The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In view of that the existing auction mechanism cannot effectively allocate cloudlet resource, which leads to a low resource utilization rate and social welfare. In this paper, we design a truthful greedy mechanism (TGM) to coordinate the auction of mobile users (buyers) and cloudlets (sellers). TGM consists of the greedy allocation algorithm based on buyer preferences and pricing mechanism, and improves...
In engineering and design problems, various noisy non-linear mathematical optimization problems can't be efficaciously solved by using conventional optimization techniques. But metaheuristic algorithms seem very efficient to approach in these problems and became very popular such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO). Recently, many new metaheuristic algorithms were proposed,...
The multi-antenna configurations used in MIMO (multi-input multi-output) system can greatly improve the transmission reliability and channel capacity. Antenna selection technique can reduce the implementation complexity and hardware cost while maintaining the advantages of MIMO system. Aiming at selecting the optimal antenna subset quickly in the changeable channel environment, a binary particle swarm...
With the advancement of miniature sensors, wireless networking and context awareness, the importance of data-intensive computing is on the rise, with practical applications such as web categorization and data mining. One of the critical challenges in data-intensive computing is data clustering, as effective clustering algorithm will enable researchers and automated systems to analyze and organize...
Monaural speech segregation from complex concurrent noise is an extremely challenging problem; binary mask is a method to solve this problem, however, the performance of binary mask is limited by remaining the noise in the result. In this paper, an algorithm integrated Spectral Subtraction and binary masking for speech separation and enhancement was proposed. It follows the framework of computational...
Multi-label classification learning concerns the determination of categories in the situation where one pattern may belong to more than one category. In this paper we propose a mixture approach, named FSMLKNN, which combines Fuzzy Similarity Measure (FSM) and Multi-Label K-Nearest Neighbor (MLKNN) for multi-label document classification. One of the problems associated with KNN-like approaches is its...
This paper presents a new approach to credit scoring by synthesizing simple nai??ve Bayesian classifier (SNBC) and the rough set theory. We adopted the combination of SNBC and rough set theory to build credit scoring model. The experiment was done on German Credit Database and showed that the model has a good prediction performance and has real world value upon application.
Automatic word-segmentation is vital for the reading, comprehension and translation of classics. However, large amount of special terms, allusions and proper names within the classics make it difficult for word segmentation. Taking classics of tea as the subject of research, a method was proposed using likelihood ratio statistics to decide two-character words candidate, three character words candidates...
In view of the fact that DBSCAN clustering algorithm can identify the data with arbitrary shape and one-pass clustering algorithm has the quick and efficient feature, this paper proposes a two-stage hybrid clustering algorithm. DBSCAN is improved to process the data with categorical attributes. By combining one-pass clustering algorithm with DBSCAN clustering algorithm, a two-stage hybrid clustering...
In this paper, a framework of region-of-interest (ROI) based multi-view video coding has been proposed to improve compression efficiency by properly segmenting the multi-view videos into different macroblock level ROI and encoding them separately. We define depth based ROI for multi-view video. Then, we propose a semantic low-complexity rode extraction algorithm based on multi-view video plus depth...
Web-based learning community allow educators to study how students learn (descriptive studies) and which learning strategies are most effective (causal/predictive studies). Since Web-based learning community are capable of collecting vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of students,...
Credit scoring models have been widely studied in academic world and the business community. Many novel approaches such as artificial neural networks (ANNs), rough sets, or decision trees have been proposed to increase the accuracy of credit scoring models. The C4.5 is a learning algorithm which adopts local search strategy, it cannot obtain the best decision rules. On the other hand, the simulated...
This paper studies hybrid dynamical evolutionary algorithm in the context of classification rule discovery. Nature inspired search algorithms such as genetic algorithms, Ant colonies and particle swarm optimization have been previously studied on data mining tasks, in particular, classification rule discovery. We extended this work by applying a hybrid algorithm which combines dynamical evolutionary...
The dynamical evolutionary algorithm is that all individuals in a population (called as particles in a dynamical system) are running and searching along with their population evolving driven by a new select mechanism. In this paper, rank-based selection is proposed for the dynamical evolutionary algorithm. The method applies rank-based selection to replace half of the lower fitness population with...
In this paper, a K-means clustering (KMC) algorithm of automation determination the clustering number K is proposed, and a approach of region-based image segmentation is introduced based on our proposed algorithm. For this approach, firstly, a suitable color space is selected, the features of color, texture, and location are extracted, and the feature space is generated. Then, in this feature space,...
C4.5 is a learning algorithm that adopts local search strategy, and it cannot obtain the best decision rules. On the other hand, the simulated annealing algorithm is a globally optimized algorithm and it avoids the drawbacks of C4.5. This paper proposes a new credit evaluation method based on decision tree and simulated annealing algorithm. The experimental results demonstrate that the proposed method...
Though the peer-to-peer network based on distributed hash table have scalability and availability features, but most of the distributed hash tables lack the support for the atomic data accessing, this ability is important to build data structures on distributed system. This paper gives the design and implementation of an atomic accessible mutable distributed hash table - FamDHT. The FamDHT use the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.