Jalal Sadoon Hameed Al-bayati^1,*, Burak Berk Üstündağ²

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1479-1496, 2021, DOI:10.32604/cmc.2020.013329 - 26 November 2020

Abstract The Fused Modified Grasshopper Optimization Algorithm has been proposed, which selects the most specific feature sets from images of the disease of plant leaves. The Proposed algorithm ensures the detection of diseases during the early stages of the diagnosis of leaf disease by farmers and, finally, the crop needed to be controlled by farmers to ensure the survival and protection of plants. In this study, a novel approach has been suggested based on the standard optimization algorithm for grasshopper and the selection of features. Leaf conditions in plants are a major factor in reducing crop… More >

Inzamam Mashood Nasir¹, Asima Bibi², Jamal Hussain Shah², Muhammad Attique Khan¹, Muhammad Sharif², Khalid Iqbal³, Yunyoung Nam⁴, Seifedine Kadry^5,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1949-1962, 2021, DOI:10.32604/cmc.2020.012945 - 26 November 2020

Abstract Agriculture is essential for the economy and plant disease must be minimized. Early recognition of problems is important, but the manual inspection is slow, error-prone, and has high manpower and time requirements. Artificial intelligence can be used to extract fruit color, shape, or texture data, thus aiding the detection of infections. Recently, the convolutional neural network (CNN) techniques show a massive success for image classification tasks. CNN extracts more detailed features and can work efficiently with large datasets. In this work, we used a combined deep neural network and contour feature-based approach to classify fruits… More >

Yinjie Wang, Yongxia Zhang, Qingquan Liu, Liangqin Liu, Suzhen Huang, Haiyan Yuan^*

Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 277-290, 2021, DOI:10.32604/phyton.2020.011545 - 20 November 2020

Abstract Quantitative real-time PCR (qPCR) is an effective and widely used method to analyze expression patterns of target genes. Selection of stable reference genes is a prerequisite for accurate normalization of target gene expression by qRT-PCR. In Iris germanica L., no studies have yet been published regarding the evaluation of potential reference genes. In this study, nine candidate reference genes were assessed at different flower developmental stages and in different tissues by four different algorithms (GeNorm, NormFinder, BestKeeper, and RefFinder). The results revealed that ACT11 (Actin 11) and EF1α (Elongation factor 1 alpha) were the most stable reference… More >

Riaz Ahmad¹, Muhammad Akbar Anjum^1,*, Safina Naz¹, Rashad Mukhtar Balal²

Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 17-34, 2021, DOI:10.32604/phyton.2020.011680 - 20 November 2020

Abstract Selection and use of molecular markers for evaluation of DNA polymorphism in plants are couple of the most important approaches in the field of molecular genetics. The assessment of genetic diversity using morphological markers is not sufficient due to little differentiating traits among the species, genera or their individuals. Morphological markers are not only highly influenced by environmental factors but skilled assessment is also prerequisite to find the variations in plant genetic resources. Therefore, molecular markers are considered as efficient tools for detailed DNA based characterization of fruit crops. Molecular markers provide new directions to More >

Dac-Nhuong Le^1,2,3,*, Gia Nhu Nguyen^2,4, Harish Garg⁵, Quyet-Thang Huynh⁶, Trinh Ngoc Bao⁷, Nguyen Ngoc Tuan⁸

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 993-1010, 2021, DOI:10.32604/cmc.2020.012464 - 30 October 2020

Abstract This paper presents a Game-theoretic optimization via Parallel MinMax Ant System (PMMAS) algorithm is used in practice to determine the Nash equilibrium value to resolve the confusion in choosing appropriate bidders of multi-round procurement problem in software project management. To this end, we introduce an approach that proposes: (i) A Game-theoretic model of multiround procurement problem (ii) A Nash equilibrium strategy corresponds to multi-round strategy bid (iii) An application of PSO for the determination of global Nash equilibrium. The balance point in Nash Equilibrium can help to maintain a sustainable structure not only in terms… More >

Sangmi Moon¹, Hyeonsung Kim¹, Seng-Phil Hong², Mingoo Kang³, Intae Hwang^1,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 59-70, 2021, DOI:10.32604/cmc.2020.013132 - 30 October 2020

Abstract Millimeter-wave communications are suitable for application to massive multiple-input multiple-output systems in order to satisfy the ever-growing data traffic demands of the next-generation wireless communication. However, their practical deployment is hindered by the high cost of complex hardware, such as radio frequency (RF) chains. To this end, operation in the beamspace domain, through beam selection, is a viable solution. Generally, the conventional beam selection schemes focus on the feedback and exhaustive search techniques. In addition, since the same beam in the beamspace may be assigned to a different user, conventional beam selection schemes suffer serious… More >

Xingxing Cao¹, Liming Jiang^1,*, Xiaoliang Wang¹, Frank Jiang²

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 187-197, 2020, DOI:10.32604/jihpp.2020.016243 - 07 January 2021

Abstract Due to the lack of consideration of movement behavior information other than time and location perception in current location prediction methods, the movement characteristics of trajectory data cannot be well expressed, which in turn affects the accuracy of the prediction results. First, a new trajectory data expression method by associating the movement behavior information is given. The pre-association method is used to model the movement behavior information according to the individual movement behavior features and the group movement behavior features extracted from the trajectory sequence and the region. The movement behavior features based on pre-association More >

Weipeng Cao¹, Zhongwu Xie¹, Xiaofei Zhou², Zhiwu Xu¹, Cong Zhou¹, Georgios Theodoropoulos³, Qiang Wang^3,*

Journal on Artificial Intelligence, Vol.2, No.4, pp. 177-187, 2020, DOI:10.32604/jai.2020.014829 - 31 December 2020

Abstract Software verification is a key technique to ensure the correctness of software. Although numerous verification algorithms and tools have been developed in the past decades, it is still a great challenge for engineers to accurately and quickly choose the appropriate verification techniques for the software at hand. In this work, we propose a general learning framework for the intelligent selection of software verification algorithms, and instantiate the framework with two state-of-the-art learning algorithms: Broad learning (BL) and deep learning (DL). The experimental evaluation shows that the training efficiency of the BL-based model is much higher More >

M. A. Rahim Khan^*, Manoj Kumar Jain

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1359-1373, 2020, DOI:10.32604/iasc.2020.013849 - 24 December 2020

Abstract Repacked mobile applications and obfuscation attacks constitute a significant threat to the Android technological ecosystem. A novel method using the Constant Key Point Selection and Limited Binary Pattern Feature (CKPS: LBP) extraction-based Hashing has been proposed to identify repacked Android applications in previous works. Although the approach was efficient in detecting the repacked Android apps, it was not suitable for detecting obfuscation attacks. Additionally, the time complexity needed improvement. This paper presents an optimization technique using Scalable Bivariant Feature Transformation extract optimum feature-points extraction, and the Harris method applied for optimized image hashing. The experiments More >

Yan Zhou, Lili Pan^*, Rongyu Chen, Weizhi Shao

Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 77-86, 2020, DOI:10.32604/jihpp.2020.010486 - 11 November 2020

Abstract In large-scale image retrieval, deep features extracted by Convolutional Neural Network (CNN) can effectively express more image information than those extracted by traditional manual methods. However, the deep feature dimensions obtained by Deep Convolutional Neural Network (DCNN) are too high and redundant, which leads to low retrieval efficiency. We propose a novel image retrieval method, which combines deep features selection with improved DCNN and hash transform based on high-dimension features reduction to gain lowdimension deep features and realizes efficient image retrieval. Firstly, the improved network is based on the existing deep model to build a… More >