Mingxu Sun^1,#,*, Yinghang Jiang^2,3,#, Qi Liu^3,4,*, Xiaodong Liu⁴

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 67-83, 2019, DOI:10.32604/cmc.2019.06079

Abstract A Functional Electrical stimulation (FES) therapy is a common rehabilitation intervention after stroke, and finite state machine (FSM) has proven to be an effective and intuitive FES control method. The FSM uses the data information generated by the accelerometer to robustly trigger state transitions. In the medical field, it is necessary to obtain highly safe and accurate acceleration data. In order to ensure the accuracy of the acceleration sensor data without affecting the accuracy of the motion analysis, we need to perform acceleration big data calibration. In this context, we propose a method for robustly calculating the auto-calibration gain using… More >

Raghisa Khalid¹, Nazeran Idrees^1,*, Muhammad Jawwad Saif²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 41-54, 2019, DOI:10.32604/cmc.2019.06554

Abstract Degree based topological indices are being widely used in computer-aided modeling, structural activity relations, and drug designing to predict the underlying topological properties of networks and graphs. In this work, we compute the certain important degree based topological indices like Randic index, sum connectivity index, ABC index, ABC₄ index, GA index and GA₅ index of Book graph B_n and Stacked book graph B_m,n. The results are analyzed by using edge partition, and the general formulas are derived for the above-mentioned families of graphs. More >

Assia Maamar^1,*, Khelifa Benahmed²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 15-39, 2019, DOI:10.32604/cmc.2019.06497

Abstract Recently, the radical digital transformation has deeply affected the traditional electricity grid and transformed it into an intelligent network (smart grid). This mutation is based on the progressive development of advanced technologies: advanced metering infrastructure (AMI) and smart meter which play a crucial role in the development of smart grid. AMI technologies have a promising potential in terms of improvement in energy efficiency, better demand management, and reduction in electricity costs. However the possibility of hacking smart meters and electricity theft is still among the most significant challenges facing electricity companies. In this regard, we propose a hybrid approach to… More >

Wei Sun^1,3,*, Hongji Du¹, Shoubai Nie^2,3, Xiaozheng He⁴

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 147-161, 2019, DOI:10.32604/cmc.2019.03581

Abstract Traffic sign recognition (TSR), as a critical task to automated driving and driver assistance systems, is challenging due to the color fading, motion blur, and occlusion. Traditional methods based on convolutional neural network (CNN) only use an end-layer feature as the input to TSR that requires massive data for network training. The computation-intensive network training process results in an inaccurate or delayed classification. Thereby, the current state-of-the-art methods have limited applications. This paper proposes a new TSR method integrating multi-layer feature and kernel extreme learning machine (ELM) classifier. The proposed method applies CNN to extract the multi-layer features of traffic… More >

Zhaohui Zhang^*,1,2,3, Jian Chen¹, Ligong Chen¹, Qiuwen Liu¹, Lijun Yang¹, Pengwei Wang^1,2,3, Yongjun Zheng⁴

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 117-132, 2019, DOI:10.32604/cmc.2019.05325

Abstract Recently, there are some online quantile algorithms that work on how to analyze the order statistics about the high-volume and high-velocity data stream, but the drawback of these algorithms is not scalable because they take the GK algorithm as the subroutine, which is not known to be mergeable. Another drawback is that they can’t maintain the correctness, which means the error will increase during the process of the window sliding. In this paper, we use a novel data structure to store the sketch that maintains the order statistics over sliding windows. Therefore three algorithms have been proposed based on the… More >

Youyu Gu¹, Xiongwei Xie², Chunsheng Gu^3,*

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 305-316, 2019, DOI:10.32604/cmc.2019.04121

Abstract As the development of cloud computing and the convenience of wireless sensor netowrks, smart devices are widely used in daily life, but the security issues of the smart devices have not been well resolved. In this paper, we present a new NTRU-type public-key cryptosystem over the binary field. Specifically, the security of our scheme relies on the computational intractability of an unbalanced sparse polynomial ratio problem (DUSPR). Through theoretical analysis, we prove the correctness of our proposed cryptosystem. Furthermore, we implement our scheme using the NTL library, and conduct a group of experiments to evaluate the capabilities and consuming time… More >

Zeyu Xiong^1,*, Qiangqiang Shen¹, Yueshan Xiong¹, Yijie Wang¹, Weizi Li²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 259-273, 2019, DOI:10.32604/cmc.2019.05155

Abstract Word vector representation is widely used in natural language processing tasks. Most word vectors are generated based on probability model, its bag-of-words features have two major weaknesses: they lose the ordering of the words and they also ignore semantics of the words. Recently, neural-network language models CBOW and Skip-Gram are developed as continuous-space language models for words representation in high dimensional real-valued vectors. These vector representations have recently demonstrated promising results in various NLP tasks because of their superiority in capturing syntactic and contextual regularities in language. In this paper, we propose a new strategy based on optimization in contiguous… More >

Yongzheng Lin¹, Hong Liu^{1, ∗}, Zhenxiang Chen², Kun Zhang², Kun Ma²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 245-257, 2019, DOI:10.32604/cmc.2019.04322

Abstract Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find… More >

Hefei Ling¹, Yang Fang¹, Lei Wu¹, Ping Li^1,*, Jiazhong Chen¹, Fuhao Zou¹, Jialie Shen²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 85-100, 2019, DOI:10.32604/cmc.2019.05588

Abstract Recently, Convolutional Neural Network (CNN) based hashing method has achieved its promising performance for image retrieval task. However, tackling the discrepancy between quantization error minimization and discriminability maximization of network outputs simultaneously still remains unsolved. Motivated by the concern, we propose a novel Balanced Deep Supervised Hashing (BDSH) based on variant posterior probability to learn compact discriminability-preserving binary code for large scale image data. Distinguished from the previous works, BDSH can search an equilibrium point within the discrepancy. Towards the goal, a delicate objective function is utilized to maximize the discriminability of the output space with the variant posterior probability… More >

Chein-Shan Liu ¹

CMC-Computers, Materials & Continua, Vol.33, No.2, pp. 175-198, 2013, DOI:10.3970/cmc.2013.033.175

Abstract An optimal m-vector descent iterative algorithm in a Krylov subspace is developed, of which the m weighting parameters are optimized from a properly defined objective function to accelerate the convergence rate in solving an ill-posed linear problem. The optimal multi-vector iterative algorithm (OMVIA) is convergent fast and accurate, which is verified by numerical tests of several linear inverse problems, including the backward heat conduction problem, the heat source identification problem, the inverse Cauchy problem, and the external force recovery problem. Because the OMVIA has a good filtering effect, the numerical results recovered are quite smooth with small error, even under… More >