Abstract In this paper, we investigate the performance of an Automatic visual speech recognition system (AVSR) using the Hidden Markov Model (HMM) which is optimized by a Genetic Algorithm (GA). The search through the space of HMM structures is combined with optimization of emission and transition probabilities using the Baum-Welch algorithm in the training process. Compared with a HMM-based system, we... In this paper, we investigate the performance of an Automatic visual speech recognition system (AVSR) using the Hidden Markov Model (HMM) which is optimized by a Genetic Algorithm (GA). The search through the space of HMM structures is combined with optimization of emission and transition probabilities using the Baum-Welch algorithm in the training process. Compared with a HMM-based system, we observe a significant 13-31% improvement of the recognition rates. Read More Read Less

Abstract We consider ranking problems where the actions are evaluated on a set of ordinal criteria and where the evaluations are imperfect and represented by basic belief assignments (BBAs). In this paper, a model inspired by PROMETHEE is proposed within this context. The notions of ascending and descending belief functions are used in order to compare the alternatives on each criterion.... We consider ranking problems where the actions are evaluated on a set of ordinal criteria and where the evaluations are imperfect and represented by basic belief assignments (BBAs). In this paper, a model inspired by PROMETHEE is proposed within this context. The notions of ascending and descending belief functions are used in order to compare the alternatives on each criterion. The proposed approach is also illustrated by a pedagogical example. Read More Read Less

Abstract The eXtensible Mark-up Language rapidly has become a very powerful standard for the data exchange. Labeling schemes have been introduced to optimize data retrieval and query processing on XML database documents. This is done by providing labels that hold information about XML tree nodes. In this paper we introduce a novel labeling scheme XDAS whose labeling technique is inspired by... The eXtensible Mark-up Language rapidly has become a very powerful standard for the data exchange. Labeling schemes have been introduced to optimize data retrieval and query processing on XML database documents. This is done by providing labels that hold information about XML tree nodes. In this paper we introduce a novel labeling scheme XDAS whose labeling technique is inspired by IP addressing and subnetting technique used in computer networks. This technique is used when dividing a network into several sub-networks. Each sub-network is assigned a subnet mask that helps in identifying the parent network. So, this labeling scheme treats XML documents as a network with sub-networks and assigns labels for XML tree nodes using the masking technique. Experimental results show that XDAS, when compared to Dewey and Range labeling schemes, provides an efficient label size, disk space required to store labels and matching time required to identify relationships between nodes. Read More Read Less

Abstract Highly virtualized data center have placed many new and unique requirements on the networking fabric. Conventional network protocols limit the scale, latency, throughput of cloud networks. To solve these problems, the large layer 2 technology is proposed. The large layer 2 technology such as TRILL and SPB has obvious advantages in scalability, convergence and resource utilization compared with the traditional... Highly virtualized data center have placed many new and unique requirements on the networking fabric. Conventional network protocols limit the scale, latency, throughput of cloud networks. To solve these problems, the large layer 2 technology is proposed. The large layer 2 technology such as TRILL and SPB has obvious advantages in scalability, convergence and resource utilization compared with the traditional layer 2 technology. However, the disadvantages of employing the large layer 2 technology are barely addressed. To study the overhead of large layer 2 networking, we setup a data center environment with 6 core switches and conduct experiments to compare the performance of the representative large layer 2 protocol—TRILL and the typical layer 2 technology-STP. We also evaluate the intra-VLAN forwarding and inter-VLAN forwarding of TRILL. From our experiments, it is observed that the forwarding efficiency of TRILL is 30.16% lower than STP on average. It is also observed that the inter-VLAN traffic forwarding of TRILL averagely costs about 54% more time and consumes about 5% more CPU than intra-VLAN with a fixed packet generation rate. This is the first study towards unveiling the inefficiency of large layer 2 approach in data center networks as far as we know. Read More Read Less