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Considering that expert's demonstrations are usually sub optimal and failed demonstrations often have some useful guidance, in this paper, a Discriminative Apprenticeship Learning algorithm is proposed, where the apprentice is taught with the join of failed attempts to acquire the ability that could discriminate the preference and non-preference cases so that to actively take a corresponding action...
Underwater acoustic channel is always a 2-D dispersive channel. For 2-D least-squares channel estimation, the design of training symbols is an open problem. In this paper, (i) we derive the optimal relation between the dimensions of the training matrix and the ffective memory lengths of the equivalent discrete-time channel model, and (ii) we propose a simple algorithm for searching suitable training...
Aimed at the problem of the automatic detection and classification identification for granary pests, an automatic granary pest identification system based on morphological feature is designed. Five morphological features such as complexity, duty cycle, elongation, moment invariants 1 and 2 are automatically extracted from granary pest image, and loaded into a BP neural network as input factors. The...
ART2 is a kind of self-organizing neural network which is based on adaptive resonance theory. It carries out the recognition by using competive learning and self-steady mechanism, and can learn by itself in dynamic environment with noise and without supervision. Its learning process can recognize learned models fastly and be adapted to new unknown objects rapidly. SAR ATR (Synthetic Aperture Radar...
Many researchers speculated that Massively Multiplayer Online Role-Playing Games (MMORPGs) could create a problem-based learning environment for students to learn teamwork skills. In this study, a highly interactive MMORPG, World of War craft (WoW) was adopted and one-group pretest posttest experiment was designed to answer two questions: (a) Do students¡¦ teamwork skills enhance through team playing...
This paper proposes a new manifold entropy function based on local tangent space (LTS). With this entropy function, we further propose a framework for image retrieval. The retrieval is treated as searching for ordered cycles by categories in image datasets. The optimal cycles can be found by minimizing our manifold entropy of images.
This paper presents a comparative study between Partial Least Squares (PLS) method and support vector regression (SVR) in modeling the relationship between the near infrared spectra (NIRS) and the polysaccharide contents in Cordyceps gunnii mycelia powder samples. Both of the models were optimized by selecting the suitable spectra preprocessing methods and the best modeling parameters. And then the...
The ongoing development of wireless sensor networks (WSNs) demands not only low-power sensors and less system cost but also good performance. Considering this background, investigating a new technology to satisfy both requirements is an important issue for current development of wireless sensor network systems. In this paper, we consider the situation that the sensor nodes in WSNs are deployed in...
Knowledge management system of flight safety and efficiency is very important for air traffic control staffs and drivers; and individuals with related knowledge is the main resource of the knowledge database. ATC staffs' abilities and techniques are key elements to avoid errors. This research, we design and build the course exams based on ADDIE model and SCORM (Sharable Content Object Reference Model)...
Lexicons are important resources for semantic tagging. However, commonly used lexicons collected from entity databases suffer from multiple problems, such as ambiguity, limited coverage and lack of relative importance. In this work we present a lexicon modeling technique that automatically expands the lexicon and assigns weights to its elements. For lexicon expansion, we use a generative model to...
As a developing endeavor of data mining on semi-structured information, sentiment analysis to the comments on the Internet has aroused people's great interest recently. This paper analysis the influence of different stop word removal methods on the result of text classification and represent the more effective stop word removal list. The experiment bases on the sentiment comments which have been grasped...
This paper proposes an automatic classification model based on rough set theory for texture image. The features from texture image are extracted by the gray level co-occurrence Matrix (GLCM), then some redundant features of them are reduced under the background of knowledge reduction of rough set theory in order to mine classification rules of texture images. And experiment shows that this model has...
The research on how to make a photo-based personalized facial sketch has important scientific significance and practical values. This paper proposes a method on how to generate a personalized sketch from digital color photo. First, the feature points are automatically extracted through Active Shape Model and the positions of these points are recorded; then, the style factor can be got from stylized...
Voice search technology has been successfully applied to help drivers reply SMS messages in automobiles, in which a predefined SMS message template set is searched with ASR hypotheses to form the reply candidate list. In order to efficiently organize the SMS message template set and improve the quality of the reply candidate list, we proposed to apply n-gram translation model and logistic regression...
The world's best technologies of triple jump are mainly two, namely, Russian category and Polish category model. For ordinary athletes to determine their own type of technology is a difficult problem. According to the closest principle, this paper applies the method of fuzzy recognition to set up the model of the proportion of the three hops in triple jumper. In addition, an example is presented to...
Detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. Execution anomalies include both work flow errors and low performance problems. People often use system logs produced by distributed systems for troubleshooting and problem diagnosis. However, manually inspecting system logs to detect anomalies is unfeasible...
Functionality Testing is one of the most popular used technologies of black-box testing strategy. Programs to be test were taken as implicit functions mapping inputs into outs. In the view of functionality testing, if the functional behaviors of the program can be predicated correctly, it could be applied as test oracles for newer test cases generation. The main problems of this issue are discussed...
As the core member in a software development team, the project manager's leadership level influences the development process in a great part. The existing literatures have shown the importance of individual's personality to his or her behaviors, which include the leadership behaviors. Exploring how the project managers' personality influences the success of the software development projects has significant...
The explosive Web make it hard to organize and manage Web information automatically. Therefore, online learning method such as incremental learning is gradually become effective instrument in practical applications. From our experiments, traditional incremental learning shows some flaws in the iterative process. To overcome the drawback caused by using only support vector to represent the whole former...
In the analysis of predicting financial distress based on support vector regression (SVR), irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper used rough sets as a preprocessor of SVR to select a subset of input variables and employed the immune clone...
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