Ultimate bearing capacity of strip footing resting on clay soil mixed with tire-derived aggregates

This study investigated the use of recycled tire-derived aggregate (TDA) mixed with kaolin as a method of increasing the ultimate bearing capacity ( UBC) of a strip footing. Thirteen 1g physical modeling tests were prepared in a rigid box of 0.6 m × 0.9 m in plan and 0.6 m in height. During sample preparation, 0%, 20%, 40%, or 60% (by weight) of powdery, shredded, small-sized granular (G 1–4 mm) or large-sized granular (G 5–8 mm) TDA was mixed with the kaolin. A strip footing was then placed on the stabilized kaolin and was caused to fail under stress-controlled conditions to determine the UBC. A rigorous 3D finite element analysis was developed in Optum G-3 to determine the UBC values based on the experimental test results. The experimental results showed that, except for the 20% powdery TDA, the TDA showed an increase in the UBC of the strip footing. When kaolin mixed with 20% G (5–8 mm), the UBC showed a threefold increase over that for the unreinforced case. The test with 20% G (1–4 mm) recorded the highest subgrade modulus. It was observed that the UBC calculated using finite element modeling overestimated the experimental UBC by an average of 9%.     

Al2O3/Yttria‐Stabilized Zirconia Hollow‐Fiber Membrane Incorporated with Iron Oxide for Pb(II) Removal

Removal by absorptive ceramic membranes can simultaneously absorb and separate metal ions from water. Alumina/yttria‐stabilized zirconia (Al₂O₃/YSZ) hollow‐fiber membranes, fabricated using phase inversion and sintering process, were deposited with iron oxide by an in‐situ hydrothermal process. The results showed that α‐Fe₂O₃ was produced and incorporated across the membranes. A reduction in flux was recorded with the deposition of α‐Fe₂O_3. However, it improved the adsorption capacity for heavy metal adsorption. The adsorption‐separation test demonstrated that the optimized membrane is able to completely remove Pb(II) ions after two hours.     

SO2 SCRUBBING BY ULTRAFINE CA(OH)2 AEROSOL

The objective of the present study was to generate submicrometer calcium hydroxide aerosols and to investigate the effectiveness of such aerosols in sulfur capture. The effectiveness of SO₂ removal by Ca(OH)₂ aerosol has been investigated in an isothermal reactor. Ca(OH) ₂ aerosol was generated by a novel fluidizer system in which submicrometer-sized powders were entrained in gases. SO₂ was added to this aerosol to a concentration of 2000 ppm. The aerosol-SO₂ mixture was heated to 550°C-750°C in an isothermal tube reactor. The SO₂ removal efficiency, which varied from 20% to 70%, was determined to be a function of the aerosol concentration, reactor temperature and residence time. The fraction of aerosol reacted was not affected strongly by the aerosol concentration. The reaction kinetics were determined from the experimental data using a simple analytical model in which the rate is first order in both SO₂ and calcium hydroxide aerosol concentrations.     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

Graft Copolymerization of Acrylamide onto Oil Palm Empty Fruit Bunch (OPEFB) Fiber

Grafting of acrylamide (AAm) onto oil palm empty fruits bunch fiber using hydrogen peroxide as initiator and methyl acrylate as comonomer was investigated. The amount of comonomer needed to make grafting of acrylamide possible was determined. The percentage of poly(acrylamide) and the comonomer in the final graft copolymer was estimated by elemental analysis. Results obtained indicated that methyl acrylate facilitated the incorporation of acrylamide monomer onto OPEFB. The reactivity ratios for both monomers were determined by using Fineman–Ross plot. The effects of reaction temperature and period as well as amount of the initiator, solvent, monomer and comonomer on the percentage of grafting at fixed amount of comonomer (11 mmol) were studied. Maximum percentage of grafting was achieved when the amount of initiator and solvent 3.98×10⁻³ mol and 50 mL respectively. The optimum reaction temperature was 50 ^○C and the reaction period was 90 min. Highest percentage of grafting was 232% when 25.6 mmol of acrylamide was used under these optimum conditions. The presence of functional group in the grafted polymer is characterized by infrared spectroscopy and the surface morphology is observed by scanning electron microscopy. Thermoanalytic investigation on OPEFB and OPEFB-g-PAAM were carried out to evaluate the thermal stability and respective activation energy of the materials.     

A survey on video content rating: taxonomy,challenges and open issues

Multimedia Tools and Applications - Rating a video based on its content is one of the most important solutions to classify videos for audience age groups. In this regard, Film content rating and TV...     

Self-generation of reward by logarithmic transformation of multiple sensor evaluations

Artificial Life and Robotics - Although the design of the reward function in reinforcement learning is important, it is difficult to design a system that can adapt to a variety of environments and...     

BASE: A bacteria foraging algorithm for cell formation with sequence data

A cellular manufacturing system (CMS) is considered an efficient production strategy for batch type production. A CMS relies on the principle of grouping machines into machine cells and grouping parts into part families on the basis of pertinent similarity measures. The bacteria foraging algorithm (BFA) is a newly developed computation technique extracted from the social foraging behavior of Escherichia coli (E. coli) bacteria. Ever since Kevin M. Passino invented the BFA, one of the main challenges has been employment of the algorithm to problem areas other than those for which the algorithm was proposed. This research work studies the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem considering the operation sequence. In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. In this paper, an attempt is made to solve the CF problem, while taking into consideration the number of voids in the cells and the number of inter-cell travels based on operational sequences of the parts visited by the machines. The BFA is suggested to create machine cells and part families. The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. The results show better performance of the proposed algorithm.     

Inchworm robot grippers for clothes manipulation

Manipulating deformable objects like clothes, plastic, and paper by a robot is very challenging. This paper focuses on clothes manipulation as an example. A tracing manipulation method is used here to find a corner of the clothes. In this paper, tracing refers to tracing the clothes’ edge, with the robot’s movement based on feedback from sensors. One difficulty during this edge tracing is to make the robot trace smoothly and speedily without dropping the clothes in the process. This is due to the fact that deformable objects are sensitive to contact forces. A solution to this problem is to design a special robot gripper that can trace the clothes without having to worry about the clothes slipping away. In this paper, the development of inchworm-type grippers is proposed. Two sets of grippers inside a robot hand will allow the robot to trace the clothes more freely because there will always be a gripper firmly holding the clothes at any time. A unique tracing method for towel spreading using the inchworm grippers is also discussed. Experimental results have demonstrated the effectiveness of both the proposed grippers and also the algorithm. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007