Zhenqiu Xiao^1,*, Bin Yang², Desy Tjahjadi³

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638

Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a… More >

Jiao Yao¹, Yiling Ni¹, Jing Zhao², Huiwei Niu¹, Shanyong Liu¹, Yuhui Zheng³, Jin Wang^4,5,*

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1109-1122, 2019, DOI:10.32604/cmc.2019.06252

Abstract Violation probability of taxi drivers in metropolis is far more than that of normal drivers because they are labor-intensive, overconfident of self-driving skill, and always searching potential customers, sometimes even picking up or dropping off passengers randomly. In this paper, four types of violated behavior of taxi drivers in metropolis were first summarized, based on which corresponding scale table was initial designed with social statistical method. Furthermore, with certain samples, relative item analysis, exploratory factor analysis, validity analysis and reliability analysis were conducted to verify validity of the initial scale table, based on which some improvements were made, and we… More >

Jiancheng Zou^1,*, Tianshu Chen¹, Xin Yang²

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1029-1040, 2019, DOI:10.32604/cmc.2019.05793

Abstract Heart rate is an important physiological parameter for clinical diagnosis, it can infer the health of the human body. Thus, efficient and accurate heart rate measurement is important for disease diagnosis and health monitoring. There are two ways to measure heart rate. One is contact type and the other is non-contact. Contact measurement methods include pulse cutting, electrocardiogram, etc. Because of the inconvenience of this method, a non-contact heart rate method has been proposed. Traditional non-contact measurement method based on image is collecting RGB three-channel signals in continuous video and selecting the average value of the green channel pixels as… More >

Kamaljit Kaur^{1, *}, Kuljit Kaur²

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 913-946, 2019, DOI:10.32604/cmc.2019.07675

Abstract Hard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data. However, HDD failures pose a huge challenge to big data servers and cloud service providers. Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability. Recently, the researchers have used SMART parameters to develop various prediction techniques, however, these methods need to be improved for reliability and real-world usage due to the following factors: they lack the ability to consider the gradual change/deterioration of HDDs; they… More >

Ashwinth Janarthanan^1,*, Dhananjay Kumar¹

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 895-912, 2019, DOI:10.32604/cmc.2019.06805

Abstract Efficient aggregation in wireless sensor nodes helps reduce network traffic and reduce energy consumption. The objective of this work Localization Based Evolutionary Routing (LOBER) is to achieve global optimization for aggregation and WMSN lifetime. Improved localization is achieved by a novel Centroid Based Octant Localization (CBOL) technique considering an arbitrary hexagonal region. Geometric principles of hexagon are used to locate the unknown nodes in the centroid positions of partitioned regions. Flower pollination algorithm, a meta heuristic evolutionary algorithm that is extensively applied in solving real life, complex and nonlinear optimization problems in engineering and industry is modified as Enhanced Flower… More >

B. V. Santhosh Krishna^{1, *}, T. Gnanasekaran²

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 855-869, 2019, DOI:10.32604/cmc.2019.07585

Abstract An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction… More >

Yiming Xue¹, Nan Wang², Yan Niu¹, Ping Zhong^{2, ∗}, Shaozhang Niu³, Yuntao Song⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 741-756, 2019, DOI:10.32604/cmc.2019.05611

Abstract In practical application, many objects are described by multi-view features because multiple views can provide a more informative representation than the single view. When dealing with the multi-view data, the high dimensionality is often an obstacle as it can bring the expensive time consumption and an increased chance of over-fitting. So how to identify the relevant views and features is an important issue. The matrix-based multi-view feature selection that can integrate multiple views to select relevant feature subset has aroused widely concern in recent years. The existing supervised multi-view feature selection methods usually concatenate all views into the long vectors… More >

Jiyuan Liu¹, Yingzhi Zeng², Jiangyong Shi², Yuexiang Yang^2,∗, Rui Wang³, Liangzhong He⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 721-739, 2019, DOI:10.32604/cmc.2019.05610

Abstract Recently, TLS protocol has been widely used to secure the application data carried in network traffic. It becomes more difficult for attackers to decipher messages through capturing the traffic generated from communications of hosts. On the other hand, malwares adopt TLS protocol when accessing to internet, which makes most malware traffic detection methods, such as DPI (Deep Packet Inspection), ineffective. Some literatures use statistical method with extracting the observable data fields exposed in TLS connections to train machine learning classifiers so as to infer whether a traffic flow is malware or not. However, most of them adopt the features based… More >

Weiwei Liu¹, Yang Tang², Fei Yang², Yi Dou³, Jin Wang^4,*

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 813-834, 2019, DOI:10.32604/cmc.2019.06754

Abstract Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle. In this paper, a multi-objective optimization model for the location layout of EVCSs is established when considering various factors such as user demand, investment cost, soil locations, the emergency charging mileage limit, the actual road condition and service network reliability. The model takes the minimum investment cost and the minimum user charging cost as the… More >

Maosen Wang¹, Shaozhang Niu^1,*, Zhenguang Gao²

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 781-794, 2019, DOI:10.32604/cmc.2019.05595

Abstract Scene text recognition is one of the most important techniques in pattern recognition and machine intelligence due to its numerous practical applications. Scene text recognition is also a sequence model task. Recurrent neural network (RNN) is commonly regarded as the default starting point for sequential models. Due to the non-parallel prediction and the gradient disappearance problem, the performance of the RNN is difficult to improve substantially. In this paper, a new TRDD network architecture which base on dilated convolution and residual block is proposed, using Convolutional Neural Networks (CNN) instead of RNN realizes the recognition task of sequence texts. Our… More >