Information2015, 6(2), 152-161; doi:10.3390/info6020152 - published 24 April 2015 Show/Hide Abstract
Abstract: As a dominant method for face recognition, the subspace learning algorithm shows desirable performance. Manifold learning can deal with the nonlinearity hidden in the data, and can project high dimensional data onto low dimensional data while preserving manifold structure. Sparse representation shows its robustness for noises and is very practical for face recognition. In order to extract the facial features from face images effectively and robustly, in this paper, a method called graph regularized within-class sparsity preserving analysis (GRWSPA) is proposed, which can preserve the within-class sparse reconstructive relationship and enhances separatability for different classes. Specifically, for each sample, we use the samples in the same class (except itself) to represent it, and keep the reconstructive weight unchanged during projection. To preserve the manifold geometry structure of the original space, one adjacency graph is constructed to characterize the interclass separability and is incorporated into its criteria equation as a constraint in a supervised manner. As a result, the features extracted are sparse and discriminative and helpful for classification. Experiments are conducted on the two open face databases, the ORL and YALE face databases, and the results show that the proposed method can effectively and correctly find the key facial features from face images and can achieve better recognition rate compared with other existing ones.
Information2015, 6(2), 134-151; doi:10.3390/info6020134 - published 21 April 2015 Show/Hide Abstract
Abstract: Taxi GPS traces, which contain a great deal of valuable information as regards to human mobility and city traffic, can be extracted to improve the quality of our lives. Since the method of visualized analysis is believed to be an effective way to present information vividly, we develop our analysis and visualization method based on a city’s short-dated taxi GPS traces, which can provide recommendation to help cruising taxi drivers to find potential passengers with optimal routes. With our approach, hot spots for loading and unloading passenger(s) are extracted using an improved DBSCAN algorithm after data preprocessing including cleaning and filtering. Then, this paper describes the start-end point-based similar trajectory method to get coarse-level trajectories clusters, together with the density-based ε distance trajectory clustering algorithm to identify recommended potential routes. A weighted tree is defined including such factors as driving time, velocity, distance and endpoint attractiveness for optimal route evaluation from vacant to occupied hot spots. An example is presented to show the effectiveness of our visualization method.
Information2015, 6(2), 122-133; doi:10.3390/info6020122 - published 27 March 2015 Show/Hide Abstract
Abstract: Aiming at the common problems of intelligent document platform-dependency, this paper proposes an MVC-based (Model View Controller-based) intelligent document model using UIML (User Interface Markup Language). The model is made on the basis of the previous work of our team, and the difference is that the new model separates user interface and interaction descriptions from the view component to make the intelligent document model much more independent of platform and programming language. To verify the intelligent document model, we implemented a prototype, which can support intelligent operations. The test result shows that our approach is correct. The model not only follows MVC framework, but also provides good flexibility and independence.
Information2015, 6(2), 111-121; doi:10.3390/info6020111 - published 27 March 2015 Show/Hide Abstract
Abstract: Taking both OOXML and UOF standards as examples, we empirically evaluate the interoperability of office document formats from the view of translation practice. With the aim of covering the complete feature set of OOXML and UOF, a novel UOF-Open XML Translator is developed in this study. Thorough experiments demonstrate that our translator implements bidirectional conversion of 80.4% features perfectly and 9.9% features with acceptable discrepancy. Regarding the remaining 9.7% features, more efforts would be taken in future work.
Information2015, 6(1), 89-110; doi:10.3390/info6010089 - published 13 March 2015 Show/Hide Abstract
Abstract: Companies are facing cut throat competition and are forced to continuously perform better than their competitors. In order to enhance their position in the competitive world, organizations are improving at a faster pace. Industrial organizations must be used to the new ideals, such as innovation. Today, innovative design in the development of new products has become a core value in most companies, while innovation is recognized as the main driving force in the market. This work applies the Russian theory of inventive problem-solving, TRIZ and the fuzzy analytical hierarchy process (FAHP) to design a new shape for machine tools. TRIZ offers several concepts and tools to facilitate concept creation and problem-solving, while FAHP is employed as a decision support tool that can adequately represent qualitative and subjective assessments under the multiple criteria decision-making environment. In the machine tools industry, this is the first study to develop an innovative design under the concept of lean production. We used TRIZ to propose the relevant principles to the shape’s design with the innovative design consideration and also used FAHP to evaluate and select the best feasible alternative from independent factors based on a multiple criteria decision-making environment. To develop a scientific method based on the lean production concept in order to design a new product and improve the old designing process is the contribution of this research.
Information2015, 6(1), 69-88; doi:10.3390/info6010069 - published 10 March 2015 Show/Hide Abstract
Abstract: Analysis of urban saturated power loads is helpful to coordinate urban power grid construction and economic social development. There are two different kinds of forecasting models: the logistic curve model focuses on the growth law of the data itself, while the multi-dimensional forecasting model considers several influencing factors as the input variables. To improve forecasting performance, a novel combined forecasting model for saturated power load analysis was proposed in this paper, which combined the above two models. Meanwhile, the weights of these two models in the combined forecasting model were optimized by employing a fruit fly optimization algorithm. Using Hubei Province as the example, the effectiveness of the proposed combined forecasting model was verified, demonstrating a higher forecasting accuracy. The analysis result shows that the power load of Hubei Province will reach saturation in 2039, and the annual maximum power load will reach about 78,630 MW. The results obtained from this proposed hybrid urban saturated power load analysis model can serve as a reference for sustainable development for urban power grids, regional economies, and society at large.