Abstract:Smart phones are becoming more popular, more powerful and have a variety of sensors available to capture information from the outside world, process the data in real-time, and transfer information remotely using wireless communications. These factors make smart phones an ideal option as a “take-anywhere” physiological monitor without the need for additional hardware, and their potential has been explored for many medical tele-monitoring applications. In this paper, we describe a few methods that perceived of human activity parameters and vital signs parameters using the existing sensors of smart phones. In addition, in order to make the fusion and integration of several monitoring methods realized, we proposed a new monitoring approach and gave an integrated solution. Finally, through comparisons with the professional health equipment, the effectiveness of the approach was verified.

Abstract:To avoid the premature convergence and enhance the search capability of the high-dimensional space, a novel self-perception high-dimensional chaotic particle swarm algorithm was presented. Firstly, a double perturbation of pBest and gBest was used to enhance the searching capability of particles. Secondly, self-perception approach was proposed to help the particle swarm to avoid the premature convergence. Lastly, three discrete PSO variants were tested on the traveling salesman problem (TSP). Experimental results show that the self-perception high-dimensional chaotic particle swarm algorithm is simple, effective and promoting in a high-dimensional space.

Abstract:The log data management system is one of the key infrastructures for cloud computing. Missing of important log data leads to inaccurate and one-sided data analysis and decision making. However, the stronger the log data capturing capability is, the higher the runtime overhead is. In order to capture necessary log data and reduce the runtime overhead as much as possible, this paper first put forward the log data capturing grain level concept was put forward firstly in this paper, and a grain-level self-configuring log data capturing platform was designed then for cloud computing. This platform is consisted of a log data capturing tool, a knowledge base storing grain-level based log capturing rules and facts, a rule-based inference engine for adding and removing specific log data capturing modules, and graphical interfaces for managing the knowledge base and querying log data sets. Finally, our preliminary case study demonstrates the efficiency of our platform.

Abstract:IoT international standardization events launched by Standard Development Organizations (SDOs), including ITU-T, OneM2M, 3GPP, IETF and OMA were introduced. Correspondingly, the differentiated positions of these events were indicated. The main content or characteristics of several standards, i.e. ITU-T Y.2060, OneM2M, 3GPP TS 23.682, IETF 6LowPan, IETF COAP, OMA DM and OMA LightWeightM2M were concluded.

Abstract:The numbers of microRNA and genes sequences have increased greatly with the advent of big data era. Thus how to explore useful information with biological significances from massive datasets has become a new hot topic. Former researches showed that microRNAs tended to play roles in diseases in a cooperative way and the relationships could be presented in the form of network. As a result, similarity analysis for microRNAs through a system way could play an important role in the field of disease biomarkers discovery. Considering that microRNAs play regulation roles by binding to their target genes, we focused on the available target gene data to analyze the similarity of microRNA pairs on functional levels. The optimization microRNA targets list generated by our former research as input were chosen and the enrichment analysis was used to map gene sets into functional term sets. The similarities between microRNAs were then calculated using similarity metrics on functional levels. Our results show that microRNAs in the same family tend to regulate the same or similar target genes. Compared with non-target genes, microRNA target genes tend to share similar cellular component. However, they show fewer similarities on biological pathway and biological progress levels.

Abstract:Big data is generated from sophisticated applications and is going to continue growing over the future years in a much diverse, larger and faster manner. Particularly, massive data with different formats sensed by various sensors, devices were from independent or connected components of Internet of Things (IoT) applications decide the diversity of applications and service type in IoT systems, which requires new technologies to manage big data with various format and to meet the requirements of various IoT applications. For such diverse business requirements, traditional systems are difficult to give a preferable solution due to their incapable system architectures. Consequently, to design new scalable system architectures is becoming a key research point for IoT big data management. This paper aims to provide a novel solution to manage big data of IoT systems, namely, the sea-cloud synergy model. Firstly, the designed architecture and the synergy mechanism of the model were discussed. Secondly, the design and implementation details of sea-side and cloudside of the sea-cloud synergy model were presented respectively. Finally, a demonstration system was built . Experimental experimental results verifies the preferable performance and feasibility of the designed sea-cloud synergy model.

Abstract:In this paper, built-in sensors were described to automatically detect human daily activities. In contrast to the previous work, this paper intends to recognize the physical activities when the phone’s orientation and position are varying. The data collected from six positions of seven subjects were investigated and two signals that are insensitive to orientation were chosen for classification. Decision trees (J48), Naive Bayes and sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs. The classification results of three classifiers were compared. The results demonstrates that the J48 classifier produces the best performance (average recognition accuracy: 90.7%). Then we chose the J48 classifier as online classifier.

Abstract:With the further development and extensive applications of the Internet of Things, the cellular network has become the most important transmission link and people pay more attention to establishing the network test platform. In this paper, the network test technology was analyzed, the test target and test processes were put forward, a comprehensive test platform which is used for the real sensor network traffic and simulation traffic was designed and a unified port for wireless network traffic and simulation traffic was provided. To approach to the real sensor network data, the self-similarity and long range dependence were introduced in the traffic generator, and the RMD(Random Midpoint Displacement) algorithm was used to process the simulation data to generate multi-user data models. The test environment would be chosen respectively in this article according to the requirement to establish a unified test platform with two different test interfaces, which could satisfy different demands and provide guide and references to the cellular network test.

Abstract:With the integration of 3G Network and Wireless Sensor Network, the Internet of Things is considered to be one of the most important technologies of the new century. For the Internet of Things, how to extend the working time of sensor nodes is the core problem. At present, there are two specifications of power management: APM (Advanced Power Management) and ACPI (Advanced Configuration and Power Interface) which are designed for PC. Due to their complexity and the requirements for BIOS layer, these two methods are not applicable to wireless sensor node. In this paper, the signalslot framework was developed firstly. Secondly, based on signal-slot framework, a simple and effective power management scheme-SPM (simple power management) was designed and applied in the popular sensor node operating system Contiki.

Abstract:The video teaching resource is an important part of the teaching resource library, and it is important to add video resources for the system platform. At present, the adding of video resources for many teaching resource libraries is done by hand, which is of low efficiency and produces heavy workload. By introducing the network crawler and using the extended function of Heritrix, the corresponding module was customized to make it automatically grasp course video resources from the network. And it could improve the video grasping efficiency and accuracy of the resource library by optimizing its grasping algorithm.

Abstract:With the rapid development of high-throughput OMICs technology in past few years, the research methodologies of life science have undergone tremendous changes. The analysis of numerous biological data urgent modern technologies and tools for big data analysis. Compared with other computing technologies, GPU has significant advantages on floating operations, parallelism and energy consumption and gets more and more attention as a generalpurpose computing device. Bioinformatics researchers apply GPU in their project and accelerate the program with a speedup of two orders of magnitude as usual. In this paper, we will review GPU application in several fields of bioinformatics and discuss the features of problems which GPU is capable of and its shortcomings.

Abstract:The research of ECG(Electrocardiograph) automated detection and diagnosis has been a hot topic in the signal processing and pattern recognition fields and a basis of adopting ECG. In this paper, the history and current state of ECG signal automatic detection were reviewed and the key technologies as well as existing problems were discussed. Finally, a prospect is given on the future trends of the technology.