A case for adaptive sub-carrier level power allocation in OFDMA networks

In today's OFDMA networks, the transmission power is typically fixed and the same for all the sub-carriers that compose a channel. The sub-carriers though, experience different degrees of fading and thus, the received power is different for different sub-carriers; while some frequencies experience deep fades, others are relatively unaffected. In this paper, we make a case of redistributing the power across the sub-carriers (subject to a fixed power budget constraint) to better cope with this frequency selectivity. Specifically, we design a joint power and rate adaptation scheme (called JPRA for short) wherein power redistribution is combined with sub-carrier level rate adaptation to yield significant throughput benefits. We further consider two variants of JPRA: (a) JPRA-CR where, the power is redistributed across sub-carriers so as to support a maximum common rate (CR) across sub-carriers and (b) JPRA-MT where, the goal is to redistribute power such that the transmission time of a packet is minimized. While the first variant decreases transceiver complexity and is simpler, the second is geared towards achieving the maximum throughput possible. We implement both variants of JPRA on our WARP radio testbed. Our extensive experiments demonstrate that our scheme provides a 35% improvement in total network throughput in testbed experiments compared to FARA, a scheme where only sub-carrier level rate adaptation is used. We also perform simulations to demonstrate the efficacy of JPRA in larger scale networks. © 2012 ACM

Mechanical performance of composite bonded joints in the presence of localised process-induced zero-thickness defects

Processing parameters and environmental conditions can introduce variation into the performance of adhesively bonded joints. The effect of such variation on the mechanical performance of the joints is not well understood. Moreover, there is no validated nondestructive inspection (NDI) available to ensure bond integrity post-process and in-service so as to guarantee initial and continued airworthiness in aerospace sector. This research studies polymer bond defects produced in the laboratory scale single-lap composite-to-composite joints that may represent the process-induced defects occurring in actual processing scenarios such as composite joining and repair in composite aircrafts. The effect of such defects on the degradation of a joint's mechanical performance is then investigated via quasi-static testing in conjunction with NDI ultrasonic C-scanning and pulsed thermography. This research is divided into three main sections: 1- manufacturing carbon fibre-reinforced composite joints containing representative nearly zero-thickness bond defects, 2- mechanical testing of the composite joints, and 3- assessment of the NDI capability for detection of the bond defects in such joints

Socio-economic and demographic factors that contribute to the growth of the civil aviation industry

The civil aviation industry has captured the world's share both in terms of operations and markets. The International Civil Aviation Organisation (ICAO) reported an increase of 6.3 percent in passenger traffic to 3.7billion in 2016 based on recorded departures globally. This paper is an effort to understand the driving force for the civil aviation sector based on demand. As per published reports, the trends show the continued growth in the sector even with the inclusion of production challenges in order to meet global market demand. Though the sector is heavily reliant on a variety of challenges and factors, the industry has established itself as the most advanced and lucrative industry that continues to 'PULL' the associated industries. This paper identifies and establishes the 'push' and 'pull' factors under social, demographic and economic factors and how they exercise significant control making the ever-growing industry RESILIENT to changing geo-economic and political landscapes

'In-situ' inspection technologies: Trends in degradation assessment and associated technologies

The advent of advanced, innovative and complex engineered systems has established new technologies that are far more superior and perform well even in harsh environments. It is well established that such next generation systems need to be maintained regularly to prevent any catastrophic failure as a result of regular wear and tear. Non-destructive and structural monitoring technologies have been supporting maintenance activities for over a century and industries still continue to rely on such technologies for effective degradation assessment. Maintenance ‘in-situ’ has been adopted for decades where the health of system or component needs to be inspected in its natural environment, especially those safety critical systems that need in-field inspection to determine its health. This paper presents selective case studies adopted in the area of damage assessment that qualify for both field and ‘in-situ’ inspection. The future directions in the applicability of traditional and advanced inspection techniques to inspect multiple materials and in the area of inaccessible area degradation assessment have also been presented as part of this study

A coefficient clustering analysis for damage assessment of composites based on pulsed thermographic inspection

This paper introduces a coefficient clustering analysis method to detect and quantitatively measure damage occurring in composite materials using pulsed thermographic inspection. This method is based on fitting a low order polynomial model for temperature decay curves, which (a) provides an enhanced visual confirmation and size measurement of the damage, (b) provides the reference point for sound material for further damage depth measurement, (c) and reduces the burden in computational time. The performance of the proposed method is evaluated through a practical case study with carbon fibre reinforced polymer (CFRP) laminates which were subjected to a drop impact test with varying energy levels. A novel method for reducing an entire thermogram sequence into a single image is introduced, which provides an enhanced visualisation of the damage area

MOCF: A Multi-Objective Clustering Framework using an Improved Particle Swarm Optimization Algorithm

Traditional clustering algorithms, such as K-Means, perform clustering with a single goal in mind. However, in many real-world applications, multiple objective functions must be considered at the same time. Furthermore, traditional clustering algorithms have drawbacks such as centroid selection, local optimal, and convergence. Particle Swarm Optimization (PSO)-based clustering approaches were developed to address these shortcomings. Animals and their social Behaviour, particularly bird flocking and fish schooling, inspire PSO. This paper proposes the Multi-Objective Clustering Framework (MOCF), an improved PSO-based framework. As an algorithm, a Particle Swarm Optimization (PSO) based Multi-Objective Clustering (PSO-MOC) is proposed. It significantly improves clustering efficiency. The proposed framework's performance is evaluated using a variety of real-world datasets. To test the performance of the proposed algorithm, a prototype application was built using the Python data science platform. The empirical results showed that multi-objective clustering outperformed its single-objective counterparts

Stimulation of shrimp (Penaeus monodon) hemocytes by lipopolysaccharide-like molecules derived from Novacq™

Immune stimulation through feed additives is a promising strategy that can help to combat disease in shrimp farming and reduce the use of antibiotics and other chemotherapeutics. The present study investigated the in vitro immunostimulatory effects of lipopolysaccharide (LPS)-like molecules isolated from the microbial based feed additive Novacq™ (N-LPS). The presence of LPS-like molecules was confirmed and quantified Novacq™ using a HEK-TLR4 reporter cell line. Primary hemocytes isolated from adult Penaeus monodon were used to measure the immunostimulatory of N-LPS compared with the control group that were treated with E. coli derived LPS (E-LPS). The N-LPS stimulated a rapid and significant induction of the phenoloxidase (PO) response in the hemocytes. The PO response increased with exposure time and LPS concentration and was significantly higher compared with an E. coli LPS (E-LPS) control. In addition, using gene expression data, we quantified the transcriptome response of the hemocytes at 15, 30 and 60 mins post stimulation. Compared with the controls, the N-LPS treated hemocytes had a significant up-regulation of genes involved in the immune system modulation and control at all time-points. Most noteworthy was the significant induction of transcripts that function as serine protease inhibitors (namely SERPINs), that regulate the overexpression of the PO system. Transcription factors from the Notch family which directly regulate the expression of many immune genes were also induced within the hemocytes. Additionally, we also saw a strong up-regulation of crustacean hyperglycemic hormone (CHH) transcripts, an important neuropeptide involved in immune function. Overall, the transcriptome profile of the hemocytes suggests that the LPS component of Novacq™ is highly immunostimulatory and generates a strong PO response in vitro. The subsequent transcriptional response appears to be directed towards preventing further activation of the PO system most likely in an attempt to limit cytoxicity to the host. Our study highlights the immunostimulatory ability of Novacq™ and provides further evidence of the positive health benefits this microbial based feed additive can have in shrimp.</p

Quantifying uncertainty in pulsed thermographic inspection by analysing the thermal diffusivity measurements of metals and composites

Pulsed thermography has been used significantly over the years to detect near and subsurface damage in both metals and composites. Where most of the research has been in either improving the detectability and/or its applicability to specific parts and scenarios, efforts to analyse and establish the level of uncertainty in the measurements have been very limited. This paper presents the analysis of multiple uncertainties associated with thermographic measurements under multiple scenarios such as the choice of post-processing algorithms; multiple flash power settings; and repeat tests on four materials, i.e., aluminium, steel, carbon-fibre reinforced plastics (CFRP) and glass-fibre reinforced plastics (GFRP). Thermal diffusivity measurement has been used as the parameter to determine the uncertainty associated with all the above categories. The results have been computed and represented in the form of a relative standard deviation (RSD) ratio in all cases, where the RSD is the ratio of standard deviation to the mean. The results clearly indicate that the thermal diffusivity measurements show a large RSD due to the post-processing algorithms in the case of steel and a large variability when it comes to assessing the GFRP laminates

Detecting failure of a material handling system through a cognitive twin

This paper describes a methodology for developing a digital twin (DT) based on a rich semantic model and principles of system engineering. The aim is to provide a general model of digital twins (DT) that can improve decision making based on semantic reasoning on real-time system monitoring. The methodology has been tested on a laboratory pilot plant that acts as a material handling system. The key contribution of this research is to propose a generic information model for DT using foundational ontology and principles of systems engineering. The efficacy of the proposed methodology is demonstrated by the automatic detection of a component level failure using semantic reasoning