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...     

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...     

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。     

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.     

基于分段非线性混沌映射的流密码加密方案

基于分段非线性混沌映射设计了一种流密码加密方案。用Logistic映射的输出作为分段非线性映射的分段参数,以Henon映射输出的混沌序列经运算后得到迭代次数,分段非线性混沌映射的输出与明文相加取模后生成密文。仿真实验和安全性分析表明,该方案的密钥空间大,对明文和密钥敏感,能有效抵抗穷举攻击、差分攻击和统计攻击,且实时性较好。     

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...     

融合关联性的多任务压缩感知行为识别方法

基于传感器的人体行为识别是一个新兴研究领域,作为物联网的一项重要应用,在医疗监护、助老助残、智能办公/家居等方面有着广阔的应用前景。识别率是行为识别的一个重要衡量指标,而特征和分类算法又是影响识别率的两个重要因素。提取了基于多传感器行为识别架构的关联特征,并引入压缩感知和稀疏表示理论,提出一种多任务压缩感知行为识别方法。最后,在基准数据库上采用个体无关的留一验证方法进行了大量实验,结果表明所提出的融合关联性的多任务压缩感知行为识别方法能有效提升行为识别率,与对应的单任务行为识别方法相比,识别速度提高约56%。     

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...     

多服务器环境下可实现访问控制的身份认证方案

相比单服务,多服务器环境的认证方案具有不需要用户重复注册和记忆多个密码等优点,近年来受到学界关注。2015年,屈娟等人提出一个多服务器环境下基于切比雪夫多项式的三因素身份认证方案。相比目前其他多服务器环境的身份认证方案,该方案具有一定新意。但通过分析可以发现该方案仍然存在如下缺陷：容易受到重复注册攻击;生物特征处理不恰当;认证过程严重依赖注册中心,容易遭受拒绝服务器攻击以及系统整体健壮性不高;协议部分设计存在不合理之处。为了解决上述问题,提出基于安全概略和切比雪夫多项式的三因素身份认证方案。通过分析可知该方案虽然计算量有所提升但是能较好解决屈娟等人所提方案存在的安全威胁,同时该方案也能实现访问控制。