A hybrid controller based on CPG and ZMP for biped locomotion

Biped locomotion has attracted much attention in recent years. The most successful implemented methods in this area are based on two approaches, central pattern generator (CPG) and zero moment point (ZMP). Unfortunately, neither of these concepts can solely solve the movement challenge completely. In this study, we introduce a hybrid controller to combine the advantages of these methods. The proposed controller is based on two major approaches, CPG and ZMP. This hybrid controller is composed of a trajectory control system and a trajectory generator system. The trajectory control system applied to keep the robot stable uses ZMP as a real time control feedback. The trajectory generator system, which is composed of nonlinear oscillators, generates stable motions. The parameters of CPG are tuned by a new two-stage approach using differential evolution (DE) and bees algorithm (BA). Furthermore, performance of the proposed controller is verified using the robotic simulation software Webots.     

A combined additive manufacturing and micro-syringe deposition technique for realization of bio-ceramic structures with micro-scale channels

This article presents a novel rapid layered manufacturing approach based on a combined additive manufacturing (AM) process and a UV-based micro-syringe deposition (μSD) technique to be used in the fabrication of bio-ceramic structures with controlled micro-sized channels for bone and osteochondral tissue regeneration. In the proposed rapid manufacturing method, micro-scale sacrificial photopolymer networks are integrated within the manufactured part by depositing the photopolymer on selected bio-ceramic powder layers using an injection system. This AM–μSD method along with a post-processing protocol can potentially overcome current limitations of traditional powder-based AM approaches that are restricted in terms of complexity of internal architecture and feature size. For bone or osteochondral repair applications, the material system composed of the bio-ceramic and sacrificial photopolymer, along with the post-processing protocol, must ensure that the final implants are free from manufacturing residuals that could trigger an immune response post-implantation. In this study, calcium polyphosphate bio-ceramic was used as the substrate material based on prior art, polyvinyl alcohol solution was used as the powder binding agent, and ethoxylated (10 bisphenol A diacrylate) photopolymer solution was used as the sacrificial photopolymer element. Material characterization suggests that the proposed material system along with heat treatment protocol is suitable for the targeted applications where micro-scale channels within the implant are produced by AM–μSD.     

Pipe Break Rate Assessment While Considering Physical and Operational Factors: A Methodology based on Global Positioning System and Data-Driven Techniques

An accurate prediction of pipes failure rate plays a substantial role in the management of Water Distribution Networks (WDNs). In this study, a field study was conducted to register pipes break and relevant causes in the WDN of Yazd City, Iran. In this way, 851 water pipes were incepted and localized by the Global Positioning System (GPS) apparatus. Then, 1033 failure cases were reported in the eight zones of understudy WDN during March-December 2014. Pipes break rate (BR_P) was calculated using the depth of pipe installation (h_P), number of failures (N_P), the pressure of water pipes in operation (P), and age of pipe (A_P). After completing a pipe break database, robust Artificial Intelligence models, namely Multivariate Adaptive Regression Spline (MARS), Gene-Expression Programming (GEP), and M5 Model Tree were employed to extract precise formulation for the pipes break rate estimation. Results of the proposed relationships demonstrated that the MARS model with Coefficient of Correlation (R) of 0.981 and Root Mean Square Error (RMSE) of 0.544 provided more satisfying efficiency than the M5 model (R?=?0.888 and RMSE?=?1.096). Furthermore, statistical results indicated that MARS and GEP models had comparatively at the same accuracy level. Explicit equations by Artificial Intelligence (AI) models were satisfactorily comparable with those obtained by literature review in terms of various conditions: physical, operational, and environmental factors and complexity of AI models. Through a probabilistic framework for the pipes break rate, the results of first-order reliability analysis indicated that the MARS technique had a highly satisfying performance when MARS-extracted-equation was assigned as a limit state function.

     

Design of CO2 absorption plant for recovery of CO2 from flue gases of gas turbine

The ongoing human-induced emission of carbon dioxide (CO₂) threatens to change the earth's climate. A major factor in global warming is CO₂ emission from thermal power plants, which burn fossil fuels. One possible way of decreasing CO₂ emissions is to apply CO₂ removal, which involves recovering of CO₂ from energy conversion processes. This study is focused on recovery of CO₂ from gas turbine exhaust of Sarkhun gas refinery power station. The purpose of this study is to recover the CO₂ with minimum energy requirement. Many of CO₂ recovery processes from flue gases have been studied. Among all CO₂ recovery processes which were studied, absorption process was selected as the optimum one, due to low CO₂ concentration in flue gas. The design parameters considered in this regard, are: selection of suitable solvent, solvent concentration, solvent circulation rate, reboiler and condenser duty and number of stages in absorber and stripper columns. In the design of this unit, amine solvent such as, diethanolamine (DEA), diglycolamine (DGA), methyldiethanolamine (MDEA), and monoethanolamine (MEA) were considered and the effect of main parameters on the absorption and stripping columns is presented. Some results with simultaneous changing of the design variables have been obtained. The results show that DGA is the best solvent with minimum energy requirement for recovery of CO₂ from flue gases at atmospheric pressure.     

Functionally Graded,Bone‐ and Tendon‐Like Polyurethane for Rotator Cuff Repair

Critical considerations in engineering biomaterials for rotator cuff repair include bone‐tendon‐like mechanical properties to support physiological loading and biophysicochemical attributes that stabilize the repair site over the long‐term. In this study, UV‐crosslinkable polyurethane based on quadrol (Q), hexamethylene diisocyante (H), and methacrylic anhydride (M; QHM polymers), which are free of solvent, catalyst, and photoinitiator, is developed. Mechanical characterization studies demonstrate that QHM polymers possesses phototunable bone‐ and tendon‐like tensile and compressive properties (12–74 MPa tensile strength, 0.6–2.7 GPa tensile modulus, 58–121 MPa compressive strength, and 1.5–3.0 GPa compressive modulus), including the capability to withstand 10 000 cycles of physiological tensile loading and reduce stress concentrations via stiffness gradients. Biophysicochemical studies demonstrate that QHM polymers have clinically favorable attributes vital to rotator cuff repair stability, including slow degradation profiles (5–30% mass loss after 8 weeks) with little‐to‐no cytotoxicity in vitro, exceptional suture retention ex vivo (2.79–3.56‐fold less suture migration relative to a clinically available graft), and competent tensile properties (similar ultimate load but higher normalized tensile stiffness relative to a clinically available graft) as well as good biocompatibility for augmenting rat supraspinatus tendon repair in vivo. This work demonstrates functionally graded, bone‐tendon‐like biomaterials for interfacial tissue engineering.     

Surgical tool motion during conventional freehand and robot-assisted microsurgery conducted using neuroArm

Surgical tool motion during microsurgery could arguably reflect surgical performance. This paper reports on how the motion of a surgical tool correlates or differs between conventional freehand surgery and robot-assisted surgery. In this pilot study, components of the position and orientation as well as the linear and angular velocities of a surgical tool, over the same period of operation, are compared during the two scenarios. For freehand surgery, a bipolar forceps is retrofitted with a tracking system to measure translational and rotational components of the tool motion. In robot-assisted surgery, the position and orientation components are obtained using kinematics of the neuroArm image-guided robotic system. A cross correlation analysis was used to investigate correlation between each pair of displacement or velocity components from freehand and robot-assisted scenarios to indicate how strongly or weakly two sets of data are linked together. The absolute maximum value of the cross correlation coefficient is calculated for each pair of components to quantitatively investigate the correlation between two sets of data. Results showed that the positional and rotational components, reflecting the surgical workspace, in both scenarios are correlated. However, for the cases studied, surgical tool rate of motion differs between the two scenarios. Results are important as they can be utilized to design robot-assisted neurosurgical systems that reflect characteristics of freehand surgery gained by surgeons through years of training, knowledge, and experience.     

Translation with Scarce Bilingual Resources

Machine translation of human languages is a field almost as old as computers themselves. Recent approaches to this challenging problem aim at learning translation knowledge automatically (or semi-automatically) from online text corpora, especially human-translated documents. For some language pairs, substantial translation resources exist, and these corpus-based systems can perform well. But for most language pairs, data is scarce, andcurrent techniques do not work well. To examine the gap betweenhuman and machine translators, we created an experiment in which humanbeings were asked to translate an unknown language into English on thesole basis of a very small bilingual text. Participants performed quite well,and debriefings revealed a number of valuable strategies. We discuss thesestrategies and apply some of them to a statistical translation system.     

Learned Models for Estimation of Rigid and Articulated Human Motion from Stationary or Moving Camera

We propose an approach for modeling, measurement and tracking of rigid and articulated motion as viewed from a stationary or moving camera. We first propose an approach for learning temporal-flow models from exemplar image sequences. The temporal-flow models are represented as a set of orthogonal temporal-flow bases that are learned using principal component analysis of instantaneous flow measurements. Spatial constraints on the temporal-flow are then incorporated to model the movement of regions of rigid or articulated objects. These spatio-temporal flow models are subsequently used as the basis for simultaneous measurement and tracking of brightness motion in image sequences. Then we address the problem of estimating composite independent object and camera image motions. We employ the spatio-temporal flow models learned through observing typical movements of the object from a stationary camera to decompose image motion into independent object and camera motions. The performance of the algorithms is demonstrated on several long image sequences of rigid and articulated bodies in motion.     

Phase I Control of Simple Linear Profiles with Individual Observations

Most of the existing literature on phase I control of simple linear profiles requires multiple observations because the profile parameters need to be estimated given each subgroup of observations. Such a requirement may not be attainable in practical applications in that the observations collected in phase I for assessing whether the process is in control and estimating the profile parameters may not necessarily follow what is prescribed by the existing phase I methods. This is particularly the case for processes in which only few observations or a single observation per subgroup can be obtained for phase I control. In this work, a control charting mechanism based on a change‐point model is proposed for phase I control of simple linear profiles with individual observations. The proposed charting mechanism consists of two control charts. The first control chart, which is essentially based on a likelihood ratio test, is used to monitor the profile parameters. The error standard deviation is monitored using a second control chart, which is constructed on the basis of the recursive residuals. Simulation results show that the control charting mechanism is effective in detecting sustained changes in the profile parameters and/or error standard deviation. The proposed phase I control charting mechanism is used in an application to demonstrate how the proposed control charts can be applied in practice. Copyright © 2012 John Wiley & Sons, Ltd.     

Improving the performance of the needleman-wunsch algorithm using parallelization and vectorization techniques

The Needleman-Wunsch (NW) is a dynamic programming algorithm used in the pairwise global alignment of two biological sequences. In this paper, three sets of parallel implementations of the NW algorithm are presented using a mixture of specialized software and hardware solutions: POSIX Threads-based, SIMD Extensions-based and a GPU-based implementations. The three implementations aim at improving the performance of the NW algorithm on large scale input without affecting its accuracy. Our experiments show that the GPU-based implementation is the best implementation as it achieves performance 72.5X faster than the sequential implementation, whereas the best performance achieved by the POSIX threads and the SIMD techniques are 2X and 18.2X faster than the sequential implementation, respectively.