Understanding holistic human pose using class-specific convolutional neural network

This paper presents a method to capture human pose from individual real-world RGB images using a deep learning technique. The current works on estimating human pose by deep learning are designed in a detection or a regression framework, and in a part-based manner. As a new perspective, we introduce a classification scheme for this problem, which reasons the pose holistically. To the best of our knowledge, this is the first work for holistic human pose classification task that owes its feasibility to the great power of convolutional neural networks in feature learning. After training a convolutional neural network to classify the input image to one of the KeyPoses, the final pose is computed as a linear combination of several KeyPoses. In this new holistic classification attitude, the vast and high degree of freedom human pose space is divided into a finite number of subspaces and the convolutional neural network shows promising results in learning the features of each subspace. Empirical results (PCP and PCK rates) demonstrate that the proposed scheme is successfully able to understand human pose (i.e., predict a valid, true and coarse pose) in real-world unconstrained images with challenges like severe occlusion, high articulation, low quality and cluttered background. Furthermore, using the proposed method, the need for defining a complex model (such as appearance model or joints pairwise relations) is relieved. We have also verified a potential application of our proposed method in semantic image retrieval based on human pose.     

A multi-objective assembly line balancing problem with worker’s skill and qualification considerations in fuzzy environment

In this study a new multi-objective assembly line balancing problem is studied. Objectives like the number of stations, the equipment purchasing cost, the worker time dependent wage, and worker dependent dis-quality level of the stations is to be minimized simultaneously with worker allocation and equipment assignment possibilities. The problem also is formulated in a fuzzy environment. To solve such problem, a new hybrid fuzzy interactive approach is proposed in two stages. In the first stage, the fuzzy formulation is converted to a crisp multi-objective formulation using a credibility-based chance constrained programming approach. Then in the second stage, the obtained crisp multi-objective formulation is solved by a new hybrid fuzzy programming approach. To evaluate the proposed approach, two generated examples and a case study from garment production industries are used for computational experiments. The extensive computational study prove the superiority of the proposed approach over the well-known approaches of the literature.     

Inverse Kinematics Based Human Mimicking System using Skeletal Tracking Technology

Humanoid robots needs to have human-like motions and appearance in order to be well-accepted by humans. Mimicking is a fast and user-friendly way to teach them human-like motions. However, direct assignment of observed human motions to robot’s joints is not possible due to their physical differences. This paper presents a real-time inverse kinematics based human mimicking system to map human upper limbs motions to robot’s joints safely and smoothly. It considers both main definitions of motion similarity, between end-effector motions and between angular configurations. Microsoft Kinect sensor is used for natural perceiving of human motions. Additional constraints are proposed and solved in the projected null space of the Jacobian matrix. They consider not only the workspace and the valid motion ranges of the robot’s joints to avoid self-collisions, but also the similarity between the end-effector motions and the angular configurations to bring highly human-like motions to the robot. Performance of the proposed human mimicking system is quantitatively and qualitatively assessed and compared with the state-of-the-art methods in a human-robot interaction task using Nao humanoid robot. The results confirm applicability and ability of the proposed human mimicking system to properly mimic various human motions.     

Alkoxysilane modification of a Ti‐based catalyst system for ethylene dimerization: A step forward in enhancing productivity and selectivity

Alkoxysilanes were used as novel enhancing agents in the Ti‐based catalyst for the highly selective ethylene dimerization to butene‐1. The dimerization of ethylene was carried out using the homogeneous Ti(OBu)₄/THF/TEA/alkoxysilane catalyst system, where Ti(OBu)₄, THF (tetrahydrofuran), TEA (triethylaluminum), and alkoxysilane were used as catalyst, additive, activator, and modifier, respectively. The nature and concentration of alkoxysilanes on the dimerization rate, catalyst yield, by‐products production, and selectivity to butene‐1 were investigated in detail. It was found that the performance of alkoxysilanes assisted with the class of the Ti‐based catalyst system, developed in this work, has been furthered by high productivity and selectivity with respect to the bare catalyst system. It proved that alkoxysilanes could play an excellent improving role in the selective ethylene dimerization process. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44615.     

Extractive oxidative desulfurization of model oil/crude oil using KSF montmorillonite-supported 12-tungstophosphoric acid

12-Tungstophosphoric acid(PW) supported on KSF montmorillonite, PW/KSF, was used as catalyst for deep oxidative desulfurization(ODS) of mixed thiophenic compounds in model oil and crude oil under mild conditions using hydrogen peroxide(H_2O_2) as an oxidizing agent. A one-factor-at-a-time method was applied for optimizing the parameters such as temperature, reaction time, amount of catalyst, type of extractant and oxidant-tosulfur compounds(S-compounds) molar ratio. The corresponding products can be easily removed from the model oil by using ethanol as the best extractant. The results showed high catalytic activity of PW/KSF in the oxidative removal of dibenzothiophene(DBT) and mixed thiophenic model oil under atmospheric pressure at 75 ℃ in a biphasic system. To investigate the oxidation and adsorption effects of crude oil composition on ODS, the effects of cyclohexene, 1,7-octadiene and o-xylene with different concentrations were studied.     

Investigation and quantifying effect of dispersion on oil recovery in the process of viscoelastic polymer flooding using numerical method

In this study an existent mathematical model was implemented to investigate the effect of dispersion on oil recovery of core-flood experiments in process of viscoelastic polymer flooding as a tertiary stage of enhanced oil recovery. Discretized forms of equations of pressure, saturation, and concentrations were obtained and solved by implicit in pressure and explicit in saturation and concentrations with considering effect of time step on solution. Furthermore, a new procedure was presented to solve polymer concentration equation by trial and error. The results showed that dispersion phenomenon reduces displacement efficiency of viscoelastic polymer flooding.     

A Complete Experimental Investigation on The Rheological Behavior of Silver Oil Based Nanofluid

In this study, thermo‐physical properties including thermal conductivity, viscosity, density and specific heat capacity of an oil based nanofluid including silver as to be nanoparticles have been experimentally studied. The results indicate an enhancement in thermal conductivity which was depended on bulk temperature and volume fraction of utilized nanofluids. Viscosity data show a significant increment through volume fraction increasing. In addition, the specific heat capacity and density of nanofluids were studied experimentally and it was found that, all measured rheological properties of these nanofluids, were not in agreement to published correlations.     

Revisiting the Kellogg diagrams: roaster diagrams and their usefulness in pyrometallurgy

While predominance area diagrams (PADs) are useful for the determination of the stable phases in the metal–sulfur–oxygen system, they are constructed at constant temperature. Varying the temperature results in shifting of the equilibrium lines and the stability areas thereof. Since the available tools in hands of an extractive metallurgist are temperature and oxygen potential, a more useful diagram would be one that shows the stability areas of different phases as a function of temperature and percent of oxygen in the roast gas. Such diagrams, called ‘roaster’ diagrams, derive directly from PADs. Although such diagrams are used by extractive practitioners, this type of diagram is unavailable in the open literature. In this paper, the relationship between the PADs and roaster diagrams is discussed and PADs and roaster diagrams for the Zn–S–O and Pb–S–O ternary systems are constructed. This information will serve as the foundation for more complex four-component systems to follow in subsequent publications.     

Liquefaction assessment using microtremor measurement,conventional method and artificial neural network (Case study: Babol,Iran)

Recent researchers have discovered microtremor applications for evaluating the liquefaction potential. Microtremor measurement is a fast, applicable and cost-effective method with extensive applications. In the present research the liquefaction potential has been reviewed by utilization of microtremor measurement results in Babol city. For this purpose microtremor measurements were performed at 60 measurement stations and the data were analyzed by suing Nakmaura’s method. By using the fundamental frequency and amplification factor, the value of vulnerability index (K _g ) was calculated and the liquefaction potential has been evaluated. To control the accuracy of this method, its output has been compared with the results of Seed and Idriss [1] method in 30 excavated boreholes within the study area. Also, the results obtained by the artificial neural network (ANN) were compared with microtremor measurement. Regarding the results of these three methods, it was concluded that the threshold value of liquefaction potential is K _g = 5. On the basis of the analysis performed in this research it is concluded that microtremors have the capability of assessing the liquefaction potential with desirable accuracy.