[show abstract][hide abstract] ABSTRACT: Teaching evaluation is an effective measure to improve the teaching quality, promote teachers' teaching level, and achieve the scientific and systematic management for faculty. In this paper, we present a model of teaching evaluation in adult higher education based on decision tree, aiming to mine the valuable knowledge from the data of teachers' evaluation and archives in teaching quality evaluation system. Firstly, we analyze the shortcomings of the ID3 algorithm and make some corresponding improvement. Secondly, we introduce the procedure of the model including the specific ways. Lastly, we carry on a case study by the presented model to demonstrate the feasibility of the model. The results show that the proposed method is feasible and can help teaching management personnel for scientific decision-making and improving teaching quality.
Information Technology and Computer Science (ITCS), 2010 Second International Conference on; 08/2010
[show abstract][hide abstract] ABSTRACT: There are many differences between human faces, but still having common characteristics. The person's facial contour can be approximated as ellipses, and the relative position of eyebrows, eyes, nose, mouth and other organs is stable in the whole face. Such shapes are similar and can provide the basis for the realization of human face synthesis. Whether in technology or in the application, human face synthesis with computer has broad prospects. As mathematical conversion model of uncertain knowledge, cloud model integrates the fuzziness and randomness to constitute the mapping between qualitative and quantitative, while the facial expression is a kind of uncertainty data. This paper proposes face synthesis technology based on cloud model. First of all, expand the cloud model algorithm from data points to data set and then put each piece of face image as a M'N (M rows, N columns are actually the image positioning) grid in order to make each image grid have a grayscale value (0-255). Secondly, extract cloud numerical characteristics (Ex, En, He) of inputted human face image with backward cloud generator. Thirdly, by positive cloud generator, generate a set of cloud droplets which have corresponding figures feature. And finally, achieve human face synthesis with backward cloud generator. Human face synthesis technology based on cloud model, realizes human face synthesis of multi-face expression sources based on different weighting ratio. The experimental results show that it can obtain different expression of modes, and enrich the connotation of the performance of facial expression by adjusting values of the weight vector.
[show abstract][hide abstract] ABSTRACT: In recent years, the text data of text mining has gradually become a new research topic. Among them, the study of the text clustering has attracted wide attention. This paper proposes an improved fuzzy clustering-text clustering method based on the fuzzy C-means clustering algorithm and the edit distance algorithm. We use the feature evaluation to reduce the dimensionality of high-dimensional text vector. Because the clustering results of the traditional fuzzy C-means clustering algorithm lack the stability, we introduce the high-power sample point set, the field radius and weight. Due to the boundary value attribution of the traditional fuzzy C-means clustering algorithm, we recommend the edit distance algorithm. The results show that the improved algorithm is applied to the text clustering, making the results of clustering more stable and accurate than the traditional FCM clustering algorithm.
Networks Security, Wireless Communications and Trusted Computing, International Conference on. 01/2010; 1:65-69.
[show abstract][hide abstract] ABSTRACT: Cloud computing is a hot topic in the field of research and applications. At present, there has been a lot of attention on cloud security and storage. Two areas in the field of cloud storage are worth mentioning. First, it is the lower layer of the cloud infrastructure which supports the functions of other layers above it. Second, through the cloud infrastructure and utilization of virtualization and distributed computing techniques, resources from server clusters are made available to enhance the data redundancy factor and efficiency for document access. As huge cloud storage facility incurs operating expenses so the question rests upon how to be reasonable and efficiently manage cloud storage, let's say, in a website for shareware download. The authors propose the use of Power-law Distributions and Improved Cubic Spline Interpolation for multi-perspective analysis of shareware download frequency. The tasks include data mining the usage patterns and to build a mathematical model. Through analysis and checks, in accordance with changes to usage requirements, our proposed methods will intelligently adjust the data redundancy of cloud storage. Thus, storage resources are fine tuned and storage efficiency is greatly enhanced.
[show abstract][hide abstract] ABSTRACT: The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity
with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated
ground data can be of importance in object identification, community planning, resource discovery and other areas. In this
paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most
of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore,
an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining
is given on the observed spatial objects, including the objects described by the first feature data field and the main feature
data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed.
The experimental results show that the new model is feasible in behavior mining.
Geo-spatial Information Science 01/2009; 12(3):202-211.
[show abstract][hide abstract] ABSTRACT: Ontology is the centre issue of semantic web architecture as a representative model of knowledge and the formal definition of common recognition of knowledge. In this paper, a new way is proposed to ontology modeling for the semantic web based on cloud model. First, the process of creating domain ontology is presented. Second, concept climbing is given to express ontology from the small concept climbing-up to big concept. Third, a case study and analysis are given on air conditioner. The result shows that it is feasible and effective to create domain ontology in terms of this model.
Granular Computing, 2008. GrC 2008. IEEE International Conference on; 09/2008
[show abstract][hide abstract] ABSTRACT: In this paper, a novel approach of data field is proposed to discover the action pattern of real-time person tracking, and
potential function is presented to find out the power of a person with suspicious action. Firstly, a data field on the first
feature is used to find the individual attributes, associated with the velocity, direction changing frequency and appearance
frequency respectively. Secondly, the common characteristic of each attribute is obtained by the data field on the main feature
from the data field created before. Thirdly, the weighted Euclidean distance classifier is used to identify whether a person
is a suspect or not. Finally, the results of the experiment show that the proposed way is feasible and effective in action
Advanced Data Mining and Applications, 4th International Conference, ADMA 2008, Chengdu, China, October 8-10, 2008. Proceedings; 01/2008
[show abstract][hide abstract] ABSTRACT: In recent years many attempts have been made to index, cluster, classify and mine prediction rules from increasing massive sources of spatial time-series data. In this paper, a novel approach of mining time-series data is proposed based on cloud model, which described by numerical characteristics. Firstly, the cloud model theory is introduced into the time series data mining. Time-series data can be described by the three numerical characteristics as their features: expectation, entropy and hyper-entropy. Secondly, the features of time-series data can be generated through the backward cloud generator and regarded as time-series numerical characteristics based on cloud model. In accordance with such numerical characteristics as sample sets, the prediction rules are obtained by curve fitting. Thirdly, the model of mining time-series data is presented, mainly including the numerical characteristics and prediction rule mining. Lastly, a case study is carried out for the prediction of satellite image. The results show that the model is feasible and can be easily applied to other forecasting.
[show abstract][hide abstract] ABSTRACT: Mainly from the angle of computer system, this paper analyzes the negative influence of natural environment caused by the
computer system. It presents a novel concept for green computing with generalized aspect and expands the traditional tasks
and relationships of green computing research. Firstly, the deep discussion of generalized green computing using hardware
and software technology and method is carried out, and the indicative meaning behind it is analyzed, including all kinds of
the scheme for research institutions and enterprises. Then, some basic ideas of green computing and generalized methods are
put forward in order to establish the necessary foundation for the methods and tools of green computing.
[show abstract][hide abstract] ABSTRACT: Identification research on spatial object, such as action identification and validity identification, is a hot topic in recent years and much study has focused on it. In this paper, data field is proposed to describe spatial object as a metric and improve the accuracy of identification. Potential function, as a part of data field, is introduced to discover the power of each object. Two kinds of data fields are created to express the personality and common characteristic of each object respectively. Weighted Euclidean Distance (WED) classifier is utilized in final identification. An experiment on real-time person tracking is carried out, and accuracy analysis is also discussed.
[show abstract][hide abstract] ABSTRACT: Energy-saving and environmental protection have become the most popular and important research topics at present. Green Computing, as an indispensable part, is a new computing model to promote scientific progress and sustainable social development. It has become the focus and the high ground of international competition, relating to the country’s political, economic and social security. In this paper, from the point of view reducing server redundancy and improving PC terminal performance, heterogeneous systems are deployed in a few or even a single server by using the virtualization technology. A globally collaborative mechanism of the Green Private Cloud Computing (GCMGPC) is proposed and the Green Private Cloud Architecture model is built with virtualization technology for meliorating the status. It can change the reality that the operating environment of Cloud Computing relies on backend servers excessively. Meanwhile, it provides a cooperative method of workload balance between servers and clients through a resources sharing dynamically balancing algorithm with the cloud servers and clients (RSDBASC). It can meet the requirement that transforms the clients into the similar cloud server nodes (SCSNs) under the premise of not increasing the number of the servers. The new integrated Green Private Cloud Architecture with global collaboration can greatly improve the utilization of hardware resources and allocate the global resource more rationally. By this architecture, it will achieve three purposes, including energy-saving, expenditure-reducing and efficiency. Experiments are carried out to validate the feasibility and superiority by such model, and the results are shown great. The presented methods establish a favorable foundation for the future research of Green Public Cloud.
Telecommunication Systems 52(2). · 1.03 Impact Factor