Human activity recognition using quasiperiodic time series collected from a single tri-axial accelerometer

The current generation of portable mobile devices incorporates various types of sensors that open up new areas for the analysis of human behavior. In this paper, we propose a method for human physical activity recognition using time series, collected from a single tri-axial accelerometer of a smartphone. Primarily, the method solves a problem of online time series segmentation, assuming that each meaningful segment corresponds to one fundamental period of motion. To extract the fundamental period we construct the phase trajectory matrix, applying the technique of principal component analysis. The obtained segments refer to various types of human physical activity. To recognize these activities we use the k-nearest neighbor algorithm and neural network as an alternative. We verify the accuracy of the proposed algorithms by testing them on the WISDM dataset of labeled accelerometer time series from thirteen users. The results show that our method achieves high precision, ensuring nearly 96 % recognition accuracy when using the bunch of segmentation and k-nearest neighbor algorithms.     

循环混沌优势进化算法

详细描述了新提出的能够快速收敛的优势进化算法以及基于混沌映射为初始群体的循环优势进化算法。对该策略利用模拟函数做了寻优测试并做了详细的讨论，测试表明在具有3^15个极小值的空间中循环优势进化算法能够在极短的时间内快速寻找到全局唯一的最小点。该全局最优算法策略具有很大的潜力运用于化学问题的复杂QSAR研究的寻优当中。     

An image encryption algorithm based on a novel 1D chaotic map and compressive sensing

Multimedia Tools and Applications - A new image encryption algorithm is presented based on a novel chaotic map and compressive sensing with excellent performance. At first, the sparse coefficient...     

A novel color image encryption scheme based on a new dynamic compound chaotic map and S-box

Multimedia Tools and Applications - In modern technological era image encryption has become an attractive and interesting field for researchers. They work for improving the security of image data...     

A novel image encryption scheme based on multi-directional diffusion technique and integrated chaotic map

Neural Computing and Applications - In recent years, many researchers have used chaos maps to encrypt digital images due to their unpredictability, ergodicity, and sensitivity to initial values....     

Mobile health monitoring system based on activity recognition using accelerometer

We propose a new method to recognize a user’s activities of daily living with accelerometers and RFID sensor. Two wireless accelerometers are used for classification of five human body states using decision tree, and detection of RFID-tagged objects with hand movements provides additional instrumental activity information. Besides, we apply our activity recognition module to the health monitoring system. We derive linear regressions for each activity by finding the correlations between the attached accelerometers and the expended calories calculated from gas exchange analyzer under different activities. Finally, we can predict the expended calories more efficiently with only accelerometer sensor depend on the recognized activity. We implement our proposed health monitoring module on smart phones for better practical use.     

A switched chaotic encryption scheme using multi-mode generalized modified transition map

Multimedia Tools and Applications - This paper presents a multi-mode generalized modified transition chaotic map and a switched chaotic encryption scheme based on it. Eight different modes of...     

A novel method for digital image steganography based on a new three-dimensional chaotic map

This paper, presents a novel chaos-based image steganography algorithm. Because of efficient property of chaos based security systems besides steganography applicability in providing secure communication, chaos based steganography algorithms served as a hot topic in recent researches. The proposed scheme possess novelties and advantageous such as: 1) Introducing a novel 3-dimensional chaotic map (LCA map) with strong chaotic characteristics and maximum Lyapunov exponent 20.58, which is used for generating three chaotic sequences, each of them represents the number of row, column, and colour component, respectively. 2) Utilizing random selection procedure for selecting subsequences with length of 2L, which L is the length of secret message 3) Specifying L pairs of triples host positions for embedding LSBs and MSBs of secret message by using three high level chaotic maps. 4) Entering some parameters dependent on elementary initial values, host image, and secret message features as a key point for adding additional layer of security alongside providing high sensitivity. 5) Providing high capacity for embedding secret message, which is equal to 50 % of whole image capacity (M?×?N?×?12). The proposed method could be applied in different criterion such as, confidential communication and data storing, protection of data alteration, and etc. Our experimental results guarantees that our scheme is not only robust against differential attacks, but also has promising results such as highly sensitive keys, Quality index, PSNR, MSE, and hiding capacity as shown in statistical security analysis.     

A novel data aggregation scheme based on self-organized map for WSN

The Journal of Supercomputing - Wireless sensor network allows efficient data collection and transmission in IoT environment. Since it usually consists of a large number of sensor nodes, a...     

基于加速度信号的人体运动平衡检测系统的研制

开发了一种基于三轴向加速度传感器的人体平衡检测系统,该系统采用三轴向直线加速度传感器获取人体运动信息,以单片机为控制核心,采用无线传输方式将采集到的数据传输到PC机上,适于检测处于自由运动情况下的对象,因此可以被广泛的应用于康复医学和运动医学。对健康人行进过程中加速度检测的结果表明,该系统可有效地对人体平衡协调能力进行评估。     

A new adaptive image steganography scheme based on DCT and chaotic map

Multimedia Tools and Applications - In this paper, a novel steganographic scheme is proposed based on chaotic map in the DCT domain. The proposed method apply the DCT on the cover image, scan the...     

穿戴位置无关的手机用户行为识别模型

基于智能手机的人体行为识别能用于健康监控和个人运动管理,针对不同用户携带手机的位置和习惯,分析基于手机传感器获取的三轴加速度信息,从人体不同位置的行为数据中提取多种特征,优选出与行为相关度高且与手机位置相关度低的特征,构建三种决策树分类模型:(行为位置)矢量模型、位置—行为模型和行为模型,其中行为模型准确率最高;针对手机放置在三种不同位置的混合样本,其行为判断准确率为80.29％,耗时最短,能有效进行用户行为识别.     

A pixel permutation based image encryption technique using chaotic map

Multimedia Tools and Applications - In the last decade, with a rapid increase in multimedia productions, image encryption has become a significant part of information security. The inherent image...     

An efficient image encryption algorithm based on a novel chaotic map

Multimedia Tools and Applications - In this paper, we propose a novel low dimensional chaotic map, namely, compounded piecewise linear map (CPLM) in order to balance between security and...     

基于单个三轴加速度计的人体行为识别研究

人工智能的发展和行业应用需求促进人体行为识别研究得到众多关注,主要研究方法或基于视频数据或基于传感器数据。得益于可穿戴传感器的发展,众多研究专注于在人体部署多个传感器以期取得良好效果。不同于以往研究,本文仅通过佩戴在手腕的单个三轴加速度计进行人体行为识别研究,以最大程度减小对个体的干扰并降低传感器部署成本。通过数据预处理和特征提取,并利用一种改进的子窗口的集成学习算法,实现对人体行为的准确识别。实验结果表明,相较于传统算法,识别准确率得以显著提升,证实了研究成果的有效性。     

A novel bit-level color image encryption using improved 1D chaotic map

Multimedia Tools and Applications - This paper introduces new simple and effective improved one-dimension(1D) Logistic map and Sine map made by the output sequences of two same existing 1D chaotic...     

A novel image encryption/decryption scheme based on chaotic neural networks

This paper presents a novel image encryption/decryption algorithm based on chaotic neural network (CNN). The employed CNN is comprised of two 3-neuron layers called chaotic neuron layer (CNL) and permutation neuron layer (PNL). The values of three RGB (Red, Green and Blue) color components of image constitute inputs of the CNN and three encoded streams are the network outputs. CNL is a chaotic layer where, three well-known chaotic systems i.e. Chua, Lorenz and Lü systems participate in generating weights and biases matrices of this layer corresponding to each pixel RGB features. Besides, a chaotic tent map is employed as the activation function of this layer, and makes the relationship between the plain image and cipher image nonlinear. The output of CNL, i.e. the diffused information, is the input of PNL, where three-dimensional permutation is applied to the diffused information. The overall process is repeated several times to make the encryption process more robust and complex. A 160-bit-long authentication code has been used to generate the initial conditions and the parameters of the CNL and PNL. Some security analysis are given to demonstrate that the key space of the new algorithm is large enough to make brute-force attacks infeasible and simulations have been carried out with detailed numerical analysis, demonstrating the high security of the new image encryption scheme.     

可变区间混沌映射在图像加密中的应用研究

针对图像等多媒体信息的特点,提出一种结合了两种混沌映射,即基于区间数目参数化的混沌映射与标准映射的数字图像加密算法.通过基于区间数目参数化的混沌映射产生混沌实数序列,将其转化为加密需要的伪随机二值序列,然后用该伪随机序列和标准映射变换进行数字图像加密.最后从理论和数字仿真实验两方面对算法的安全性进行分析,仿真实验结果表明,该算法是一个具有较好的安全性能和抗攻击能力的混沌加密算法.     

A secret image sharing scheme based on piecewise linear chaotic map and Chinese remainder theorem

In this paper, a secret image sharing scheme, by combining arithmetic compression coding and Chinese remainder theorem (CRT) is proposed. It is well known that arithmetic compression coding method for image has a good compressibility, and it can reduce the size of the shadow image, which consists of sharing values. Usually, a smaller shadow image is convenient to store and transmit. The piecewise linear map is applied to design compression coding scheme, which has the same properties as the conventional arithmetic compression coding. The CRT is used to construct the sharing scheme for compression codes. Meanwhile, it also has encryption effects in the process of sharing. Finally, the security and the effectiveness of the secret image sharing scheme are confirmed by some computer simulation results.