Anjie Peng¹, Kang Deng¹, Shenghai Luo¹, Hui Zeng^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2217-2231, 2020, DOI:10.32604/cmc.2020.011006

Abstract The multi-purpose forensics is an important tool for forge image detection. In this paper, we propose a universal feature set for the multi-purpose forensics which is capable of simultaneously identifying several typical image manipulations, including spatial low-pass Gaussian blurring, median filtering, re-sampling, and JPEG compression. To eliminate the influences caused by diverse image contents on the effectiveness and robustness of the feature, a residual group which contains several highpass filtered residuals is introduced. The partial correlation coefficient is exploited from the residual group to purely measure neighborhood correlations in a linear way. Besides that, we also combine autoregressive coefficient and… More >

Xiaoyu Li¹, Qinsheng Zhu^{2, *}, Yiming Huang¹, Yong Hu², Qingyu Meng², Chenjing Su¹, Qing Yang², Shaoyi Wu², Xusheng Liu³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2143-2151, 2020, DOI:10.32604/cmc.2020.010865

Abstract Quantum correlation shows a fascinating nature of quantum mechanics and plays an important role in some physics topics, especially in the field of quantum information. Quantum correlations of the composite system can be quantified by resorting to geometric or entropy methods, and all these quantification methods exhibit the peculiar freezing phenomenon. The challenge is to find the characteristics of the quantum states that generate the freezing phenomenon, rather than only study the conditions which generate this phenomenon under a certain quantum system. In essence, this is a classification problem. Machine learning has become an effective method for researchers to study… More >

Rui Li¹, Guang Sun^1,*, Jingyi He¹, Ying Jiang¹, Rui Sun¹, Haixia Li¹, Peng Guo^1,2, Jianjun Zhang³

Journal on Internet of Things, Vol.2, No.2, pp. 65-73, 2020, DOI:10.32604/jiot.2020.09868

Abstract User portrait has been a booming concept in big data industry in recent years which is a direct way to restore users’ information. When it talks about user portrait, it will be connected with precise marketing and operating. However, there are more ways which can reflect the good use of user portrait. Commercial use is the most acceptable use but it also can be used in different industries widely. The goal of this paper is forecasting gender by user portrait and making it useful in transportation safety. It can extract the information from people who violated traffic principle to know… More >

Ali Khosravi^1,*, Oscar Ricardo Sandoval Rodriguez², Behnam Talebjedi¹, Timo Laukkanen¹, Juan Jose Garcia Pabon³, Mamdouh El Haj Assad⁴

Energy Engineering, Vol.117, No.5, pp. 249-265, 2020, DOI:10.32604/EE.2020.011024

Abstract The energy coming from solar radiation could be harvested and transformed into electricity through the use of solar-thermal power generation and photovoltaic (PV) power generation. Placement of solar collectors (thermal and photovoltaic) affects the amount of incoming radiation and the absorption rate. In this research, new correlations for finding the monthly optimum slope angle (OSA) on flat-plate collectors are proposed. Twelve equations are developed to calculate the monthly OSA by the linear regression model, for the northern and the southern hemisphere stations from 15° to 55° and –20° to –45°, respectively. Also, a new equation for calculating the yearly tilt… More >

Jen-Yuan Yeh^∗

Computer Systems Science and Engineering, Vol.33, No.1, pp. 41-52, 2018, DOI:10.32604/csse.2018.33.041

Abstract As a crucial task in information retrieval, ranking defines the preferential order among the retrieved documents for a given query. Supervised learning has recently been dedicated to automatically learning ranking models by incorporating various models into one effective model. This paper proposes a novel supervised learning method, in which instances are represented as bags of contexts of features, instead of bags of features. The method applies rank-order correlations to measure the correlation relationships between features. The feature vectors of instances, i.e., the 1st-order raw feature vectors, are then mapped into the feature correlation space via projection to derive the context-level… More >

Detian Huang¹, Peiting Gu², Hsuan-Ming Feng^3,*, Yanming Lin¹, Lixin Zheng¹

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 313-322, 2020, DOI:10.31209/2019.100000105

Abstract To tackle the problem of illumination sensitive, scale variation, and occlusion in the Kernelized Correlation Filters (KCF) tracker, an improved robust tracking algorithm based on KCF is proposed. Firstly, the color attribute was introduced to represent the target, and the dimension of target features was reduced adaptively to obtain low-dimensional and illumination-insensitive target features with the locally linear embedding approach. Secondly, an effective appearance model updating strategy is designed, and then the appearance model can be adaptively updated according to the Peak-to-Sidelobe Ratio value. Finally, the low-dimensional color features and the HOG features are utilized to determine the target state… More >

Hongtao Bai^{1, 2}, Xuan Li^{1, 2}, Lili He^{1, 2}, Longhai Jin^{1, 2}, Chong Wang^{1, 2, 3}, Yu Jiang^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1591-1603, 2020, DOI:10.32604/cmc.2020.09981

Abstract A current problem in diet recommendation systems is the matching of food preferences with nutritional requirements, taking into account individual characteristics, such as body weight with individual health conditions, such as diabetes. Current dietary recommendations employ association rules, content-based collaborative filtering, and constraint-based methods, which have several limitations. These limitations are due to the existence of a special user group and an imbalance of non-simple attributes. Making use of traditional dietary recommendation algorithm researches, we combine the Adaboost classifier with probabilistic matrix factorization. We present a personalized diet recommendation algorithm by taking advantage of probabilistic matrix factorization via Adaboost. A… More >

V. E. Prokhorov^*

FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.4, pp. 737-746, 2020, DOI:10.32604/fdmp.2020.08988

Abstract The collision of droplets with a water surface is being actively developed in the interests of many applied problems—transfer of matter through the ocean-atmosphere boundary, underwater acoustic noise of the marine environment, measurement of precipitation intensity, various technologies, and much more. One of the research priorities is acoustic radiation, in particular, shock sound arising at the moment a drop contacts the surface. The impact of the drop is preceded by processes that affect the shape of the drop, because of which it noticeably deviates from the spherical one. As a result, the final (contact) velocity changes–one of the most important… More >

Amin Alqudah^1,2, Hussein R. Al-Zoubi², Mahmood A. Al-Khassaweneh^2,3, Mohammed Al-Qodah¹

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 493-505, 2018, DOI:10.31209/2018.100000005

Abstract Handwritten numeral recognition is one of the most popular fields of research in automation because it is used in many applications. Indeed, automation has continually received substantial attention from researchers. Therefore, great efforts have been made to devise accurate recognition methods with high recognition ratios. In this paper, we propose a method for integrating the correlation coefficient with a Self-Organizing Maps (SOM)-based technique to recognize offline handwritten Arabic decimal digits. The simulation results show very high recognition rates compared with the rates achieved by other existing methods. More >

Yani Hou, Wenzhong Zhu, Erli Wang

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 805-814, 2019, DOI:10.31209/2019.100000084

Abstract Hyperspectral remote sensing, with its narrow band imaging, provides the potential for fine identification of ground objects, and has unique advantages in mineral detection. However, the image is nonlinear and the pure pixel is scarce, so using standard spectrum detection will lead to an increase of the number of false alarm and missed detection. The density peak algorithm performs well in high-dimensional space and data clustering with irregular category shape. This paper used the density peak clustering to determine the cluster centers of various categories of images, and took it as the target spectrum, and took the clustering results as… More >