Automatic navigation of mobile robots in unknown environments

Online navigation with known target and unknown obstacles is an interesting problem in mobile robotics. This article presents a technique based on utilization of neural networks and reinforcement learning to enable a mobile robot to learn constructed environments on its own. The robot learns to generate efficient navigation rules automatically without initial settings of rules by experts. This is regarded as the main contribution of this work compared to traditional fuzzy models based on notion of artificial potential fields. The ability for generalization of rules has also been examined. The initial results qualitatively confirmed the efficiency of the model. More experiments showed at least 32 % of improvement in path planning from the first till the third path planning trial in a sample environment. Analysis of the results, limitations, and recommendations is included for future work.     

Morphological, structural, and functional properties of maranta (Maranta arundinacea L) starch

Starch isolated from maranta (Maranta arundinacea) tuber and studied for its various physicochemical characteristics. The amylose content of the starch was 24.8%. SEM showed that the granules were small indented and spherical. Maranta starch granule size has a range of 2.92–6.42 μm, (mean of 4.84 μm), length/degree of 1.20, and roundness of 0.73. Maranta starch has a gelatinization temperature of 74.8°C, peak viscosity of 498 BU, and cold paste viscosity of 669 BU. It also possessed higher freeze-thaw stability. Dynamic rheological properties of maranta starch, measured using parallel plate geometry showed increased storage modulus (G’) values, while loss modulus (G″) values were decreased with increasing frequency values (0–100 Hz). The low gelatinization temperature and high freeze thaw stability of starch indicates its potential for application as a thickener in food industries.     

La0.8Sr0.2Cr0.95Ru0.05O3−x and Sm0.8Ba0.2Cr0.95Ru0.05O3−x as partial oxidation catalysts for diesel

La_0.8Sr_0.2Cr_0.95Ru_0.05O_3−x (LSCR) and Sm_0.8Ba_0.2Cr_0.95Ru_0.05O_3−x (SBCR), Ru-substituted perovskite catalysts, are investigated for the partial oxidation (POX) of diesel to produce hydrogen-rich gases for fuel cell applications. Metal-substituted perovskite materials have been investigated as reforming catalysts because the metal atoms are well-dispersed in the perovskite structure. However, Ru de-mixing and a secondary phase of LSCR and SBCR are observed after reduction at high temperature. The thermal stability, sulfur tolerance and aromatic decomposition over LSCR and SBCR are compared to those over Ru on Ce_0.9Gd_0.1O_2−x (CGO). During the thermal stability test, the catalytic activities of LSCR and SBCR improve after operating at 1000 °C. The sulfur tolerance and aromatic decomposition activity of LSCR and SBCR improve when the temperature increases to 950 °C. The improvements are attributed to the de-mixed Ru from the perovskite structure at high temperatures under a reductive atmosphere.     

Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system

Despite the proven advantages of sampling-based motion planning algorithms, their inability to handle online navigation tasks and providing low-cost solutions make them less efficient in practice. In this paper, a novel sampling-based algorithm is proposed which is able to plan in an unknown environment and provides solutions with lower cost in terms of path length, runtime and stability of the results. First, a fuzzy controller is designed which incorporates the heuristic rules of Tabu search to enable the planner for solving online navigation tasks. Then, an adaptive neuro-fuzzy inference system (ANFIS) is proposed such that it constructs and optimizes the fuzzy controller based on a set of given input/output data. Furthermore, a heuristic dataset generator is implemented to provide enough data for the ANFIS using a randomized procedure. The performance of the proposed algorithm is evaluated through simulation in different motion planning queries. Finally, the proposed planner is compared to some of the similar motion planning algorithms to support the claim of superiority of its performance.

     

Distribution and Prediction of Boundary Shear in Diverging Compound Channels

Measurement of bed shear stress is always a challenging task for engineers. In river engineering, bed shear is a fundamental variable and is important in estimating flow resistance and sediment transport. In this study, experiments are carried out in diverging compound channel with smooth bed (perspex sheet) and rough bed (Gravel) conditions to determine the effect of roughness. The shear velocity is estimated from universal logarithmic law. The effect of geometry and roughness on Von-Karman constant, eddy viscosity coefficient, friction factor is studied. The mass conservation and momentum conservation equations are used to derive apparent shear forces at interface of main channel and floodplain. A genetic algorithm model is developed to predict percentage of shear force (%Sfp) carried by sub-sections. To perform better with less and unseen data K-Fold cross-validation technique is used. The model is compared with available models in literature and it is observed that developed model gave better predictions with low MAPE.

     

Three-Dimensional Study of Multiple-Jet Cross Flow Cooling System with Single Array of Heat Sources

The objective of this study is to predict fluid flow and thermal characteristics associated with forced convection cooling of an array of heat sources mounted in a three-dimensional duct by impinging jets in the presence of cross flow. The equations governing fluid flow and heat transfer are solved using Streamline Upwind / Petrov - Galerkin based finite element method. The role of three dimensional flow structures, horseshoe vortex and counter rotating vortex pair in overall heat transfer distribution is examined. A parametric study is performed to analyze the performance of jets in cross flow for various Reynolds numbers (Re = 100, 250, 500) and velocity ratios (VR = 1.0, 5.0, 10.0). It is observed that with the increase in velocity ratio, the enhancement of heat transfer from heat sources occurs due to increase in the dominance of jet flow accompanied by an unfavorable reduction in heat transfer owing to the increase in size of horseshoe vortex. From numerical studies, it can be concluded that VR = 5.0 exhibits higher overall surface averaged Nusselt number (51.7% over VR = 1.0 and 44.1% over VR = 10.0 for Re = 500) compared to other velocity ratios considered in this study.     

超高效液相色谱法快速测定饮料中赤藓红含量

目的：建立一种简便处理样品并准确快速检测赤藓红含量的超高效液相色谱法(UPLC)。方法：色谱柱为ACQUITY UPLC BEH C18(100 mm×2.1 mm，1.7 μm)；采用二极管阵列检测器，检测波长530 nm；柱温40 ℃；流动相为乙腈—0.02 mol/L乙酸铵溶液(乙酸调节pH至6.25)；梯度洗脱：乙腈0 min—5%，2 min—25%，3 min—45%，6 min—70%，6.5 min—5%，8 min—5%；流速0.3 mL/min；进样量5 μL。待测样品加氨水调节pH至7.00，用5%乙腈水溶液溶解，超声提取30 min，过0.20 μm 滤膜后直接上机测定。结果：赤藓红标准曲线相关系数R2＞0.999，加标回收率为92%~109%，相对标准偏差(RSD)＜3.2%，检出限(LOD)为0.01 mg/L，定量限(LOQ)为0.03 mg/L。结论：该法适用于大批饮料中赤藓红含量的准确快速测定。     

钢铁企业中数字无线对讲系统设计与应用

由于无线对讲系统在钢铁企业中的应用非常广泛,而企业前期使用的均为模拟对讲机,在通话质量、传输距离、频率繁忙程度等方面已无法满足需求。因此以数字无线系统在钢铁企业中的应用测试为例,对该系统在生产过程中的应用进行了论述。该系统不但能解决模拟对讲机存在的问题,同时可在不更换设备的前提下满足企业将来扩容的需求。     

Characterizing pairwise contact patterns in human contact networks

We use a counting process representation of the pairwise contact process to analyze pairwise contact patterns. Studying two real-world traces, we find that the pairwise contact patterns have three characteristics. First, human contact patterns are influenced by daily and weekly cycles of activity. Second short time intervals with intensive contact event (bursts) are separated by long periods with few contact events. Third, the pairwise contact process exhibits long range dependence. We introduce a Markov modulated Poisson process (MMPP) as a flexible model for pairwise contact process exhibiting both regular structure and irregular bursts of activity. Using standard statistical techniques, we demonstrate that the proposed model is consistent with the empirical data. Our work has significant implication for mobility modeling and performance analysis in human contact networks.