Kun Zhu¹, Nana Zhang¹, Qing Zhang², Shi Ying^{1, *}, Xu Wang³

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1467-1486, 2020, DOI:10.32604/cmc.2020.011415

Abstract Software defect prediction plays a very important role in software quality assurance, which aims to inspect as many potentially defect-prone software modules as possible. However, the performance of the prediction model is susceptible to high dimensionality of the dataset that contains irrelevant and redundant features. In addition, software metrics for software defect prediction are almost entirely traditional features compared to the deep semantic feature representation from deep learning techniques. To address these two issues, we propose the following two solutions in this paper: (1) We leverage a novel non-linear manifold learning method - SOINN Landmark Isomap (SLIsomap) to extract the… More >

Huiping Jiang^{1, *}, Zequn Wang¹, Rui Jiao¹, Shan Jiang²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1453-1465, 2020, DOI:10.32604/cmc.2020.011793

Abstract Emotion recognition systems are helpful in human–machine interactions and Intelligence Medical applications. Electroencephalogram (EEG) is closely related to the central nervous system activity of the brain. Compared with other signals, EEG is more closely associated with the emotional activity. It is essential to study emotion recognition based on EEG information. In the research of emotion recognition based on EEG, it is a common problem that the results of individual emotion classification vary greatly under the same scheme of emotion recognition, which affects the engineering application of emotion recognition. In order to improve the overall emotion recognition rate of the emotion… More >

Zhaoquan Gu¹, Yu Su¹, Chenwei Liu¹, Yinyu Lyu¹, Yunxiang Jian¹, Hao Li², Zhen Cao³, Le Wang^{1, *}

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1437-1452, 2020, DOI:10.32604/cmc.2020.011834

Abstract The license plate recognition system (LPRS) has been widely adopted in daily life due to its efficiency and high accuracy. Deep neural networks are commonly used in the LPRS to improve the recognition accuracy. However, researchers have found that deep neural networks have their own security problems that may lead to unexpected results. Specifically, they can be easily attacked by the adversarial examples that are generated by adding small perturbations to the original images, resulting in incorrect license plate recognition. There are some classic methods to generate adversarial examples, but they cannot be adopted on LPRS directly. In this paper,… More >

Min Long^{1, *}, Man Kong¹, Sai Long¹, Xiang Zhang²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1425-1436, 2020, DOI:10.32604/cmc.2020.011116

Abstract KLEIN-64 is a lightweight block cipher designed for resource-constrained environment, and it has advantages in software performance and hardware implementation. Recent investigation shows that KLEIN-64 is vulnerable to differential fault attack (DFA). In this paper, an improved DFA is performed to KLEIN-64. It is found that the differential propagation path and the distribution of the S-box can be fully utilized to distinguish the correct and wrong keys when a half-byte fault is injected in the 10^th round. By analyzing the difference matrix before the last round of S-box, the location of fault injection can be limited to a small range.… More >

Wei Liang^{1, 2}, Yang Ni³, Tingyi Li¹, Xuejiao Lin¹, Soo-Jin Chung^{1, *}

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1411-1424, 2020, DOI:10.32604/cmc.2020.011166

Abstract Agricultural culture is a productive activity about education and management. It aims at high efficiency and high quality, uses technology as its means, and takes nature as its carrier. Agricultural cultural resources are the product of the rapid development of modern economy. It promotes the development of the national economy and profoundly affects people's production and life. DEA model, also known as data envelope analysis method, is an algorithm that uses multiple data decision units for input and output training to obtain the final model. This article explains the concept and basic characteristics of agricultural culture. Through questionnaire surveys and… More >

Gongde Guo¹, Kai Yu¹, Hui Wang², Song Lin^{1, *}, Yongzhen Xu¹, Xiaofeng Chen³

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1397-1409, 2020, DOI:10.32604/cmc.2020.011399

Abstract As an important branch of machine learning, clustering analysis is widely used in some fields, e.g., image pattern recognition, social network analysis, information security, and so on. In this paper, we consider the designing of clustering algorithm in quantum scenario, and propose a quantum hierarchical agglomerative clustering algorithm, which is based on one dimension discrete quantum walk with single-point phase defects. In the proposed algorithm, two nonclassical characters of this kind of quantum walk, localization and ballistic effects, are exploited. At first, each data point is viewed as a particle and performed this kind of quantum walk with a parameter,… More >

Xiangchun Liu¹, Jing Yu²,Wei Song^{1, 3, *}, Xinping Zhang¹, Lizhi Zhao¹, Antai Wang⁴

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1385-1395, 2020, DOI:10.32604/cmc.2020.011308

Abstract With the development of satellite technology, the satellite imagery of the earth’s surface and the whole surface makes it possible to survey surface resources and master the dynamic changes of the earth with high efficiency and low consumption. As an important tool for satellite remote sensing image processing, remote sensing image classification has become a hot topic. According to the natural texture characteristics of remote sensing images, this paper combines different texture features with the Extreme Learning Machine, and proposes a new remote sensing image classification algorithm. The experimental tests are carried out through the standard test dataset SAT-4 and… More >

Xiaoye Shi^{1, *}, Jin Sun¹, Dongming Li¹, Fei Ding², Zhaowei Zhang¹

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1373-1384, 2020, DOI:10.32604/cmc.2020.011018

Abstract In this paper, we study the rate-energy tradeoff for wireless simultaneous information and power transfer in full-duplex and half-duplex scenarios. To this end, the weighting function of energy efficiency and transmission rate, as rate-energy tradeoff metric is first introduced and the metric optimization problem is formulated. Applying Karush-Kuhn-Tucker (KKT) conditions for Lagrangian optimality and a series of mathematical approximations, the metric optimization problem can be simplified. The closed-form solution of the power ratio is obtained, building direct relationship between power ratio and the rate-energy tradeoff metric. By choosing power ratio, one can make the tradeoff between information rate and harvested… More >

Yunfan Ye¹, Fang Liu^{1, *}, Shan Zhao², Wanting Hu³, Zhiyao Liang⁴

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1361-1372, 2020, DOI:10.32604/cmc.2020.011632

Abstract By efficiently and accurately predicting the adoptability of pets, shelters and rescuers can be positively guided on improving attraction of pet profiles, reducing animal suffering and euthanization. Previous prediction methods usually only used a single type of content for training. However, many pets contain not only textual content, but also images. To make full use of textual and visual information, this paper proposed a novel method to process pets that contain multimodal information. We employed several CNN (Convolutional Neural Network) based models and other methods to extract features from images and texts to obtain the initial multimodal representation, then reduce… More >

Jin Sun¹, Dengyin Zhang^{1, *}, Xiaoye Shi¹, Fei Ding^{1, 2}

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1349-1360, 2020, DOI:10.32604/cmc.2020.011459

Abstract Initial alignment is the precondition for strapdown inertial navigation system (SINS) to navigate. Its two important indexes are accuracy and rapidity, the accuracy of the initial alignment is directly related to the working accuracy of SINS, but in selfalignment, the two indexes are often contradictory. In view of the limitations of conventional data processing algorithms, a novel method of compass alignment based on stored data and repeated navigation calculation for SINS is proposed. By means of data storage, the same data is used in different stages of the initial alignment, which is beneficial to shorten the initial alignment time and… More >