Modeling research on manufacturing execution system based on large-scale system cybernetics

A cybernetics model of manufacturing execution system(MES CM) was proposed and studied from the viewpoint of cybernetics.Combining with the features of manufacturing system, the MES CM was modeled by"generalized modeling"method that is discussed in large-scale system theory.The mathematical model of MES CM was constructed by the generalized operator model, and the main characteristics of MES CM were analyzed.     

Multi-try counter-meshing gears discrimination device based on MEMS technology

A multi-try counter-meshing gears (CMG) discrimination device based on micro electromechani-cal system (MEMS) technology was designed for some specified information fields. The discrimination deviceconsists of two groups of metal CMG, two pawl/ratchet mechanisms, two driving micromotors and two re-setting micromotors, which make the CMG withdraw by raising the pawls. The energy-coupling element isa photoelectric sensor with a circular plate which is notched. Micromotor is fabricated using the ultravioletLiGA (UV-LiGA) fabrication process and precision mechanical engineering. The discrimination device has thefunction which can automatically reset, with the correct resetting code, it can be tried another times.     

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.     

A Discrete Bat Algorithm for Disassembly Sequence Planning

Based on the bat algorithm (BA), this paper proposes a discrete BA (DBA) approach to optimize the disassembly sequence planning (DSP) problem, for the purpose of obtaining an optimum disassembly sequence (ODS) of a product with a high degree of automation and guiding maintenance operation. The BA for solving continuous problems is introduced, and combining with mathematical formulations, the BA is reformed to be the DBA for DSP problems. The fitness function model (FFM) is built to evaluate the quality of disassembly sequences. The optimization performance of the DBA is tested and verified by an application case, and the DBA is compared with the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and differential mutation BA (DMBA). Numerical experiments show that the proposed DBA has a better optimization capability and provides more accurate solutions than the other three algorithms.     

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.     

Dynamic Behavior of Two Part Towing Cable System During Turning

An improved numerical method is used to simulate the dynamic behavior of a two part towing cable systems during turnings. In U turns and full turns, periodical heave motions are found both for the towed vehicle and for the depressor. Periodic motions of the subsea units and of the cable surface tension are closely related to the turning parameters, such as turning velocity and turning radius. System parameters, such as length of the second cable and the vehicle hydrodynamics, also damp turning instability.