Parts internal structure definition using non-uniform patterned lattice optimization for mass reduction in additive manufacturing

Engineering with Computers - Today, being able to generate and produce shapes that fit mechanical and functional requirements and having as low as possible mass is crucial for aerospace and...     

Transient performance analysis of adaptive multitask network based on correntropy criterion

In this paper, we investigate the transient performance of the proposed distributed multitask learning algorithm that is developed based on maximum correntropy criterion. In the first stage, we derive the proposed multitask learning algorithm in which the correntropy‐based combination matrix determines which sensors should collaborate together and which sensors should stop the collaboration. In the second stage, according to the variance relation of the error vector, we derive a closed‐form relation that shows the transition of mean‐square‐deviation learning performance. We also find the lower and upper bounds of the step size that ensure the stability of the multitask learning algorithm. The theoretical finding of the transient performance is shown to fit a well match with simulation results.     

An achievable rate region and a capacity outer bound for 3‐user Gaussian multiple access channel with feedback

Extension of the Ozarow capacity theorem for 2‐transmitter Gaussian multiple access channel (MAC) with feedback to the channels with more than 2 transmitters is a widely studied and long standing problem (for example, see the Kramer sum‐capacity region). In this paper, we investigate and analyze this possible extension. Specifically, exploiting a class of Schalkwijk‐Kailath linear feedback codes, we obtain an achievable rate region for 3‐user Gaussian MAC with full feedback and also a capacity outer bound. Then the results are extended for a case where there is no feedback link for one user, and the corresponding achievable rate region and capacity outer bound are computed. Furthermore, the gap between the derived rates and the sum capacity of 3‐user Gaussian MAC with full and partial feedback is computed under special assumptions.     

Optimization of Bio-Implantable Power Transmission Efficiency Based on Input Impedance

Recently, the inductive coupling link is the most robust method for powering implanted biomedical devices, such as micro-system stimulators, cochlear implants, and retinal implants. This research provides a novel theoretical and mathematical analysis to optimize the inductive coupling link efficiency driven by efficient proposed class-E power amplifiers using high and optimum input impedance. The design of the coupling link is based on two pairs of aligned, single-layer, planar spiral circular coils with a proposed geometric dimension, operating at a resonant frequency of 13.56 MHz. Both transmitter and receiver coils are small in size. Implanted device resistance varies from 200 Ω to 500 Ω with 50 Ω of stepes. When the conventional load resistance of power amplifiers is 50 Ω, the efficiency is 45%; when the optimum resonant load is 41.89 Ω with a coupling coefficient of 0.087, the efficiency increases to 49%. The efficiency optimization is reached by calculating the matching network for the external LC tank of the transmitter coil. The proposed design may be suitable for active implantable devices.     

Efficient failure prediction in autonomic networks based on trend and frequency analysis of anomalous patterns

We describe an efficient failure prediction system based on new algorithms that model and detect anomalous behaviors using multi‐scale trend analysis of multiple network parameters. Our approach enjoys many advantages over prior approaches. By operating at multiple timescales simultaneously, the new system achieves robustness against unreliable, redundant, incomplete and contradictory information. The algorithms employed operate with low time complexity, making the system scalable and feasible in real‐time environments. Anomalous behaviors identified by the system can be stored efficiently with low space complexity, making it possible to operate with minimal resource requirements even when processing high‐rate streams of network parameter values. The developed algorithms generate accurate failure predictions quickly, and the system can be deployed in sa distributed setting. Prediction quality can be improved by considering larger sets of network parameters, allowing the approach to scale as network complexity increases. The system is validated by experiments that demonstrate its ability to produce accurate failure predictions in an efficient and scalable manner. Copyright © 2013 John Wiley & Sons, Ltd.     

Dairy biofilm: an investigation of the impact on the surface chemistry of two materials: silicone and stainless steel

Biofilms are the most common mode of bacterial growth in nature and the formation will occur on organic or inorganic solid surfaces in contact with a liquid. The aims of this study were, by combining numeration and sessile drop technique, (i) to characterize the structural dynamics of dairy biofilm growth and the physico chemical properties on silicone and stainless steel and (ii) to evaluate the impact of bio-adhesion on chemistry of surfaces at different times of contact (2, 7, 9 and 24?h). Significantly, greater biofilm volumes were observed after 48?h on two materials. Gram-positive bacteria and fungal population exhibited a significantly higher biofilm organization than gram-negative (43–64%). Elsewhere, after 48?h, results showed a slight difference on gram-negative adhered cells on stainless steel than silicone (2.6?×?10⁷?cfu/cm² and 4.7?×?10⁵?cfu/cm², respectively). Moreover, the physico chemical properties of the surfaces showed that the silicone and stainless steel have a hydrophobic character (Giwi?=??68.28?mJ/m² and ?57.6?mJ/m², respectively). Also, both the surfaces present a weak electron donor character (γ ^??=?2.2?mJ/m² and 4.1?mJ/m², respectively). The real-time investigation of the impact of dairy biofilm on the physico chemical properties of the materials has shown a decrease of hydrophobicity degree of the silicone surface that becomes hydrophilic (ΔGiwi?=?11.47?mJ/m²) after 7?h and the increase of electron donor character (γ ^??=?75.8?mJ/m²). Elsewhere, bio-adhesion on stainless steel was accompanied with a decrease of hydrophobicity degree of the surface, which becomes hydrophilic after 7?h of contact (ΔGiwi?=?6.62?mJ/m²) and the increase of the electron donor character (γ ^??=?44.8?mJ/m²). While, after 24?h of contact, results showed a decrease of the hydrophilicity degree and surface energy components of silicone and stainless steel that become hydrophobic (ΔGiwi?=??21.2?mJ/m² and ΔGiwi?=??56.51?mJ/m², respectively) and weak electron donor (γ ^??=?14.0 and 2.3?mJ/m², respectively).     

Natural phospholipids: Occurrence,biosynthesis, separation,identification, and beneficial health aspects

During the last years, phospholipids (PLs) have attracted great attention because of their crucial roles in providing nutritional values, technological and medical applications. There are considerable proofs that PLs have unique nutritional benefits on human health, such as reducing cholesterol absorption, improving liver functions, and decreasing the risk of cardiovascular diseases. PLs are the main structural lipid components of cell and organelle membranes in all living organisms, and therefore, they occur in all organisms and the derived food products. PLs are distinguished by the presence of a hydrophilic head and a hydrophobic tail, consequently they possess amphiphilic features. Due to their unique characteristics, the extraction, separation, and identification of PLs are critical issues to be concerned. This review is focused on the content of PLs classes in several sources (including milk, vegetable oils, egg yolk, and mitochondria). As well, it highlights PLs biosynthesis, and the methodologies applied for PLs extraction and separation, such as solvent extraction and solid-phase extraction. In addition, the determination and quantification of PLs classes by using thin layer chromatography, high-performance liquid chromatography coupled with different detectors, and nuclear magnetic resonance spectroscopy techniques.     

Remediation of hexavalent chromium by consortia of indigenous bacteria from tannery waste-contaminated biotopes in Fez,Morocco

Bioremediation is a promising, safe and economical technology widely used to clean up both soils and wastewaters containing Cr(VI). Most work uses pure microbial cultures. Little research has been done with mixed microbial cultures. In this study, consortia of indigenous bacteria isolated from a polluted site have been used to study the effect of different conditions such as Cr(VI) concentration, metal ions, electron donors and pH on Cr(VI) reduction by the consortia. We also evaluate the microbial ability to detoxify repeatedly and continuously in a non-modified medium. Results show that consortia of indigenous bacteria are resistant to greater than 200 mg/L Cr(VI). However, mixed cultures exhibited decreasing diversity with increasing levels of chromate. The consortia show high Cr(VI) removal capacity under various conditions and exhibit an ability for continuous reduction of Cr(VI) up to three consecutive inputs. The consortia may be appropriate for environmental applications for Cr(VI) remediation.     

Design and Implementation of a Scalable RFID-Based Attendance System with an Intelligent Scheduling Technique

Radio Frequency Identification (RFID) technology; a convenient and flexible technology which is well suited for fully automated systems, is directing human lifestyle towards automation and reality. Integrating RFID into attendance management systems makes the tasks of both users and administrators easy, smart, convenient, and practical. Earlier implementations of RFID-based attendance systems involve different approaches and facilities. Different intertwined characteristics (i.e., scalability, and automation) are suggested in evaluating the performance of these systems. The coverage of these characteristics appears to be adequate in achieving a good systems implementation. Some of the existing systems present high performance; however, these systems still have gaps in some of the suggested characteristics. In order to mind these gaps, a scalable RFID-based attendance system with an intelligent scheduling technique; called Intelligent and fully Automated Attendance System (IAAS), has been designed and implemented. Finally, the performance of IAAS has been evaluated through a comparison with existing attendance systems.