual environment map and guides the robot to reach these marks. Mobile robots have to perform a specific task according to the given paths and solve the local obstacles avoidance individually. The salient point’s detection, vector mark estimation and optimal path calculation are done on the supervisor computer using colored Petri nets. The proposed approach was extended… More >

  • Open Access


    Binaural Speech Separation Algorithm Based on Long and Short Time Memory Networks

    Lin Zhou1, *, Siyuan Lu1, Qiuyue Zhong1, Ying Chen1, 2, Yibin Tang3, Yan Zhou3

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1373-1386, 2020, DOI:10.32604/cmc.2020.010182

    Abstract Speaker separation in complex acoustic environment is one of challenging tasks in speech separation. In practice, speakers are very often unmoving or moving slowly in normal communication. In this case, the spatial features among the consecutive speech frames become highly correlated such that it is helpful for speaker separation by providing additional spatial information. To fully exploit this information, we design a separation system on Recurrent Neural Network (RNN) with long short-term memory (LSTM) which effectively learns the temporal dynamics of spatial features. In detail, a LSTM-based speaker separation algorithm is proposed to extract the spatial features in each time-frequency… More >

  • Open Access


    A Coarse Alignment Based on the Sliding Fixed-Interval Least Squares Denoising Method

    Yongyun Zhu1, Tao Zhang1,*, Mohan Li2, Di Wang1, Shaoen Wu3

    CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1305-1321, 2019, DOI:10.32604/cmc.2019.06406

    Abstract The observation vectors in traditional coarse alignment contain random noise caused by the errors of inertial instruments, which will slow down the convergence rate. To solve the above problem, a real-time noise reduction method, sliding fixed-interval least squares (SFI-LS), is devised to depress the noise in the observation vectors. In this paper, the least square method, improved by a sliding fixed-interval approach, is applied for the real-time noise reduction. In order to achieve a better-performed coarse alignment, the proposed method is utilized to de-noise the random noise in observation vectors. First, the principles of proposed SFI-LS algorithm and coarse alignment… More >

  • Open Access


    A Hybrid Approach of TLBO and EBPNN for Crop Yield Prediction Using Spatial Feature Vectors

    Preeti Tiwari1, *, Piyush Shukla1

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 45-58, 2019, DOI:10.32604/jai.2019.04444

    Abstract The prediction of crop yield is one of the important factor and also challenging, to predict the future crop yield based on various criteria’s. Many advanced technologies are incorporated in the agricultural processes, which enhances the crop yield production efficiency. The process of predicting the crop yield can be done by taking agriculture data, which helps to analyze and make important decisions before and during cultivation. This paper focuses on the prediction of crop yield, where two models of machine learning are developed for this work. One is Modified Convolutional Neural Network (MCNN), and the other model is TLBO (Teacher… More >

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