Non-iterative parameter estimation of the 2R-1C model suitable for low-cost embedded hardware

Frontiers of Information Technology & Electronic Engineering - Parameter estimation of the 2R-1C model is usually performed using iterative methods that require high-performance processing...     

Tone-Based Contention Resolution for Multi-hop Wireless Sensor Networks

Wireless Personal Communications - Medium access control protocols with common active period (AP MACs) are frequently used in wireless sensor networks (WSNs) with medium-load traffic requirements....     

Steering rules for AGV based on primitive function and elementary movement control

The complete structure of an AGV control system is described in the first part of this paper. The AGV control system is hierarchical and consists of five levels. The structure of one level does not depend on the structures of the other levels. This means that the control system depends on the design of the AGV at the lowest level only, at the actuator servo-control level and its coordination in realizing AGV primitive functions.The second part of the paper describes rules applicable to AGV steering. The structure of these rules depends on two groups of factors. The first group is dependent on information groups fed to the AGV processor by the position sensor. The second group of factors represents aims and conditions and AGV steering such as positioning accuracy, positioning time, allowed room for maneuver, the shape of the given trajectory, etc. The AGV steering rules contain sequences of primitive functions. These primitive functions are of such types as “turn left”, “straighten” (correct), “go straight on”, etc. Trajectory, as one of the basic factors, is defined at the level of controlling an elementary movement. The term “to control an elementary movement” means to select a transport road throughout the transport network and to code it using “elementary movement” such as “go straight” (relating to road section), “turn left” (relating to turning at a crossroad) etc.The results of the AGV steering simulation are presented in the third part of the paper. An exact kinematic AGV model used for stimulating control models is also presented.     

Approach to partially self-checking combinational circuits design

This paper presents a cost-effective, non-intrusive technique of partially self-checking combinational circuits design. The proposed technique is similar to duplication with comparison, wherein duplicated function module and comparator act as a function checker that detects any erroneous response of the original function module. However, instead of realizing checker with full error-detection capability, we select a subset of erroneous responses to implement partial, but simplified function checker. A heuristic procedure that tries to find the optimal sum-of-product expression for partial function checker that minimizes its area while providing specified error coverage is described here. Effectiveness of the technique is evaluated on a set of MCNC 91 benchmark combinational circuits.     

Reduction in intra-abdominal adipose tissue after strength training in older women

The purpose of this study was to examine the effects of a total body strength-training program on changes in total and regional body composition, in particular intra-abdominal adipose tissue (IAAT), in older women. Fourteen healthy older women (mean age 67 +/- 1 yr) exercised 3 times/wk for 16 wk. Strength was assessed by one-repetition maximum tests, with training intensity gradually increased to approximately 67% of one repetition maximum. Body composition was measured by hydrodensitometry and regional body composition was measured by computed tomography. Strength was significantly increased in the upper (51%) and lower body (65%). There was no significant change in body weight (64.4 +/- 2.7 vs. 64.2 +/- 2.7 kg), total body fat (38.7 +/- 1.4 vs. 38.0 +/- 1.6%) or fat-free mass (39.7 +/- 1.0 vs. 40.0 +/- 0.9 kg). However, after ST, there were significant reductions in IAAT (143.9 +/- 13.3 vs. 130.0 +/- 12.4 cm2), the IAAT-to-subcutaneous adipose tissue ratio (0.48 +/- 0.04 vs. 0.44 +/- 0.04), and midthigh subcutaneous adipose tissue (141.7 +/- 11.5 vs. 133.6 +/- 10.8 cm2) and an increase in midthigh muscle (52.9 +/- 2.6 vs. 58.0 +/- 2.0 cm2) (all P < 0.05). In conclusion, significant reductions in IAAT and an increase in strength and muscle area were observed after a strength-training program in healthy older women. These changes may be important in preventing the negative health outcomes associated with the age-related increase in intra-abdominal obesity.     

Void-free Au-Sn eutectic bonding of GaAs dice and its characterization using scanning acoustic microscopy

A new technique to produce perfect bonding between GaAs dice and alumina substrates is reported. Utilizing this technique, void-free bondings have been achieved consistently. The quality of the bonded devices is confirmed by a Scanning Acoustic Microscope (SAM) having a spatial resolution of 25 μm. Thermal cycling between -25° C and 125° C, and thermal shock between -196° C and 135° C, have been used to assess the reliability of the specimens. The SAM was used to study the variation of the bonds in the tests. After the tests, the bonds show no sign of degradation and the GaAs dice did not crack. Shear test has also been performed. All the well bonded specimens passed the shear test. The shear strength correlated very well with the SAM images of the specimens taken before the test.     

A principal component analysis of the Katz Adjustment Scale in a traumatic brain injury rehabilitation sample.

Relatives of 88 clients enrolled in a postacute rehabilitation program for the treatment of traumatic brain injury completed Section 1 of the Katz Adjustment Scale (KAS-R1). The items were subjected to a principal component analysis, which yielded 10 statistically significant component groups. Internal consistency as determined by Cronbach alpha ranged from 0.78 to 0.94. Moderate correlations were observed between several component groups, suggesting some overlap in components derived. Results suggest that the 127 items of the KAS-R1 form component groups that may represent categorically differentiated behavioral symptoms. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Serum leptin and energy expenditure in children

Leptin has been hypothesized to play an important role in energy balance by affecting both energy intake and energy expenditure. The purpose of our study was to determine the relationship between fasting serum leptin concentrations and measures of energy expenditure in prepubertal children. We measured total energy expenditure (TEE; by the doubly labeled water technique), resting energy expenditure (REE; after an overnight fast), activity energy expenditure (AEE; TEE-REE), body composition (by dual energy x-ray absorptiometry), and fasting serum leptin concentration (by RIA) in 76 children. Simple correlations showed that all measures of energy expenditure (TEE, REE, and AEE) were positively related to the serum leptin concentration (r = 0.50, P < 0.001; r = 0.45, P < 0.001; and r = 0.30, P < 0.01, respectively). However, after adjusting for body composition (fat-free mass and fat mass), gender, and ethnicity, serum leptin concentrations were not related to any measure of energy expenditure (TEE, P = 0.61; REE, P = 0.97; AEE, P = 0.65). These latter findings were further confirmed using structural equation models with leptin and energy expenditure as dependent variables, and fat-free mass and fat mass as independent variables. Results from these models showed no direct effect of leptin and no indirect effect of fat mass (through leptin) on any measure of energy expenditure, when a path between fat mass and energy expenditure was present in the model. Thus, our data do not support the hypothesis that the serum leptin concentration (independent of fat mass) is related to measures of energy expenditure in children.     

Integrated process planning and scheduling in networked manufacturing systems for I4.0: a review and framework proposal

Wireless Networks - Integrated process planning and scheduling in networked manufacturing systems plays a crucial role nowadays and in the forthcoming context of Industry 4.0 to enable effective...     

A comparison of machine learning methods for cutting parameters prediction in high speed turning process

Support vector machines are arguably one of the most successful methods for data classification, but when using them in regression problems, literature suggests that their performance is no longer state-of-the-art. This paper compares performances of three machine learning methods for the prediction of independent output cutting parameters in a high speed turning process. Observed parameters were the surface roughness (Ra), cutting force \((F_{c})\), and tool lifetime (T). For the modelling, support vector regression (SVR), polynomial (quadratic) regression, and artificial neural network (ANN) were used. In this research, polynomial regression has outperformed SVR and ANN in the case of \(F_{c}\) and Ra prediction, while ANN had the best performance in the case of T, but also the worst performance in the case of \(F_{c}\) and Ra. The study has also shown that in SVR, the polynomial kernel has outperformed linear kernel and RBF kernel. In addition, there was no significant difference in performance between SVR and polynomial regression for prediction of all three output machining parameters.