A practical framework for data collection in wireless sensor networks

Optimizing energy consumption for extending the lifetime in wireless sensor networks is of dominant importance. Groups of autonomous robots and unmanned aerial vehicles (UAVs) acting as mobile data collectors are utilized to minimize the energy expenditure of the sensor nodes by approaching the sensors and collecting their buffers via single hop communication, rather than using multihop routing to forward the buffers to the base station. This paper models the sensor network and the mobile collectors as a system-of-systems, and defines all levels and types of interactions. A practical framework that facilitates deploying heterogeneous mobiles without prior knowledge about the sensor network is presented. Realizing the framework is done through simulation experiments and tested against several performance metrics.<br /

Optimal multisensor data fusion for linear systems with missing measurements

Multisensor data fusion has attracted a lot of research in recent years. It has been widely used in many applications especially military applications for target tracking and identification. In this paper, we will handle the multisensor data fusion problem for systems suffering from the possibility of missing measurements. We present the optimal recursive fusion filter for measurements obtained from two sensors subject to random intermittent measurements. The noise covariance in the observation process is allowed to be singular which requires the use of generalized inverse. Illustration example shows the effectiveness of the proposed filter in the measurements loss case compared to the available optimal linear fusion methods.<br /

Decentralized mobility models for data collection in wireless sensor networks

Controlled mobility in wireless sensor networks provides many benefits towards enhancing the network performance and prolonging its lifetime. Mobile elements, acting as mechanical data carriers, traverse the network collecting data using single-hop communication, instead of the more energy demanding multi-hop routing to the sink. Scaling up from single to multiple mobiles is based more on the mobility models and the coordination methodology rather than increasing the number of mobile elements in the network. This work addresses the problem of designing and coordinating decentralized mobile elements for scheduling data collection in wireless sensor networks, while preserving some performance measures, such as latency and amount of data collected. We propose two mobility models governing the behaviour of the mobile element, where the incoming data collection requests are scheduled to service according to bidding strategies to determine the winner element. Simulations are run to measure the performance of the proposed mobility models subject to the network size and the number of mobile elements.<br /

A life cycle inventory of aluminium die casting

As part of an ongoing project, a life cycle inventory (LCI) of aluminium high pressure die casting (HPDC) has been collected. This has been conducted from the view of an individual product and also the entire process. The objective of the study was to analyse the process and suggest changes to reduce environmental impacts. One modem aluminium high pressure die casting plant located in Victoria, Australia was evaluated and modelled. Site specific data on energy and materials was gathered and the process was modelled using a typical automotive component. The paper also presents our experience and methodology used in this inventory data collection process from the real industry for LCA purposes. The inventory data collected itself reveals that the HPDC process is energy intensive and as such the major emissions were from the use of natural gas fired furnaces and from the brown coal derived electricity. It is also found the large environmental benefits of using secondary aluminium over primary aluminium in the HPDC process. A detailed LCA is being cal1ied out based on the inventory obtained.</div

Multi-Agent Deep Reinforcement Learning with Human Strategies

Deep learning has enabled traditional reinforcement learning methods to deal with high-dimensional problems. However, one of the disadvantages of deep reinforcement learning methods is the limited exploration capacity of learning agents. In this paper, we introduce an approach that integrates human strategies to increase the exploration capacity of multiple deep reinforcement learning agents. We also report the development of our own multi-agent environment called Multiple Tank Defence to simulate the proposed approach. The results show the significant performance improvement of multiple agents that have learned cooperatively with human strategies. This implies that there is a critical need for human intellect teamed with machines to solve complex problems. In addition, the success of this simulation indicates that our multi-agent environment can be used as a testbed platform to develop and validate other multi-agent control algorithms.Comment: 2019 IEEE International Conference on Industrial Technology (ICIT), Melbourne, Australi

Electromagnetic interference shielding and radiation absorption in thin polypyrrole films

Results of permittivity measurements, electromagnetic interference shielding effectiveness, and heat generation due to microwave absorption in conducting polymer coated textiles are reported and discussed. The intrinsically conducting polymer, polypyrrole, doped with anthraquinone-2-sulfonic acid (AQSA) or para-toluene-2-sulfonic acid (pTSA) was applied on textile substrates and the resulting materials were investigated in the frequency range 1&ndash;18 GHz. The 0.54 mm thick conducting textile/polypyrrole composites absorbed up to 49.5% of the incident 30&ndash;35 W microwave radiation. A thermography station was used to monitor the temperature of these composites during the irradiation process, where absorption was confirmed via visible heat losses. Samples with lower conductivity showed larger temperature increases caused by microwave absorption compared to samples with higher conductivity. A sample with an average sheet resistivity of 150 &Omega;/sq. showed a maximum temperature increase of 5.27 &deg;C, whilst a sample with a lower resistivity (105 &Omega;/sq.) rose by 3.85 &deg;C.<br /

Efficacy of ω-3 supplementation in patients with psoriasis:a meta-analysis of randomized controlled trials

Several studies have been conducted with the aim of investigating the effect of Omega(�)-3 on different psoriasis indices including Psoriasis Area and Severity Index (PASI) score, erythema, scaling, itching, area involved, and infiltration. Nevertheless, a pooled analysis of trials that evaluated these variables has not been conducted. Therefore, the aim of this meta-analysis was to assess the efficacy of �-3 fatty acids in treating patients with psoriasis. We searched through different electronic, references of retrieved articles, and previous related reviews databases up to November 2018. Both combined and stratified analyzes were conducted. A fixed-effects or random effects model was used to assess the mean effect sizes. An eventual 10 studies involving 560 participants were considered as eligible for inclusion in the present meta-analysis. The meta-analysis indicated a significant reduction in PASI score by � 1.58 (95 confidence interval (CI), � 2.24, � 0.92; P < 0.001) in favor of �-3 polyunsaturated fatty acid (PUFA) group. The random effects model showed a statistically significant beneficial effect of �-3 PUFA supplementation on reducing erythema by � 1.66 unit and reducing scaling (weighted mean difference (WMD), � 0.69; 95 CI, � 1.26, � 0.13; P = 0.02). Significant improvements in erythema, itching, and scale were observed in the trials which used the higher dosage of �-3 supplementation. The results of current meta-analysis study support the use of �-3 PUFA supplementation for the improvement of the evaluated parameters in psoriatic patients. However, well-controlled and randomized studies are needed to confirm the veracity of non-significant and/or equivocal findings. © 2019, International League of Associations for Rheumatology (ILAR)

Airport and air cargo operation systems

Analysis of airport and air cargo operations is commonly performed in isolation, sharing only simple information such as flight schedules. Systems theory and Systems methodology can enhance such analysis by considering all aspects of air operations. It provides the decision-maker with an improved understanding of the implication of policy decisions, resource allocations and infrastructure investment strategies, through the capture of emergent behaviours and interdependencies. For example, the term airport operations, initially reminds us of the thought of passengers being transported by aircraft. Deeper thinking would identify activities that affect passenger operations, such as baggage handling systems, aircraft maintenance, and passenger security. In reality, airport operations consist of numerous aspects, including; concourses, runways, airlines, fuel depots, cargo terminal operators, retail, parking, cleaning, catering and many interacting people including travellers, service providers and visitors. For the airport to function effectively, these numerous systems must work together. This talk will focus on new tools and methodologies that are required for model development and analysis. It will then focus on modelling, simulation and analysis of the airport operations, providing greater understanding of airport operation with an emphasis towards security