Development of a multi-behavior based mobile robot for remotesupervisory control through the Internet

We review the networked mobile robot systems and suggest taxonomy based on the three levels of control commands. The performance analysis result shows that direct control has potential difficulty for implementation due to the unpredicted transmission delay of the network. To tackle this problem, we have suggested the behavior-programming control concept to avoid disturbances of the Internet latency. For this purpose, primitive local intelligence of the mobile robot is grouped into motion planner, motion executor, and motion assistant, where each of a group is treated as an agent. They are integrated by centralized control architecture based on multi-agent concept, communicated through a center information memory. The event-driven concept is applied on the robot to switch the behaviors to accommodate the unpredicted mission autonomously. We have successfully demonstrated experimentally the feasibility and reliability for system through a performance comparison with direct remote control     

Raman,X-ray and electrical properties of MOD PZT/PLZT thin films

Abstract

Ferroelectric PZT/PLZT thin films have been fabricated using the metallo-organic precursor compounds. The structural development, spectroscopic and dielectric properties of these films have been investigated using atomic force microscopy (AFM), X-ray diffraction, Raman scattering and dielectric measurements. Experimental results show that Raman spectroscopy is an effective tool of monitoring the structural development of the small sized PZT films in the tetragonal phase field. Dielectric characteristics have been improved by the rapid thermal processing approach. A rosette growth model is proposed to explain the observation of the tri-intersection of the perovskite phase in PZT films.     

Intrinsic hardness of crystalline solids

The current status of various theoretical approaches to the “prediction” of material hardness has been reviewed. It is shown that the simple empirical correlation with the shear moduli generally provide very good estimates of the Vickers hardness. Semi-empirical models based solely on the strength of the chemical bonds, although performed as well, are theoretically incomplete. First-principles calculations of the ideal stress and shear strength is perhaps the most reliable and theoretically sound approach available to compare theoretical predictions with experiment.     

利用改进Rayleigh商逆迭代法进行大系统特定模式降阶

对大系统特定模式进行降阶计算.依据特征值灵敏度对系统状态矩阵A重新排序,仅保留与特定模式强相关的发电机组,使矩阵维数得以降低.由于降阶后矩阵一般为复数形式,把矩阵虚部作为实部的修正量.以实部的特定特征值作为初值,用改进Rayleigh商逆迭代格式准确计算.算例分析验证了该方法的有效性.     

Pressure Sensitive Adhesives Based on VectorR SIS Polymers I. Rheological Model and Adhesive Design Pathways

Dexco Polymers (a Dow/Exxon partnership) has been manufacturing Vector^R SIS polymers since 1990.¹ This paper describes experiments carried out to study Vector SIS polymers and model pressure sensitive adhesive (PSA) formulations based on Exxon Chemical's Escorez^R 1310LC tackifier. The adhesive behavior of tackified polymers was quantitatively analyzed by applying the rheological principle of time-temperature superposition² and the mapping approach,^3,4 and the pressure sensitive rheological model⁵ developed earlier. This model⁵ was developed by expanding and modifying an equation [adhesive fracture strength = (intrinsic adhesion) × (bulk energy dissipation)] proposed by Gent et al.^6,7 and Andrews et al.^8,9 This study delivers two key results. The first is that the fracture strength of the PSA/steel bond is the multiplication of three terms: the intrinsic (or interfacial) adhesion, the bonding and the debonding terms (Fig. 1). The debonding term is correlated with the logarithm of the loss modulus at the PSA debonding frequency or with the logarithm of the monomeric friction coefficient of the block copolymer/tackifier system. Both the loss modulus and the monomeric friction coefficient measure the energy dissipation in the bulk adhesive. The second is that PSA design pathways can be established by a mapping approach in the rheological space of the plateau modulus versus the loss modulus peak position in the frequency scale (Fig. 2). Plateau modulus is the bonding parameter because it measures the wetting capability of the adhesive with the substrate surface. The loss modulus peak position is the debonding parameter because it corresponds approximately to the time scale (or the frequency scale) in which one deforms the adhesive to maximize energy dissipation. Therefore, the tackifier and oil combination lowers the plateau modulus, but increases the T_g of the polyisoprene phase of the SIS polymer. This increase in T_g is equivalent to the lowering of the rate of local rearrangement (frequency of segment jumps) of the polyisoprene chains of the block copolymer. An optimal “tackification pathway” in this rheological space is achieved by tailoring the tackifier type and T_g, and the amount of oil used in the PSA.

In brief, the PSA rheological model and mapping approach described in this work for Vector SIS polymers give a comprehensive understanding and adhesive design pathways. This concept and approach not only allow raw material suppliers to improve and design better tackifier and polymer products, but also provide PSA formulators a quantitative tool to achieve PSA end property results.     

Comparison of the homogeneous and the heterogenizing homogeneous Co3+ catalyst in the synthesis of organic peroxides

Abstract

Comparison of the homogeneous and heterogenizing homogeneous cobalt ion catalyst in the synthesis of organic peroxides was studied. The heterogenizing or immobilizing homogeneous cobalt ion catalyst was prepared by ion exchange of the cobalt ion on a polymer support. Acetaldehyde was used as the model compound for the comparison of the homogeneous and the heterogenizing homogeneous catalyst. The results indicate that both the selectivity and yield of peracetic acid by using the heterogenizing homogeneous catalyst is higher than that of using a homogeneous catalyst. The comparison of the reaction mechanism as well as the kinetics of using these two types of catalysts were also obtained.     

A contour propagation approach to surface filling-in and volume formation.

A new approach to surface and volume formation is introduced in response to the question, "Why do some silhouettes look 3 dimensional (3D) and others took 2D?" The central idea is that form information can propagate away from a "propagable segment" (PS) of occluding contour that could have projected onto the image from the visible portion of a cross-section of a surface. A key property of a PS is that it exhibits abrupt curvature changes where it meets the rest of the occluding contour. An algorithm is described for filling in curved surfaces from a PS: When copies of a PS are propagated into the interior, they act as cross-sectional surface contours that also exhibit abrupt curvature changes with the rest of the occluding contour. The result is a nonmetric coding of 3D-shape in terms of local ordinal surface curvature and orientation relationships that is scale, translation, and rotation invariant. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Mutations in the reduced folate carrier gene which confer dominant resistance to 5,10-dideazatetrahydrofolate

L1210/D3 mouse leukemia cells are resistant to 5, 10-dideazatetrahydrofolate due to expansion of cellular folate pools which block polyglutamation of the drug (Tse, A., and Moran, R. G. (1998) J. Biol. Chem. 273, 25944-25952). These cells were found to have two point mutations in the reduced folate carrier (RFC), resulting in a replacement of isoleucine 48 by phenylalanine and of tryptophan 105 by glycine. Each mutation contributes to the resistance phenotype. Genomic DNA from resistant cells contained both the wild-type and mutant alleles, but wild-type message was not detected. Folic acid was a much better substrate, and 5-formyltetrahydrofolate was a poorer substrate for transport in L1210/D3 cells relative to L1210 cells. Enhanced transport of folic acid was due to a marked, approximately 20-fold, decrease in the influx Km. Influx of methotrexate and 5,10-dideazatetrahydrofolate were minimally altered. Transfection of mutated rfc cDNA into RFC-null L1210/A cells produced the substrate specificity and 5, 10-dideazatetrahydrofolate resistance observed in the L1210/D3 line. Transfection of the mutant cDNA into wild-type cells also conferred resistance to 5,10-dideazatetrahydrofolate. We conclude that the I48F and W105G mutations in RFC caused resistance to 5, 10-dideazatetrahydrofolate, that the region of the RFC protein near these two positions defines the substrate-binding site, that the wild-type allele was silenced during the multistep development of resistance, and that this mutant phenotype represents a genetically dominant trait.     

EClass: An execution classification approach to improving the energy-efficiency of software via machine learning

Energy efficiency at the software level has gained much attention in the past decade. This paper presents a performance-aware frequency assignment algorithm for reducing processor energy consumption using Dynamic Voltage and Frequency Scaling (DVFS). Existing energy-saving techniques often rely on simplified predictions or domain knowledge to extract energy savings for specialized software (such as multimedia or mobile applications) or hardware (such as NPU or sensor nodes). We present an innovative framework, known as EClass, for general-purpose DVFS processors by recognizing short and repetitive utilization patterns efficiently using machine learning. Our algorithm is lightweight and can save up to 52.9% of the energy consumption compared with the classical PAST algorithm. It achieves an average savings of 9.1% when compared with an existing online learning algorithm that also utilizes the statistics from the current execution only. We have simulated the algorithms on a cycle-accurate power simulator. Experimental results show that EClass can effectively save energy for real life applications that exhibit mixed CPU utilization patterns during executions. Our research challenges an assumption among previous work in the research community that a simple and efficient heuristic should be used to adjust the processor frequency online. Our empirical result shows that the use of an advanced algorithm such as machine learning can not only compensate for the energy needed to run such an algorithm, but also outperforms prior techniques based on the above assumption.