In communication and signal processing course there are some challenges in explaining the basic theory of signal and how to process the signal as well. Educational tool to demonstrate how the system works is important and more attractive to improve the understanding of student. Software Defined Radio (SDR) brings the concept of software-based processing. This paper implements the using of SDR as the innovative teaching method to demonstrate the fundamental concept in signal processing course. Students build the audio signal processing projects on SDR platform using GNU Radio. Three interesting projects including the adjustment of sampling rate, DSB-AM modulation, and audio processing for gender identification are simulated using GNU Radio software. This Project Based Learning shows the positive result of the implementation of SDR in raising the student interest and motivation. Furthermore this study opens wide application of SDR based technique especially for education.

The visible image-based approach has long been considered the most powerful approach to facial emotion estimation. However it is illumination dependency. Under uncontrolled operating conditions, es...

To solve the problem of indoor surveillance, this paper is concerned about the framework that allows the detection of moving objects based on IP camera. The current background subtraction algorithms cannot correctly classify foreground and background if there are sudden illumination changes. To eliminate the influence of illumination changes, intensity flicker correction technique is employed before background subtraction in this paper. Meanwhile to reduce the false alarms further, the union of two separate detection results is employed. In the experimental results, both global illumination changes and local ones are included. The results show that the improved subtractor proposed in this paper performs better than ViBe both in the aspect of correct detection rate and false alarms.

With the wide application of Internet in almost all fields, it has become the most important way for information publication, providing a large number of channels for spreading public opinion. Public opinions, as the response of Internet users to the information such as social events and government policies, reflect the status of both society and economics, which is highly valuable for the decision-making and public relations of enterprises. At present, the analysis methods for Internet public opinion are mainly based on discriminative approaches, such as Support Vector Machine (SVM) and neural network. However, when these approaches analyze the sentiment of Internet public opinion, they are failed to exploit information hidden in text, e.g. topic. Motivated by the above observation, this paper proposes a detection method for public sentiment based on Probabilistic Latent Semantic Analysis (PLSA) model. PLSA inherits the advantages of LSA, exploiting the semantic topic hidden in data. The procedure of detecting the public sentiment using this algorithm is composed of three main steps: (1) Chinese word segmentation and word refinement, with which each document is represented by a bag of words; (2) modeling the probabilistic distribution of documents using PLSA; (3) using the Z-vector of PLSA as the features of documents and delivering it to SVM for sentiment detection. We collect a set of text data from Weibo, blog, BBS etc. to evaluate our proposed approach. The experimental results shows that the proposed method in this paper can detect the public sentiment with high accuracy, outperforming the state-of-the-art approaches, i.e., word histogram based approach. The results also suggest that, text semantic analysis using PLSA could significantly boost the sentiment detection.

Automatically locating face areas can advance applications either in images or videos. This paper proposes a video-based approach for face detection and tracking in an indoor environment to determine where face areas appear in video sequences. Our approach involves four main modules: an initialization module for setting all configurations, a Condensation module for face tracking, a template module for measuring the observation process in Condensation, and a correction module for correcting the tracking if the tracked face has been lost. We adapted the Condensation algorithm for dealing with the face tracking problem, and designed a checklist scheme for the template module that can record the most significant templates of the tracked face poses. We also performed experiments to demonstrate the performance and the robustness of our proposed approach for face detection and tracking.

The eye ground texture is disturbed by non ideal imaging factor such as noise, it will affect the clinical diagnosis in practice, an improved multi scale retina eye ground texture recognition algorithm is proposed based on fusion area threshold. The nonlinear sampling multi-scale transform is used to analyze the geometric space coefficient of retinal vessels with multi direction and shift invariant features, the regional threshold filtering is integrated, it is used to suppress the effect of non-uniform blocks for texture recognition. The maximum likelihood local mean standard deviation analysis is used for texture parameters estimation and recognition. The noise reduced greatly, accurate identification of texture feature is obtained. Simulation results show that the algorithm can well characterize the retinal vascular texture, it has good performance in different texture feature recognition, the recognition accuracy is improved, and it has good robustness.

To investigate the rules of a user’s attention allocation and attention shift when they are using a display control terminal, using both methods of information processing, situation awareness theory and eye-movement tracking technology were applied to analyze the influence of different interface element layouts on attention allocation and attention shift. In this study, 26 participants performed an operating task under different display control interfaces, which were divided into two types and used to simulate different situation awareness levels, and the fixation point distribution was recorded as the evaluation index. The participants were asked to perform a daily washing task and a fixed task on the simulation interface of a cylinder washing machine. The experimental results revealed that different situations and different situational awareness levels of the participants influenced the rule of attention allocation and transfer; the information elements on the interface play a key role in the user's cognitive process. The experimental results and users’ subjectivities were generally in agreement; thus, the present study could provide ergonomic evidence with display and control terminal interface design

This paper concentrates on how to mine useful information from massive XML documents in cloud computing environment. The structure of the Cloud computing and the corresponding tree data model of a XML document are analyzed in advance. Afterwards, structure of the proposed XML data mining system is illustrated, which is made up of three layers, such as “Application layer”, “Data processing layer”, and “XML Data converting layer”. In the XML Data converting layer, XML data are collected from databases and documents, and then the source data can be converted to XML file effectively. In the data processing layer, the process of data selection, cleaning and standardization for XML data set is implemented, moreover, a XML data set with higher degree of structure and rich semantics are obtained. In the application layer, “the results report module”, “data query module” and “results analysis module” are included. Next, massive XML data mining algorithm is proposed. The main innovations of this algorithm lie in that 1) the structure of a XML document is represented as an unordered tree, 2) the sub-structures of a XML document are modeled as sub-trees, and XML trees are regarded as a forest which is made up of all the sub-trees. Experimental results show that the proposed method can effectively mine useful information from massive XML documents in cloud computing environment with high efficiency.

With the rapid development of computer network and information technology, traditional clothing industry has taken a giant stride forward to computer information and digitization. In this paper, 250 3D point-cloud photos of young females were selected as subjects, and related characteristic points of neck rhizosphere (including front neck point, side neck point and back neck point) were determined. Then the height size, width size, thickness size and girth size of characteristic points were measured by the software named Imageware 12.1. At last, with software called Excel and SPSS, the height rules of characteristic points were analyzed, front and back neck rhizosphere were obtained by width and thickness sizes of characteristic points. The research in this paper has laid the foundation for building female neck rhizosphere line of virtual mannequin which provides datum line and basic sizes for 3D collar patterns

Recognition rate of mainstream fingerprint recognition algorithm is very low for occluded fingerprint image. In order to solve this problem, based on multi association matching features this thesis proposes the recognition algorithm (RA-MAMF). Firstly, image is pre-processing, the fingerprint image's Gabor filter is enhanced, and bi-narized and thinning pretreated are involved; secondly, the image is divided into multi homogeneous subsets, in which statistical association features and the bifurcation points of each subset are respectively extracted; finally on the basis of fingerprint, images are to be recognized, they are compared and match with the subset. Complete and occluded fingerprints data sets are used to make tested; the recognition algorithm based on multi association matching features has achieved excellent recognition accuracy; the RA-MAMF algorithm does not significantly increase the operating time, and this method effectively solves the low accuracy of traditional identifying the Occluded fingerprint image.