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The aim of this study was to identify the regional variations in the mechanical properties of vertebral can cellous bones at both the apparent and tissue levels, and their relative differences with respect to ageing. Ninety trabecular specimens were obtained from six normal L4 vertebral bodies of six male cadavers in two age groups, three aged 62 years and three aged 69 years, and were scanned using a high-resolution micro-computed Tomography (micro-CT) system. The obtained micro-CT reconstruction models were then converted to micro-finite element models. Micro-finite element analyses were done to determine the apparent Young's moduli and tissue-level von Mises stress distribution for each trabecular specimen in the longitudinal direction (on-axis direction), and medial-lateral and anterior-posterior directions (off-axis directions), respectively. Regional variations about the mechanical properties at both apparent and tissue levels in different transverse layers and vertical columns within and between the two age groups were then analyzed. The results showed significant decreases in the apparent Young's moduli and tissue level von Mises stresses in each direction with ageing; those in the two off-axis directions decreased more with ageing compared with the longitudinal direction, and there were no statistically significant differences between the mechanical properties in the two off-axis directions. The mechanical properties followed their own patterns of regional variations within each group, suggesting both mechanical and age-related adaptation. This study offered an insight into the distributions and variations of mechanical properties within a vertebral body. The mechanical properties calculated from this study may serve as reference for gender and ethnic comparisons and may help us to better understand the regional fracture risk and mechanisms of vertebral fracture, and prevent osteoporotic fracture in older individuals. [ABSTRACT FROM AUTHOR]

A three-dimension, neuromusculoskeletal model of the human upper limb, consisting of 30 muscle-tendon systems, was combined with dynamic optimization theory to simulate reaching-grasping movements. The model was verified using experimental kinematics, muscle forces, and electromyographic(EMG) data from volunteer subjects performing reaching-grasping movements. Despite joint redundancy, the topological invariance was observed in the trajectories of different task performance, and the linear relationships between joints covariation were exhibited. Quantitative comparisons of the model predictions and muscle activations obtained from experiment show that the minimum torque-change criterion is a valid measure of reaching-grasping performance. [ABSTRACT FROM AUTHOR]

Muscular coordination analysis of lower limbs during rising from a squat is one of the important categories in rehabilitation engineering and gymnastic science. This paper describes an efficient biomechanical model of the human lower limb with the aim of simulating the real human rising from a squat with lifting. To understand how intermuscular control coordinates limb muscle excitations the optimal control technique is used to solve the muscle forces sharing problem. The validity of the model is assessed comparing the calculated muscle excitations with the registered surface electromyogramm (EMG) of the muscles. The results show that synergistic muscles are build up by the neural control signals using a minimum fatigue criterion during human squat lifting, with distinct phases that include the acceleration during the initial movement and the posture at the final specified position. Synergistic muscular groups can be used to simplify motor control, and are essential to reduce the number of controlled parameters and amount of information needing to be analyzed in the performance of any motor act. [ABSTRACT FROM AUTHOR]

Understanding how the retina encodes visual information is a key issue for the development of a retinal prosthesis. To study this issue, the neural retina is modeled as a retina module (RM) consisted of an ensemble of spatial-temporal (ST) filters and each ST filter simulates the input-output property of an individual ganglion cell (GC). Two receptive field (RF) models of retinal GC, the difference of Gaussians (DOG) model and the disinhibition (DIS) model, are employed to implement these ST filters respectively. RM performs the encoding operation from an input optical pattern to a group of parallel action potential (AP) trains. To assess the encoding efficiency of RF models, a central visual system module (VM) consisted of a group of artificial neural networks is employed to perform the decoding operation from AP trains to an output perceptual pattern. A matching error is defined as an index to quantify the similarity between the input optical pattern and the output perceptual pattern generated by VM. The simulation results suggest that the matching error declines dramatically when the DOG model is replaced by the DIS model, which implies that the encoding mechanism of the DIS model might be more effective than that of the DOG model. [ABSTRACT FROM AUTHOR]

A variety of subscriptions in Conditional Access System (CAS) of DTV broadcasting network bring complexity to the key distribution scheme. In this paper, an innovation of hierarchical key distribution scheme for CAS in DTV broadcasting is proposed to reduce the computation of encryption and the number of messages for key refreshment. Compared with the conventional key distribution schemes, no encrypted message is distributed for key refreshment when a subscriber leaves. Further more, our hierarchical tree of key can provide a lot more dynamic management, from which broadcasters can improve efficiency in managing program channels. [ABSTRACT FROM AUTHOR]

Web service composition provides a way to build value-added services and web applications by integrating and composing existing web services. In this paper, a composite web service is modeled using queueing network for the purpose of performance analysis. Each component web service participating the composite web service corresponds to one service center. The control flow between component web services is represented by the Markov chain that describes the transition of customers between service centers. To perform performance analysis, the Markov chain should be known first. However, a web service is usually a black box and only its interfaces can be seen externally, so the internal control flow can be only estimated from history execution logs. This paper gives a method that mines the Markov chain of a composite web service from its execution logs. Then, bottlenecks identification and performance analysis are conducted for the queueing network model. Experimental results show that this model mining method is effective and efficient. [ABSTRACT FROM AUTHOR]

Web service composition provides a way to build value-added services and web applications by integrating and composing existing web services. In a two-stage approach for web service composition, an abstract specification is synthesized in the first phase and an executable composition process is generated in the second phase by selecting and binding a concrete web service for each abstract task. However, the selection of a web service for one task is not a stand-alone operation, as there may be compatibility conflicts between this service and services chosen for other tasks. This paper gives a method for dynamic web service selection in the presence of inter service dependencies and conflicts. Firstly, a method based on Integer Programming is discussed to implement the process of dynamic service selection. Then, inter service conflicts are explored and expressed formally, which are accommodated into the IP-based method. By combing domain specific service conflicts into a two-stage approach, the method in this paper provides a united approach for dynamic service selection that can integrate both QoS constraints and other domain specific constraints. Experiments show that this method is effective and efficient. [ABSTRACT FROM AUTHOR]

Simultaneous recording of multiple spike trains from population of neurons provides the possibility for understanding how neurons work together in response to various stimulations. But currently method is still lacking for researchers to perform multiple spike train data analysis and those existing techniques either allow people to analyze pair-wise neuronal activities only or are seriously subject to the selection of parameters. In this paper, a new measurement of information discrepancy, which is based on the comparisons of subsequence distributions, is applied to deal with a group of spike trains (n > 2) and analyze the synchronization pattern among the neurons, where the analytical result mostly depends on the experimental data and is affected little by subjective interference. [ABSTRACT FROM AUTHOR]

Process and data are two key perspectives of an SOA solution. They are usually designed relatively independently by different roles with different tools, and then linked together during the implementation phase to produce a runnable solution. It follows the separation of concerns principle to reduce development complexity, but it results in an integration gap for data access in processes, including both functional and non-functional aspects. Currently the gap is manually bridged, so that the development quality and efficiency highly depend on developers' capability. This paper proposes a novel approach to automatically bridge the gap by generating data access components whose granularity and performance are optimized according to process models. Firstly we build a platform independent process data relationship model (PDRM) based on process and data models, and then generate data access components with proper granularity by analyzing the PDRM. Furthermore, indexing technology is applied to optimize performance of data access components. Keywords: Process, Data Access Component, Granularity, Index, SOA. [ABSTRACT FROM AUTHOR]

The imperative demand on the description of semantic metadata and the processing of real-time data presents unique challenge to Grid Metadata Service. Grid Monitoring Architecture (GMA), which is a framework for dynamic data management, is limited by its conventional interface of relational database and therefore fails to address the problem of interoperability. Faced with the problem of metadata publishing in GMA, we present a new publish-harvest protocol for semantic metadata called GMA-PSMH (Grid Monitoring Architecture-Protocol for Semantic Metadata Harvesting) by modifying the OAI-PMH metadata harvest framework. As part of the Semantic Metadata Service Project in Peking University, the associated dynamic metadata management framework is then implemented according to the above protocol. At the end, we make the conclusion and overview the future work. [ABSTRACT FROM AUTHOR]

Due to the heterogeneity of network processor architectures and constantly evolving network applications, it is currently a challenge to characterize the network processor workloads. In this paper, we formally model the task-level workloads of network processors as reactive dataflow process network (RDPN). RDPN is a suitable model of computation for formally describing the behaviors of packet-level parallel processing and event interaction with control point of network processors. We extend the expressive capability of RDPN by using three transformations (i.e., clustering, decomposing and duplicating) to analyze the model and support the further design space exploration of network processors. [ABSTRACT FROM AUTHOR]

Grid provides a promising platform for the efficient execution of drug molecular docking design. Scheduling such applications is challenging for the heterogeneity, autonomy, and dynamic adaptability of grid resources. Assuming resource owners have a preemptive priority, we propose an adaptive algorithm of jobs scheduling based on time balancing strategy, which solves parallel molecular docking task by using the idle resources in the Grid. A mathematical model is developed to predict performance, which also considers systems with heterogeneous machine utilization and heterogeneous service distribution. According to the time balancing policy, ligands are partitioned into several subtasks and scheduled. The expected value of molecular docking completion time is predicted with performance model. To get better parallel computing performance, an optimal subset of heterogeneous resources with the shortest parallel executing time of tasks can be selected with the algorithm. Keywords: Molecular docking, ligand, receptor, Grid, time-balancing, jobs scheduling. [ABSTRACT FROM AUTHOR]

Metadata is the information that describes the most important feature of an object. In recent years, metadata plays a more and more important role in data intensive applications. In this paper, we propose a semantic metadata catalog service, Semantic MCS. Semantic MCS has a well-organized data management model and supports the query mechanism using Ontology inference. Furthermore, we discuss the main problems that we met in real Grid applications. We propose a framework of metadata interoperation to resolve the problem of the services interoperability. And we propose a dynamic framework for metadata management for the rapid changing metadata in Grid. [ABSTRACT FROM AUTHOR]

Text Categorization is the process of automatically assigning predefined categories to free text documents. Although there have existed a large number of text classification algorithms, most of them are either inefficient or too complex. In this paper, we propose the concept of category memberships, which stand for the degrees that words belonging to categories. Based on category memberships, a simple but efficient algorithm is presented. To evaluate our new algorithm, we have conducted experiments using Newsgroup_18828 text collection to compare it with Naive Bayes and k-NN. Experimental results show that our algorithm outperforms Naive Bayes and k-NN if a suitable category membership function is adopted. [ABSTRACT FROM AUTHOR]

We present a study on a rough set based approach for feature selection. Instead of using significance or support, Parameterized Average Support Heuristic (PASH) considers the overall quality of the potential set of rules. It will produce a set of rules with balanced support distribution over all decision classes. Adjustable parameters of PASH can help users with different levels of approximation needs to extract predictive rules that may be ignored by other methods. This paper finetunes the PASH heuristic and provides experimental results to PASH. [ABSTRACT FROM AUTHOR]

The contents and topologies of inter-document linkages, such as citations and references among scientific literature, have received increasing research interests in recent years. Some technologies have been fully studied and utilized upon this meaningful information to improve the organization, analysis and evaluation of scientific digital libraries. In this paper, we present a CiteSeer-like system to access scientific papers in computer science discipline by reference linking technique. Moreover, implicit semantics behind reference indices are mined and organized to improve accessibility of scientific papers. In order to model scientific literature and their interlinked relationships, we develop a domain-specific ontology to analyze contents and citation anchor context of scientific papers. Compared with abstract of a specific paper written by authors themselves, we introduce an automatic summary generation algorithm to create objective descriptions from other scholars' perspectives based on the ontology. Semantic queries can also be asked to discover interesting patterns in scientific libraries in order to provide a comprehensive and meaningful guidance for users. [ABSTRACT FROM AUTHOR]