Trajectory design for autonomous underwater vehicles based on ocean model predictions for feature tracking

Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.

Design and implementation of sensor networks for the observation and research of harmful algal blooms in southern California coastal waters

Harmful Algal Blooms (HABs) have become an important environmental concern along the western coast of the United States. Toxic and noxious blooms adversely impact the economies of coastal communities in the region, pose risks to human health, and cause mortality events that have resulted in the deaths of thousands of fish, marine mammals and seabirds. One goal of field-based research efforts on this topic is the development of predictive models of HABs that would enable rapid response, mitigation and ultimately prevention of these events. In turn, these objectives are predicated on understanding the environmental conditions that stimulate these transient phenomena. An embedded sensor network (Fig. 1), under development in the San Pedro Shelf region off the Southern California coast, is providing tools for acquiring chemical, physical and biological data at high temporal and spatial resolution to help document the emergence and persistence of HAB events, supporting the design and testing of predictive models, and providing contextual information for experimental studies designed to reveal the environmental conditions promoting HABs. The sensor platforms contained within this network include pier-based sensor arrays, ocean moorings, HF radar stations, along with mobile sensor nodes in the form of surface and subsurface autonomous vehicles. FreewaveTM radio modems facilitate network communication and form a minimally-intrusive, wireless communication infrastructure throughout the Southern California coastal region, allowing rapid and cost-effective data transfer. An emerging focus of this project is the incorporation of a predictive ocean model that assimilates near-real time, in situ data from deployed Autonomous Underwater Vehicles (AUVs). The model then assimilates the data to increase the skill of both nowcasts and forecasts, thus providing insight into bloom initiation as well as the movement of blooms or other oceanic features of interest (e.g., thermoclines, fronts, river discharge, etc.). From these predictions, deployed mobile sensors can be tasked to track a designated feature. This focus has led to the creation of a technology chain in which algorithms are being implemented for the innovative trajectory design for AUVs. Such intelligent mission planning is required to maneuver a vehicle to precise depths and locations that are the sites of active blooms, or physical/chemical features that might be sources of bloom initiation or persistence. The embedded network yields high-resolution, temporal and spatial measurements of pertinent environmental parameters and resulting biology (see Fig. 1). Supplementing this with ocean current information and remotely sensed imagery and meteorological data, we obtain a comprehensive foundation for developing a fundamental understanding of HAB events. This then directs labor- intensive and costly sampling efforts and analyses. Additionally, we provide coastal municipalities, managers and state agencies with detailed information to aid their efforts in providing responsible environmental stewardship of their coastal waters.

Trajectory design and implementation for multiple autonomous underwater vehicles based on ocean model predictions

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Facile synthesis of Lithium Niobate squares by a combustion route

A combustion synthesis of lithium niobate (LN) squares from activated niobium oxide (Nb2 O5.nH2O) and Li2CO3 was studied to understand all the chemical reactions involved, and the nucleation and square-growth mechanisms. It was found that first the lithium ions react with the fuel (urea), then niobium ions of Nb2 O5.nH2O begin a continuous reaction with the fuel to form metal-organic complexes. LN nuclei are formed by the solid-state reaction of Li- and Nb-organic complexes at 430 degrees celcius. Lithium niobate squares are obtained in the crystallization stasge at 700 degrees celcius, which go on the grow into larger squares at 850 degrees celcius because of the agglomeration effect.

Transmission system expansion planning considering combined operation of wind farms and energy storage systems

An energy storage system (ESS) can provide ancillary services such as frequency regulation and reserves, as well as smooth the fluctuations of wind power outputs, and hence improve the security and economics of the power system concerned. The combined operation of a wind farm and an ESS has become a widely accepted operating mode. Hence, it appears necessary to consider this operating mode in transmission system expansion planning, and this is an issue to be systematically addressed in this work. Firstly, the relationship between the cost of the NaS based ESS and its discharging cycle life is analyzed. A strategy for the combined operation of a wind farm and an ESS is next presented, so as to have a good compromise between the operating cost of the ESS and the smoothing effect of the fluctuation of wind power outputs. Then, a transmission system expansion planning model is developed with the sum of the transmission investment costs, the investment and operating costs of ESSs and the punishment cost of lost wind energy as the objective function to be minimized. An improved particle swarm optimization algorithm is employed to solve the developed planning model. Finally, the essential features of the developed model and adopted algorithm are demonstrated by 18-bus and 46-bus test systems.

Indoor aerosols : from personal exposure to risk assessment

Motivated by growing considerations of the scale, severity and risks associated with human exposure to indoor particulate matter, this work reviewed existing literature to: (i) identify state-of-the-art experimental techniques used for personal exposure assessment; (ii) compare exposure levels reported for domestic/school settings in different countries (excluding exposure to environmental tobacco smoke and particulate matter from biomass cooking in developing countries); (iii) assess the contribution of outdoor background vs indoor sources to personal exposure; and (iv) examine scientific understanding of the risks posed by personal exposure to indoor aerosols. Limited studies assessing integrated daily residential exposure to just one particle size fraction, ultrafine particles, show that the contribution of indoor sources ranged from 19-76%. This indicates a strong dependence on resident activities, source events and site specificity, and highlights the importance of indoor sources for total personal exposure. Further, it was assessed that 10-30% of the total burden-of-disease from particulate matter exposure was due to indoor generated particles, signifying that indoor environments are likely to be a dominant environmental factor affecting human health. However, due to challenges associated with conducting epidemiological assessments, the role of indoor generated particles has not been fully acknowledged, and improved exposure/risk assessment methods are still needed, together with a serious focus on exposure control.

Effect of Reynolds numbers on flow past four square cylinders in an in-line square configuration for different gap spacings

In this paper two-dimensional (2-D) numerical investigation of flow past four square cylinders in an in-line square configuration are performed using the lattice Boltzmann method. The gap spacing g=s/d is set at 1, 3 and 6 and Reynolds number ranging from Re=60 to 175. We observed four distinct wake patterns: (i) a steady wake pattern (Re=60 and g=1) (ii) a stable shielding wake pattern (80≤Re≤175 and g=1) (iii) a wiggling shielding wake pattern (60≤Re≤175 and g=3) (iv) a vortex shedding wake pattern (60≤Re≤175 and g=6) At g=1, the Reynolds number is observed to have a strong effect on the wake patterns. It is also found that at g=1, the secondary cylinder interaction frequency significantly contributes for drag and lift coefficients signal. It is found that the primary vortex shedding frequency dominates the flow and the role of secondary cylinder interaction frequency almost vanish at g=6. It is observed that the jet between the gaps strongly influenced the wake interaction for different gap spacing and Reynolds number combination. To fully understand the wake transformations the details vorticity contour visualization, power spectra of lift coefficient signal and time signal analysis of drag and lift coefficients also presented in this paper.

The importance of individual difference : examining anthropomorphic tendency and responses to spokes-characters

Anthropomorphism is a cognitive bias, which occurs when individuals see human characteristics in a non-human agent, object or animal. Anthropomorphism is especially interesting to marketers, because once anthropomorphic bias has been triggered, it can lead to a greater feeling of connectedness to a non-human agent (Tam, Lee and Chao, 2013), the emulation of behaviours (Aggarwal and McGill, 2012) or greater attribution of brand personality and brand liking (Delbaere, McQuarrie and Phillips, 2011). Importantly, research now shows that levels of this tendency vary between individuals (Waytz, Cacioppo and Epley, 2010), but research to date has failed to focus on how anthropomorphic tendency influences individual responses to marketing communications messages. Spokes-characters present an ideal context through which to examine this gap, given that they function as personified brands, designed to trigger consumer anthropomorphic tendency. Further, little is understood about how spokes-characters operate and which consumers will prefer them to their human counterparts. Like anthropomorphic research, much empirical work to date has focused on design and outcomes, examining the sender’s encoding process and the feedback generated, but ignoring the individual decoding process that is so important to understanding individual differences and message effectiveness. The current research employs three experiments using an online survey with stimulus exposure to show that anthropomorphic tendency, personality similarity and spokes-character type all have relevance to the understanding of this complex relationship. Study one and two indicate that while a human spokesperson is still preferred by many, higher levels of anthropomorphic tendency increase likeability of cartoon spokes characters. Study three highlights the importance of personality similarity, which further increases likability. Additional analyses provide key findings concerning the nature of anthropomorphic tendency as an individual difference and trait. This research contributes to a greater understanding of anthropomorphism theory and fills existing gaps in the consumer psychology and marketing communications literature.

Visible light photocatalysts for synthesis of fine organic chemicals on supported nanostructures

This thesis is focus on developing new photocatalysts for synthesis of fine organic chemicals on supported nanostructures. These photocatalysts can facilitate reactions by using visible light, moderate temperature and atmospheric pressure which is suitable for a sustainable, green and eco-friendly modern chemical industry. Both Semiconductor Photocatalyst and Noble Metal Photocatalysts are designed to facilitate the homocouplings reaction of imine generation by amines.

Rough set based approach to text classification

Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.

Microstructure and electromagnetic characteristics of Ni nanoparticle film coated carbon microcoils

Carbon microcoils (CMCs) have been coated with a Ni nanoparticle film using an electroless plating process. The morphology, the elemental composition and the phases in the coating layer, complex permittivity and permeability of the CMCs and Ni-coated CMCs were, respectively, investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and microwave vector network analysis at room temperature. A homogeneous dispersion of Ni nanoparticles on the outer surface of the CMCs was obtained, with a mean particle size of ∼34.4 nm and the phosphorus content of about 8.5 wt%. When comparing the coated and uncoated CMC samples, the real (ε′) and imaginary (ε″) part of the complex permittivity as well as dielectric dissipation factor (tgδε = ε″/ε′) of the Ni-coated CMCs were much smaller, while the real (μ′) and imaginary (μ″) part of the complex permeability and the magnetic dissipation factor (t g σμ = μ″ / μ′) were larger. The enhanced microwave absorption of Ni-coated CMCs resulted from stronger dielectric and magnetic losses. In contrast, the microwave absorption of uncoated CMCs was mainly attributed to the dielectric rather than magnetic losses.

Unconventional Ni–P alloy-catalyzed CVD of carbon coil-like micro- and nano-structures

Conventional catalyzed thermal CVD of carbon microcoils commonly suffers from poor control of the coil shape and morphology and rarely reaches the nanoscale size range. This article reports on an unconventional Ni-P alloy-catalyzed, high-throughput, highly reproducible CVD of ultra-long carbon coil-like micro- and nano-structures using acetylene precursor at relatively low process temperatures. Helical carbon microcoils with consistently uniform, circular cross-sections and a high degree of crystallinity have been synthesized at 750 °C. A further reduction of the temperature to 650 °C led to the growth of ultra-long (up to several mm) wave-like carbon nanofibers made of two nanowires with the diameters in the 100-200 nm range. The results of the XRD and Raman analysis reveal that the nanofibers feature only a slightly more disordered structure compared to the microcoils. Our results suggest that morphology and structure of the carbon coil-like micro- and nano-structures can be tailored by the appropriate alloying of the catalyst and the choice of the CVD process parameters.