A hybrid Jacobian control for uncalibrated robot visual servoing

Visualservocontrolhasbeenanactiveareaofre searchformanyyears.Since1973,therehasbeen significantprogressonvisualservoingcontrol[1],and severalspecialissuesonvisualservoinghavebeen published[2,3].Therearetwobasicapproachestovi sualservocontrol[1]:Position BasedVisualServoing(PBVS)andImage BasedVisualServoing(IBVS).InPBVSsystem,theobject’s3Dposeisrecovered throughcomputervisionandtheerrorbetweenthe currentposeandthedesiredposeiscomputedinthe Cartesiantaskspace.Estimationof3Dmotionsfrom…     

A buffering method for quadruped robots based on active impedance control①

Compared with wheeled or tracked robots , legged robots exhibit advantages on agile locomotion and higher survival chance for deadly impacts .A buffering strategy is proposed for quadruped robots with non-extreme initial attitudes from the end of air-righting to the steady standing on the ground . This approach consists of landing phase , buffering phase and recovering phase .The variable stiff-ness control, proportional-derivative(PD) force control and foot trajectory planning are applied to the joints of quadruped robots until the end of the recovering phase .The PD parameters are tuned according to the desired performance of each phase .The above approach is verified on a virtual plat-form.     

A visual awareness pathway in cognitive model ABGP①

The cognitive model ABGP is a special model for agents , which consists of awareness , beliefs, goals and plans .The ABGP agents obtain the knowledge directly from the natural scenes only through some single preestablished rules like most agent architectures .Inspired by the biological vis-ual cortex ( V1 ) and the higher brain areas perceiving the visual feature , deep convolution neural networks ( CNN) are introduced as a visual pathway into ABGP to build a novel visual awareness module .Then a rat-robot maze search simulation platform is constructed to validate that CNN can be used for the awareness module of ABGP .According to the simulation results , the rat-robot imple-mented by the ABGP with the CNN awareness module reaches the excellent performance of recogniz-ing guideposts , which directly enhances the capability of the communication between the agent and the natural scenes and improves the ability to recognize the real world , which successfully demon-strates that an agent can independently plan its path in terms of the natural scenes .     

A novel endorectal RF coil for high resolution MRI and spectroscopy of the prostate

The diagnosis of prostate diseases by magnetic resonance imaging (MRI) in vivo is sometimes difficult for the lower signal to noise ratio (SNR). To increase the SNR of the prostate image, we designed a RF coil that can be inserted into rectum and was named endorectal coil. The properties of RF coil were evaluated using a network analyzer. Moreover the images and spectroscopy of a special phantom were acquired and the results were compared to those of the commercial TORSO coil (G.E. Medical Systems, USA). Our coil gave a significantly higher SNR at the region of interest (ROI). The achieved high local SNR and resulting high spatial resolution would add more anatomic and biochemical information to the diagnosis of prostate diseases.     

A novel algorithm of artificial immune system for high-dimensional function numerical optimization

Based on the clonal selection theory and immune memory theory, a novel artificial immune system algorithm, immune memory clonal programming algorithm (IMCPA), is put forward. Using the theorem of Markov chain, it is proved that IMCPA is convergent. Compared with some other evolutionary programming algorithms (like Breeder genetic algorithm), IMCPA is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like high-dimensional function optimization, which maintains the diversity of the population and avoids prematurity to some extent, and has a higher convergence speed.     

A novel method for evaluating and improving the 1H-MRSI glioma data quality

Metabolic information obtained by proton magnetic resonance spectroscopic imaging (1H-MRSI) has been approved to be a powerful tool to identify either benign or malignant glioma, as well as to confirm the tumor level. However, 1H-MRSI data are affected by various factors, such as the thermal noise, eddy currents, susceptibility artifacts, and rigid body motion. To get accurate quantitative metabolic information, the key problem is to assess the 1H-MRSI data quality. In this paper, we introduce a new evaluating system to filter the data, and a new method, called wavelet denoising method, to improve the data quality under the evaluating system. Experimental results on 1H-MRSI glioma data demonstrate that preprocessing is prerequisite and the proposed algorithm with evaluating system is effective.     

A novel dynamic frame rate control algorithm for H.264 low-bit-rate video coding

The goal of this paper is to improve human visual perceptual quality as well as coding efficiency of H. 264 video at low bit rate conditions by adaptively adjusting the number of skipped frames. The encoding frames are selected according to the motion activity of each frame and the motion accumulation of successive frames. The motion activity analysis is based on the statistics of motion vectors and with consider- ation of the characteristics of H. 264 coding standard. A prediction model of motion accumulation is pro- posed to reduce complex computation of motion estimation. The dynamic encoding frame rate control algorithm is applied to both the frame level and the GOB （Group of Macroblocks ） level. Simulation is done to compare the performance of JM76 with the proposed frame level scheme and GOB level scheme.     

A mathematical model for solid liquid and mass transfer coupling and numerical simulation for hydraulic fracture in rock salt

The hydraulic fracture in rock salt is a complicated solid fluid and mass transfer coupling process. Through theoretical analysis, a solid fluid and mass transfer coupling mathematical model of hydraulic fracture in rock salt is established in this work, and numerical simulations are carried out with the model. The simulation results indicate that rock salt cracks in the typical way of wing-crack(or tensile crack) during the fracture, and the relation of fracture aperture (w) with expanding distance (x) and fracture time (t) is w＝(0.0034＋0.0006t)e(0.0007+0.0018t)x. Furthermore, it has been found that both the water pressure in the crack and the expanding velocity of the crack decrease gradually as a result of the influence of salt dissolving during fracturing. These numerical simulations well illustrate the process of hydraulic fracture in rock salt and are significantly meaningful in engineering practice.     

Impact chaos control and stress release? -A key for development of ultra fine vibration milling

Through our previous experimental and analytical studies, it has been discovered that the key for the development of vibration milling is the impact chaos control and stress release. The necessities for the chaos control and stress release are: (i) to strictly eliminate the sub-harmonics; (ii) to control the super-harmonics to a lower level and (iii) to load the system compressively with relatively higher period, in order that the vibration energy can be absorbed by the particles effectively and sufficiently. A new vibration model for ultra fine milling is proposed, which has wide applications in preparing ultra fine particles.     

H∞ control for uncertain Markovian jump systems with mode-dependent mixed delays

We study the problem of H_∞ control for a class of Markovian jump systems with norm-bounded parameter uncertainties and modedependent mixed delays including discrete delays and distributed delays in this paper. Our aim is to present a new delay-dependent control approach such that the resulting closed-loop system is robust mean-square (MS) exponentially stable and satis?es a prescribed H_∞ performance level, irrespective of the parameter uncertainties. Such delay-dependent approach does not require system transformation or free-weighting matrix. A numerical example shows that the results are less conservative and more e?ective.     

Node ordinal encoded genetic algorithm for the optimal allocation of water resources

A new method, node ordinal encoded genetic algorithm (NOEGA), is proposed for solving water resources optimal allocation problems, in which the capacity of water resources is split into a number of smaller parts so that successive operations can be overlapped. Our objective is to maximize the whole benefit function. To overcome the “dimensionality and algorithm complexity curse” while searching for solutions and looking for an optimal solution, the operations of one-point crossover operator, gene exchange operator, gene random operator, gene shift operator and node ordinal strings are established. It is proved to be an effective optimal method in searching for global solutions. The NOEGA does not need a diversity of initial population, and it does not have the problem of immature convergence. The results of two cases show that using NOEGA to solve the optimal allocation model is very efficient and robust. In addition, the algorithm complexity of NOEGA is discussed.     

Improvement of different source function expressions in SWAN model for the Bohai Sea

The simulating wave nearshore (SWAN) wave model has been widely used in coastal areas, lakes and estuaries. However, we found a poor agreement between modeling results and measurements in analyzing the chosen four typical cases when we used the default parameters of the source function formulas of the SWAN to make wave simulation for the Bohai Sea. Also, it was found that at the same wind process the simulated results of two wind generation expressions (Komen, Janssen) demonstrated a large difference. Further study showed that the proportionality coefficient α in linear growth term of wave growth source function plays an unperceived role in the process of wave development. Based on experiments and analysis, we thought that the coefficient α should change rather than be a constant. Therefore, the coefficient α changing with the variation of friction velocity U* was introduced into the linear growth term of wave growth source function. Four weather processes were adopted to validate the improvement in the linear growth term. The results from the improved coefficient α agree much better with the measurements than those from the default constant coefficient α. Furthermore, the large differences of results between Komen wind generation expression and Janssen wind generation expression were eliminated. We also experimented with the four weather processes to test the new white-capping mechanisms based on the cumulative steepness method. It was found that the parameters of the new white-capping mechanisms are not suitable for the Bohai Sea, but Alkyon's white-capping mechanisms can be applicable to the Bohai Sea after amendments, demonstrating that this improvement of parameter α can improve the simulated results of the Bohai Sea.     

A novel hybrid CDL-based multipath propagation model for the high-speed railway at 2.35 GHz

In this study, based on the actual channel measurements of the high-speed railway （HSR） in a via- duct scenario at 2.35 GHz, a hybrid cluster delay line （CDL） channel modeling technology which combines a statistical model and a theoretical model is proposed. This novel channel-characterization approach is used to reveal the statistical properties for ＂random＂ scattering and to provide a geometric mechanism for computing the time- variant paths for ＂periodically moving＂ scattering. Using a modified clustering algorithm in the delay domain, the inter-cluster and intra-cluster characteristics against the distance between the transmitter and the receiver were extracted and analyzed. In addition, the measurement results were compared with some conclusions from other measurement studies, and the proposed channel model was validated by comparing the simulated results with the measurement data. The study results provide a useful technique for the evaluation and verification of wireless communications in the HSR environment.     

Variation of the FeMn ratio of ferromanganese crusts from the Central North Pacific: implication for paleoclimate changes

Contents of Fe, Mn and other elements in four ferromanganese crusts recovered from the central North Pacific are analyzed at high depth-resolution by electron microprobe for reconstructing factors controlling their deposition. Manganese (IV) in hydrogenetic ferromanganese crusts is mainly supplied as colloidal precipitates from the Oxygen Minimum Zone (OMZ), which concentrates high amounts of dissolved Mn (II). The iron is derived from carbonate dissolution and silicate particles of eolian dust. An increase in paleoproductivity during cooler climate would potentially lead to a decrease in Mn deposition due to enlargement of the OMZ which has a “temporary storage” effect for Mn. On the other hand, not affected by the OMZ, the iron entering the Fe-Mn crust would likely increase with the eolian dust input and surface productivity at glacial stages. As a result, the increasing FeMn ratio should indicate a cooling climate. This is supported by the following observations. In the profile of the past 1 Ma, the variations of FeMn ratio coincide with benthic oxygen isotope fluctuation in glacial-interglacial cycles. Three episodes with high FeMn ratios, approximately at 2.6, 1.8 and 0.8 Ma, are detected within the past 3 Ma and coincide with major climate transitions and cooling events. The secular evolution pattern of FeMn ratio in the Cenozoic is similar to the Pb isotope evolution which is mainly controlled by eolian dust and related to climate. The FeMn evolution pattern is also broadly consistent with the global deep-sea oxygen isotope records. Therefore, FeMn ratio recorded in the ferromanganese crusts may be a new proxy for climate change.