K. K. Thyagharajan, G. Nirmala^*

Computer Systems Science and Engineering, Vol.41, No.1, pp. 357-371, 2022, DOI:10.32604/csse.2022.020258

Abstract In this paper, copy-move forgery in image is detected for single image with multiple manipulations such as blurring, noise addition, gray scale conversion, brightness modifications, rotation, Hu adjustment, color adjustment, contrast changes and JPEG Compression. However, traditional algorithms detect only copy-move attacks in image and never for different manipulation in single image. The proposed LLP (Laterally linked pixel) algorithm has two dimensional arrays and single layer is obtained through unit linking pulsed neural network for detection of copied region and kernel tricks is applied for detection of multiple manipulations in single forged image. LLP algorithm consists of two channels such… More >

Raman Kumar Goyal¹, Jaskirat Singh¹, Nidhi Kalra¹, Anshu Parashar^1,*, 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 >

Mustansar Mubeen¹, Yasir Iftikhar^1,*, 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 >

Ayesha Javed¹, Mir Yasir Umair^1,*, 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 >

S. Bartkevicius^a, O. Fiodorova^b, A. Knys^c, A. Derviniene^d, G. Dervinis^c, V. Raudonis^c, A. Lipnickas^c, V. Baranauskas^c, K. Sarkauskas^c, L. Balasevicius^c

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 >

Lin Zhou^{1, *}, Siyuan Lu¹, Qiuyue Zhong¹, Ying Chen^{1, 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 >

Yongyun Zhu¹, Tao Zhang^1,*, 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 >

Preeti Tiwari^{1, *}, 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 >