Mechanical behaviors of the foot after individual releases of plantar fascia and ligaments during the balanced standing

To quantify mechanical effects of plantar fascia and ligaments on the arch structure, a 3D finite element model of the foot was created to simulate the balanced standing posture. Four cases after individual releases of plantar fascia, spring ligament, long and short plantar ligaments were simulated respectively to compare their consequences to the predictions of the intact structure. It was founded that the foot arch didn’t collapse obviously after any individual release of these structures. As plantar fascia was released, tensions of plantar ligaments were largely increased. Long and short plantar ligaments performed mutual compensation functions.     

Mesh motion approach based on spring analogy method for unstructured meshes

Mesh motion strategy is one of the key points in many fluid-structure interaction problems. One popular technique used to solve this problem is known as the spring analogy method. In this paper a new mesh update approach based on the spring analogy method is presented for the effective treatment of mesh moving boundary problems. The proposed mesh update technique is developed to avoid the generation of squashed invalid elements and maintain mesh quality by considering each element shape and grid scale to th...     

H_∞ Autopilot Design for Autonomous Underwater Vehicles

The design approach of H∞ autopilot for autonomous underwater vehicles (AUVs) is proposed. Comprised by the three sub-controllers,i.e. speed,heading and depth controllers,the designed autopilot has advantage over existing H∞ control of AUVs. The overshoot in speed,heading and depth control systems under step commands is restricted by refining the weighting function for robust stability. The dynamic performance of heading and depth control systems is improved by feeding back yaw rate and pitch angle,respecti...     

Fully secure revocable attribute-based encryption

Distributed information systems require complex access control which depends upon attributes of protected data and access policies. Traditionally, to enforce the access control, a file server is used to store all data and act as a reference to check the user. Apparently, the drawback of this system is that the security is based on the file server and the data are stored in plaintext. Attribute-based encryption (ABE) is introduced first by Sahai and Waters and can enable an access control mechanism over encrypted data by specifying the users’ attributes. According to this mechanism, even though the file server is compromised, we can still keep the security of the data. Besides the access control, user may be deprived of the ability in some situation, for example paying TV. More previous ABE constructions are proven secure in the selective model of security that attacker must announce the target he intends to attack before seeing the public parameters. And few of previous ABE constructions realize revocation of the users’ key. This paper presents an ABE scheme that supports revocation and has full security in adaptive model. We adapt the dual system encryption technique recently introduced by Waters to ABE to realize full security.     

Research on Spatially Adaptive High-Order Total Variation Model for Weak Fluorescence Image Restoration

Photoacoustic imaging acquires the absorption contrast of biological tissue with ultrasound resolution. It has been broadly investigated in biomedicine for animal and clinical studies. Recently, a micro-electro-mechanical system (MEMS) scanner has been utilized in photoacoustic imaging systems to enhance their performance and extend the realm of applications. The review provides a recap of recent developments in photoacoustic imaging using MEMS scanner, from instrumentation to applications. The topics include the design of MEMS scanner, its use in photoacoustic microscopy, miniature imaging probes, development of dual-modality systems, as well as cutting-edge bio-imaging studies.     

Full Duplex Communications for Next Generation Cellular Networks: The Capacity Gain

Full duplex communication highly improves spectrum efficiency of a wireless communication link. However, when it is applied to a cellular network, the capacity gain from this technology remains unknown. The reason is that full duplex communication changes the aggregate interference experienced by each communication link in cellular networks. In this paper, the capacity gain from full duplex communication is studied for cellular networks of 4G and beyond, where the same frequency channel is adopted in each cell. A two-layer Poisson point process (PPP) is adopted to model the network topology, and stochastic geometry is employed to derive the coverage probability and the average capacity of typical link in a cellular network. On the basis of these derived parameters, the capacity gain from full duplex communication is determined. Numerical results reveal that without mutual interference cancellation (MIC), the capacity gain is small under various power levels; with perfect MIC at base stations, the capacity gain can exceed 60%; with imperfect MIC at base stations, the capacity gain decreases quickly even with a slight drop of MIC performance.     

Optimal Threshold Policies for Robust Data Center Control

With the simultaneous rise of energy costs and demand for cloud computing, efficient control of data centers becomes crucial. In the data center control problem, one needs to plan at every time step how many servers to switch on or off in order to meet stochastic job arrivals while trying to minimize electricity consumption. This problem becomes particularly challenging when servers can be of various types and jobs from different classes can only be served by certain types of server, as it is often the case in real data centers. We model this problem as a robust Markov decision process (i.e., the transition function is not assumed to be known precisely). We give sufficient conditions (which seem to be reasonable and satisfied in practice) guaranteeing that an optimal threshold policy exists. This property can then be exploited in the design of an efficient solving method, which we provide. Finally, we present some experimental results demonstrating the practicability of our approach and compare with a previous related approach based on model predictive control.     

Estimation of Load-Induced Damage and Repair Cost in Post-Tensioned Concrete Rocking Walls

Post-tensioned concrete rocking walls might be used to avoid severe seismic damage at the base of structural walls, decrease residual drift, and lessen post-earthquake repair costs. The prediction of load-induced damage to the rocking wall resulting from seismic loading can provide an extremely valuable tool to evaluate the status and safety of structural concrete walls following earthquakes. In this study, the behavior and the damage state of monolithic, self-centering, rocking walls, as a new type of concrete rocking wall, are investigated. The nonlinear mechanical behavior of the wall is first modeled numerically, and subsequently the mechanical parameters from the numerical simulation are used to generate the local damage index. The results from the damage index model are compared with the full-scale test results, confirming the viability of the numerically based damage index method for estimating the seismically induced damage in concrete walls. Moreover, the estimated damage can be utilized as a qualitative and quantitative scale to assess the status of the wall following seismic loading events. Finally, an equation is proposed to estimate the repair cost based on the predicted damage state for the studied structural system.     

Decomposing and Cluster Refinement Design Method for Application-Specific Network-on-Chips

Along with higher and higher integration of intellectual properties (IPs) on a single chip, traditional bus-based system-on-chips (SoC) meets several design difficulties (such as low scalability, high power consumption, packet latency and clock tree problem). As a promising solution, network-on-chips (NoC) has been proposed and widely studied. In this work, a novel algorithm for NoC topology synthesis, which is decomposing and cluster refinement (DCR) algorithm, has been proposed to minimize the total power consumption of application-specific NoC. This algorithm is composed of two stages: decomposing with cluster generation, and cluster refinement. For partitioning and cluster generation, an initial low-power solution for NoC topology is generated. For cluster refinement, the clustering is optimized by performing floorplan to further reduce power consumption. Meanwhile, a good tradeoff between power consumption and CPU time can be achieved. Experimental results show that the proposed method outperforms the existing work.     

Research on Web Page Classification Method Based on Query Log

Web page classification is an important application in many fields of Internet information retrieval, such as providing directory classification and vertical search. Methods based on query log which is a light weight version of Web page classification can avoid Web content crawling, making it relatively high in efficiency, but the sparsity of user click data makes it difficult to be used directly for constructing a classifier. To solve this problem, we explore the semantic relations among different queries through word embedding, and propose three improved graph structure classification algorithms. To reflect the semantic relevance between queries, we map the user query into the low-dimensional space according to its query vector in the first step. Then, we calculate the uniform resource locator (URL) vector according to the relationship between the query and URL. Finally, we use the improved label propagation algorithm (LPA) and the bipartite graph expansion algorithm to classify the unlabeled Web pages. Experiments show that our methods make about 20% more increase in F1-value than other Web page classification methods based on query log.