Search results for: distributed acoustic sensing

Authors: Haitham A. Hussein, Rozi Abdullah, Issa Saket, Md. Azlin

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The gravitational effect has been extensively applied to separate oil from water in water and wastewater treatment systems. The maximum oil globules removal efficiency is improved by obtaining the best flow uniformity in separator tanks. This study used 2D computational fluid dynamics (CFD) to investigate the effect of different inlet baffle positions inside the separator tank. Laboratory experiment has been conducted, and the measured velocity fields which were by Nortek Acoustic Doppler Velocimeter (ADV) are used to verify the CFD model. Computational investigation results indicated that the construction of an inlet baffle in a suitable location provides the minimum recirculation zone volume, creates the best flow uniformity, and dissipates kinetic energy in the oil and water separator tank. Useful formulas were predicted to design the oil and water separator tanks geometry based on an experimental model.

Keywords: oil/water separator tanks, inlet baffles, CFD, VOF

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Authors: Baptiste Bouvier

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While we are constantly flooded with stimuli in daily life, attention allows us to select the ones we specifically process and ignore the others. Some salient stimuli may sometimes pass this filter independently of our will, in a "bottom-up" way. The role of the acoustic properties of the timbre of a sound on its salience, i.e., its ability to capture the attention of a listener, is still not well understood. We implemented a paradigm called the "additional singleton paradigm", in which participants have to discriminate targets according to their duration. This task is perturbed (higher error rates and longer response times) by the presence of an irrelevant additional sound, of which we can manipulate a feature of our choice at equal loudness. This allows us to highlight the influence of the timbre features of a sound stimulus on its salience at equal loudness. We have shown that a stimulus that is brighter than the others but not louder leads to an attentional capture phenomenon in this framework. This work opens the door to the study of the influence of any timbre feature on salience.

Keywords: attention, audition, bottom-up attention, psychoacoustics, salience, timbre

Procedia PDF Downloads 171

Authors: Israel Ropo Orimoloye, Johanes A. Belle, Olusola Adeyemi, Olusola O. Ololade

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With more than 100,000 orbits during the past 20 years, Terra has significantly improved our knowledge of the Earth's climate and its implications on societies and ecosystems of human activity and natural disasters, including drought events. With Terra instrument's performance and the free distribution of its products, this study utilised Terra MOD13Q1 satellite data to assess drought disaster events and its spatiotemporal patterns over the Free State Province of South Africa between 2001 and 2019 for summer, autumn, winter, and spring seasons. The study also used high-resolution downscaled climate change projections under three representative concentration pathways (RCP). Three future periods comprising the short (the 2030s), medium (2040s), and long term (2050s) compared to the current period are analysed to understand the potential magnitude of projected climate change-related drought. The study revealed that the year 2001 and 2016 witnessed extreme drought conditions where the drought index is between 0 and 20% across the entire province during summer, while the year 2003, 2004, 2007, and 2015 observed severe drought conditions across the region with variation from one part to the another. The result shows that from -24.5 to -25.5 latitude, the area witnessed a decrease in precipitation (80 to 120mm) across the time slice and an increase in the latitude -26° to -28° S for summer seasons, which is more prominent in the year 2041 to 2050. This study emphasizes the strong spatio-environmental impacts within the province and highlights the associated factors that characterise high drought stress risk, especially on the environment and ecosystems. This study contributes to a disaster risk framework to identify areas for specific research and adaptation activities on drought disaster risk and for environmental planning in the study area, which is characterised by both rural and urban contexts, to address climate change-related drought impacts.

Keywords: remote sensing, drought disaster, climate scenario, assessment

Procedia PDF Downloads 188

Authors: António J. Gano, Carmen Rangel

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Currently, electric energy storage systems for stationary applications have known an increasing interest, namely with the integration of local renewable energy power sources into energy communities. Li-ion batteries are considered the leading electric storage devices to achieve this integration, and Battery Management Systems (BMS) are decisive for their control and optimum performance. In this work, the advancement of a smart BMS (sBMS) prototype with a modular distributed topology is described. The system, still under development, has a distributed architecture with modular characteristics to operate with different battery pack topologies and charge capacities, integrating adaptive algorithms for functional state real-time monitoring and management of multicellular Li-ion batteries, and is intended for application in the context of a local energy community fed by renewable energy sources. This sBMS system includes different developed hardware units: (1) Cell monitoring units (CMUs) for interfacing with each individual cell or module monitoring within the battery pack; (2) Battery monitoring and switching unit (BMU) for global battery pack monitoring, thermal control and functional operating state switching; (3) Main management and local control unit (MCU) for local sBMS’s management and control, also serving as a communications gateway to external systems and devices. This architecture is fully expandable to battery packs with a large number of cells, or modules, interconnected in series, as the several units have local data acquisition and processing capabilities, communicating over a standard CAN bus and will be able to operate almost autonomously. The CMU units are intended to be used with Li-ion cells but can be used with other cell chemistries, with output voltages within the 2.5 to 5 V range. The different unit’s characteristics and specifications are described, including the different implemented hardware solutions. The developed hardware supports both passive and active methods for charge equalization, considered fundamental functionalities for optimizing the performance and the useful lifetime of a Li-ion battery package. The functional characteristics of the different units of this sBMS system, including different process variables data acquisition using a flexible set of sensors, can support the development of custom algorithms for estimating the parameters defining the functional states of the battery pack (State-of-Charge, State-of-Health, etc.) as well as different charge equalizing strategies and algorithms. This sBMS system is intended to interface with other systems and devices using standard communication protocols, like those used by the Internet of Things. In the future, this sBMS architecture can evolve to a fully decentralized topology, with all the units using Wi-Fi protocols and integrating a mesh network, making unnecessary the MCU unit. The status of the work in progress is reported, leading to conclusions on the system already executed, considering the implemented hardware solution, not only as fully functional advanced and configurable battery management system but also as a platform for developing custom algorithms and optimizing strategies to achieve better performance of electric energy stationary storage devices.

Keywords: Li-ion battery, smart BMS, stationary electric storage, distributed BMS

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Authors: Rogelio Luck, Yucheng Liu

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This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

Procedia PDF Downloads 156

Authors: Tariq Mahmood, Faiza Lehrasab, Faraz Akrim, Muhammad Sajid nadeem, Muhammad Mushtaq, Unza waqar, Ayesha Sheraz, Shaista Andleeb

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Brown bear (Ursus arctos), a member of the family Ursidae, is distributed in a wide range of habitats in North America, Europe and Asia. Suspectedly, the global distribution range of brown bears is decreasing at the moment due to various factors. The carnivore species is categorized as ‘Least Concern’ globally by the IUCN Red List of Threatened Species. However, there are some fragmented, small populations that are on the verge of extinction, as is in Pakistan, where the species is listed as ‘Critically Endangered’, with a declining population trend. Importantly, the global historical distribution range of brown bears is undocumented. Therefore, in the current study, we reconstructed and estimated the historical distribution range of brown bears using QGIS software and also analyzed the network of protected areas in the past and current ranges of the species. Results showed that brown bear was more widely distributed in historic times, encompassing 52.6 million km² area as compared to their current distribution of 38.8 million km², resulting in a total range contraction of up to approximately 28 %. In the past, a total of N = 62,234 protected Areas, covering approximately 3.89 million km² were present in the distribution range of the species, while now a total of N= 33,313 Protected Areas, covering approximately 2.75 million km² area, are present in the current distribution range of the brown bear. The brown bear distribution range in the protected areas has also contracted by 1.15 million km² and the total percentage reduction of PAs is 29%.

Keywords: brown bear, historic distribution, range contraction, protected areas

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Authors: Tridipa Biswas, Kamal Pandey

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A Digital Elevation Model (DEM) is a simple representation of a surface in 3 dimensional space with elevation as the third dimension along with X (horizontal coordinates) and Y (vertical coordinates) in rectangular coordinates. DEM has wide applications in various fields like disaster management, hydrology and watershed management, geomorphology, urban development, map creation and resource management etc. Cartosat-1 or IRS P5 (Indian Remote Sensing Satellite) is a state-of-the-art remote sensing satellite built by ISRO (May 5, 2005) which is mainly intended for cartographic applications.Cartosat-1 is equipped with two panchromatic cameras capable of simultaneous acquiring images of 2.5 meters spatial resolution. One camera is looking at +26 degrees forward while another looks at –5 degrees backward to acquire stereoscopic imagery with base to height ratio of 0.62. The time difference between acquiring of the stereopair images is approximately 52 seconds. The high resolution stereo data have great potential to produce high-quality DEM. The high-resolution Cartosat-1 stereo image data is expected to have significant impact in topographic mapping and watershed applications. The objective of the present study is to generate high-resolution DEM, quality evaluation in different elevation strata, generation of ortho-rectified image and associated accuracy assessment from CARTOSAT-1 data based Ground Control Points (GCPs) for Aglar watershed (Tehri-Garhwal and Dehradun district, Uttarakhand, India). The present study reveals that generated DEMs (10m and 30m) derived from the CARTOSAT-1 stereo pair is much better and accurate when compared with existing DEMs (ASTER and CARTO DEM) also for different terrain parameters like slope, aspect, drainage, watershed boundaries etc., which are derived from the generated DEMs, have better accuracy and results when compared with the other two (ASTER and CARTO) DEMs derived terrain parameters.

Keywords: ASTER-DEM, CARTO-DEM, CARTOSAT-1, digital elevation model (DEM), ortho-rectified image, photogrammetry, RPC, stereo pair, terrain parameters

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Authors: Manikanta Prasad Banda, Che Hua Yang

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Anti-symmetric wave propagation along the particle motion of the wedge waves is known as anti-symmetric flexural (ASF) modes which travel along the wedge tips of the mid-plane apex with a small truncation. This paper investigates the characteristics of the ASF modes propagation with the wedge tip crack. The simulation and experimental results obtained by a three-dimensional (3-D) finite element model explained the contact acoustic non-linear (CAN) behavior in explicit dynamics in ABAQUS and the ultrasonic non-destructive testing (NDT) method is used for defect detection. The effect of various parameters on its high and low-level conversion modes are known for complex reflections and transmissions involved with direct reflections and transmissions. The results are used to predict the location of crack through complex transmission and reflection coefficients.

Keywords: ASF mode, crack detection, finite elements method, laser ultrasound technique, wedge waves

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Authors: Lican Wang, Rongqian Chen, Yancheng You, Ruofan Qiu

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In the applications of jet engine, open-jet wind tunnel and airframe, there wildly exists a shear layer formed by the velocity and temperature gradients between jet flow and surrounded medium. The presence of shear layer will refract and reflect the sound path that consequently influences the measurement results in far-field. To investigate and evaluate the shear layer effect, a gradient term suppression and filtering method is adopted to simulate sound propagation through a steady sheared flow in three dimensions. Two typical configurations are considered: one is an incompressible and cold jet flow in wind tunnel and the other is a compressible and hot jet flow in turbofan engine. A numerically linear microphone array is used to localize the position of given sound source. The localization error is presented and linearly fitted.

Keywords: aeroacoustic, linearized Euler equation, acoustic propagation, source localization

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Authors: Seyed Mahdi Jameii

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Underwater wireless sensor networks have been attracting the interest of many ‎researchers lately, and the past three decades have beheld the rapid progress of ‎underwater acoustic communication. One of the major problems in underwater wireless ‎sensor networks is how to transfer data from the moving node to the base stations and ‎choose the optimized route for data transmission. Secure routing in underwater ‎wireless sensor network (UWCNs) is necessary for packet delivery. Some routing ‎protocols are proposed for underwater wireless sensor networks. However, a few ‎researches have been done on secure routing in underwater sensor networks. In this ‎article, a secure routing protocol is provided to resist against wormhole and sybil ‎attacks. The results indicated acceptable performance in terms of increasing the packet ‎delivery ratio with regards to the attacks, increasing network lifetime by creating ‎balance in the network energy consumption, high detection rates against the attacks, ‎and low-end to end delay.‎

Keywords: attacks, routing, security, underwater wireless sensor networks

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Authors: Samir Chekchaki, ArifaBeddiar

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Nowadays, more and more species are introduced outside their natural range. If most of them remain difficult, some may adopt a much more dynamic behavior. Indeed, we have witnessed in recent decades, the development of high forests of Acacia mearnsii in El Kala National Park. Introduced indefinitely, this leguminous intended to make money (nitrogen supply for industrial plantations of Eucalyptus), became one of the most invasive and more costly in terms of forest management. It has crossed all barriers: it has acclimatized, naturalized and then expanded through diverse landscapes; entry into competition with native species such as cork oak and altered ecosystem functioning. Therefore, it is interesting to analyze this new threat by relying on plants as bio-indicator for assessing biodiversity at different scales. We have identified the species present in several plots distributed in a range of vegetation types subjected to different degrees of disturbance by using the braun-blanquet method. Fifty-six species have been recorded. They are distributed in 48 genera and 29 families. The analysis of the relative frequency of species correlated with relative abundance clearly shows that the Acacia mearnsii feels marginalized. The ecological analysis of this biological invasion shows that disruption of either natural or anthropogenic origin (fire, prolonged drought, cut) represent the factors that exacerbate invasion by opening invasion windows. The lifting of seeds of Acacia mearnsii lasting physical dormancy (and variable) is ensured by the thermal shock in relation to its heliophilous character.

Keywords: Acacia mearnsii De Wild, El Kala National park, fire, invasive, vegetation

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Authors: Lizhi Ma, Dan Liu

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Pipeline parallelism has been widely used to accelerate distributed deep learning to alleviate GPU memory bottlenecks and to ensure that models can be trained and deployed smoothly under limited graphics memory conditions. However, in highly heterogeneous distributed clusters, traditional model partitioning methods are not able to achieve load balancing. The overlap of communication and computation is also a big challenge. In this paper, HePipe is proposed, an efficient pipeline parallel training method for highly heterogeneous clusters. According to the characteristics of the neural network model pipeline training task, oriented to the 2-level heterogeneous cluster computing topology, a training method based on the 2-level stage division of neural network modeling and partitioning is designed to improve the parallelism. Additionally, a multi-forward 1F1B scheduling strategy is designed to accelerate the training time of each stage by executing the computation units in advance to maximize the overlap between the forward propagation communication and backward propagation computation. Finally, a dynamic recomputation strategy based on task memory requirement prediction is proposed to improve the fitness ratio of task and memory, which improves the throughput of the cluster and solves the memory shortfall problem caused by memory differences in heterogeneous clusters. The empirical results show that HePipe improves the training speed by 1.6×−2.2× over the existing asynchronous pipeline baselines.

Keywords: pipeline parallelism, heterogeneous cluster, model training, 2-level stage partitioning

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Authors: Ashok Tejankar, Rohan K. Pathrikar

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Maharashtra is covered by heterogeneous flows of Deccan basaltic terrains of upper cretaceous to lower Eocene age. It consist mainly different types of basalt flow, having heterogeneous Geohydrological characters. The study area Aurangabad dist. lies in the central part of Maharashtra. The study area is typically covered by Deccan traps formation mainly basalt type of igneous volcanic rock. The area is located in the survey of India toposheet No. 47M and laying between 19° to 20° north latitudes and 74° to 76° east longitudes. Groundwater is the primary source for fresh water in the study area. There has been a growing demand for fresh water in domestic & agriculture sectors. Due to over exploitation and rainfall failure has been created an irrecoverable stress on groundwater in study area. In an effort to maintain the water table condition in balance, artificial recharge is being implemented. The selection of site for artificial recharge is a very important task in recharge basalt. The present study aims at sitting artificial recharge structure at village Pachod in basaltic terrain of the Godavari-Purna river basin in Aurangabad district of Maharashtra, India. where the average annual rainfall is 650mm. In this investigation, integrated remote sensing and GIS techniques were used and various parameters like lithology, structure, etc. aspect of drainage basins, landforms and other parameters were extracted from visual interpretation of IRS P6 Satellite data and Survey of India (SIO) topographical sheets, aided by field checks by carrying well inventory survey. The depth of weathered material, water table conditions, and rainfall data were been considered. All the thematic information layers were digitized and analyzed in Arc-GIS environment and the composite maps produced show suitable site, depth of bed rock flows for successful artificial recharge in village Pachod to increase groundwater potential of low laying area.

Keywords: hard rock, artificial recharge, remote sensing, GIS

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Authors: Kyung-Im Han

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This study examines dialect and gender variations in the place and manner of articulation between the two Korean fricatives, /s/ and /s’/, as produced by speakers of the Daegu and Jeju dialects. The acoustic parameters of center of gravity and skewness for the place of articulation, and the rise time and the amplitude rise slope for the manner of articulation were measured. The study results revealed a gender effect, but no dialect effect, for the center of gravity and the skewness. No main effect for either the gender or dialect was found for the rise time and the amplitude rise slope. These findings indicated that, with regard to the place of articulation, Korean fricative sound differences are a gender distinction, not a dialectal one.

Keywords: dialect, gender, Korean fricative, manner of articulation, place of articulation, spectral moments

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Authors: Meriam Khelifa

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In recent years, many studies have focused on the harvesting of the vibrations energy to produce electrical energy using contact separation (CS) triboelectric nanogenerators (TENG). The simplest design for a TENG consists of a capacitor comprising a single moving electrode. The conversion efficiency of vibration energy into electrical energy can, in principle, reach 100%. But to actually achieve this objective, it is necessary to optimize the parameters of the TENG, such as the dielectric constant and the thickness of the insulator, the load resistance, etc. In particular, the use of a switch which is actioned at optimal times within the TENG cycle is essential. Using numerical modeling and experimental design, we applied a methodology to find the TENG parameters which optimize the energy transfer efficiency (ETE) to almost 100% for any vibration frequency and amplitude. The rather simple design of a TENG is promising as an environment friendly device. It opens the doors for harvesting acoustic vibrations from the environment and to design effective protection against environmental noise.

Keywords: vibrations, CS TENG, efficiency, design of experiments

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Authors: Chi Man Luk, Ming Kiu Tsang, Chi Fan Chan, Shu Ping Lau

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Nitrogen-doped graphene quantum dots (N-GQDs) were fabricated by microwave-assisted hydrothermal technique. The optical properties of the N-GQDs were studied. The luminescence of the N-GQDs can be tuned by varying the excitation wavelength. Furthermore, two-photon luminescence of the N-GQDs excited by near-infrared laser can be obtained. It is shown that N-doping play a key role on two-photon luminescence. The N-GQDs are expected to find application in biological applications including bioimaging and sensing.

Keywords: graphene quantum dots, nitrogen doping, photoluminescence, two-photon fluorescence

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Authors: Rani Danavath, V. B. Narsimha

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Cloud computing is emerging as a new paradigm of large scale distributed computing. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., three service models, and four deployment networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics models. Load balancing is one of the main challenges in cloud computing, which is required to distribute the dynamic workload across multiple nodes, to ensure that no single node is overloaded. It helps in optimal utilization of resources, enhancing the performance of the system. The goal of the load balancing is to minimize the resource consumption and carbon emission rate, that is the direct need of cloud computing. This determined the need of new metrics energy consumption and carbon emission for energy-efficiency load balancing techniques in cloud computing. Existing load balancing techniques mainly focuses on reducing overhead, services, response time and improving performance etc. In this paper we introduced a Technique for energy-efficiency, but none of the techniques have considered the energy consumption and carbon emission. Therefore, our proposed work will go towards energy – efficiency. So this energy-efficiency load balancing technique can be used to improve the performance of cloud computing by balancing the workload across all the nodes in the cloud with the minimum resource utilization, in turn, reducing energy consumption, and carbon emission to an extent, which will help to achieve green computing.

Keywords: cloud computing, distributed computing, energy efficiency, green computing, load balancing, energy consumption, carbon emission

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Authors: Cristina Núñez, Rufina Bastida, Elena Labisbal, Alejandro Macías, María T. Pereira, José M. Vila

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A highly selective quinoline-based fluorescent sensor L was designed in order to functionalize gold nanoparticles (GNPs@L). The cytotoxicity of compound L and GNPs@L on the MCF-7 breast cancer cells was explored and it was observed that L and GNPs@L compounds induced apoptosis in MCF-7 cancer cells. The cellular uptake of the hybrid system GNPs@L was studied using confocal laser scanning microscopy (CLSM).

Keywords: cytotoxicity, fluorescent probes, nanoparticles, quinoline

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Authors: Sangseung Kang, Kyekyung Kim, Suyoung Chi

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A good posture is the most important factor in riding. In this paper, we present an effective posture correction system for a riding simulator environment to provide position error detection and customized training functions. The proposed system detects and analyzes the rider's posture using depth data and inertial sensing data. Our experiments show that including these functions will help users improve their seat for a riding.

Keywords: posture correction, posture training, riding posture, riding simulator

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Authors: Yunzhe Tong, Jun Fan, Bin Wang

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The vibroacoustic behavior of an immersed infinite cylindrical shell with periodic lengthwise ribs has been studied in this paper. The motions of the shell are described by the Donnell equations. Each lengthwise rib is modeled as an elastic beam. The motions of the bulkheads are decomposed into the longitudinal motions and flexural motions. The analytical expressions of the shell motions can be obtained through circumferential mode expansion, Fourier Transform and periodic boundary condition in the circumferential direction. Furthermore, the far-field radiated pressure has been obtained using the stationary phase. The analysis of wavenumber domain shows that periodic lengthwise stiffeners in the circumferential direction can produce flexural Bloch waves. The dominant feature in far-field pressure amplitude is the resonance of the supersonic components of the flexural Bloch waves in the circumferential direction.

Keywords: flexural Bloch wave, stiffened shell, vibroacoustics, wavenumber analysis

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Authors: K. Yang, Y. Wei, M. Zhang, S. Yong, R. Torah, J. Tudor, S. Beeby

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E-textiles are traditional textiles with integrated electronic functionality. It is an emerging innovation with numerous applications in fashion, wearable computing, health and safety monitoring, and the military and medical sectors. The piezoelectric effect is a widespread and versatile transduction mechanism used in sensor and actuator applications. Piezoelectric materials produce electric charge when stressed. Conversely, mechanical deformation occurs when an electric field is applied across the material. Lead Zirconate Titanate (PZT) is a widely used piezoceramic material which has been used to fabricate e-textiles through screen printing, electro spinning and hydrothermal synthesis. This paper explores an alternative fabrication process: Spray coating. Spray coating is a straightforward and cost effective fabrication method applicable on both flat and curved surfaces. It can also be applied selectively by spraying through a stencil which enables the required design to be realised on the substrate. This work developed a sprayable PZT based piezoelectric ink consisting of a binder (Fabink-Binder-01), PZT powder (80 % 2 µm and 20 % 0.8 µm) and acetone as a thinner. The optimised weight ratio of PZT/binder is 10:1. The components were mixed using a SpeedMixer DAC 150. The fabrication processes is as follows: 1) Screen print a UV-curable polyurethane interface layer on the textile to create a smooth textile surface. 2) Spray one layer of a conductive silver polymer ink through a pre-designed stencil and dry at 90 °C for 10 minutes to form the bottom electrode. 3) Spray three layers of the PZT ink through a pre-designed stencil and dry at 90 °C for 10 minutes for each layer to form a total thickness of ~250µm PZT layer. 4) Spray one layer of the silver ink through a pre-designed stencil on top of the PZT layer and dry at 90 °C for 10 minutes to form the top electrode. The domains of the PZT elements were aligned by polarising the material at an elevated temperature under a strong electric field. A d33 of 37 pC/N has been achieved after polarising at 90 °C for 6 minutes with an electric field of 3 MV/m. The application of the piezoelectric textile was demonstrated by fabricating a pressure sensor to switch an LED on/off. Other potential applications on e-textiles include motion sensing, energy harvesting, force sensing and a buzzer.

Keywords: piezoelectric, PZT, spray coating, pressure sensor, e-textile

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Authors: Arafan Traore, Teiji Watanabe

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Conakry, the capital city of the Republic of Guinea, has experienced a rapid urban expansion and population increased in the last two decades, which has resulted in remarkable local weather and climate change, raise energy demand and pollution and treating social, economic and environmental development. In this study, the spatiotemporal variation of the land surface temperature (LST) is retrieved to characterize the effect of urban growth on the thermal environment and quantify its relationship with biophysical indices, a normalized difference vegetation index (NDVI) and a normalized difference built up Index (NDBI). Landsat data TM and OLI/TIRS acquired respectively in 1986, 2000 and 2016 were used for LST retrieval and Land use/cover change analysis. A quantitative analysis based on the integration of a remote sensing and a geography information system (GIS) has revealed an important increased in the LST pattern in the average from 25.21°C in 1986 to 27.06°C in 2000 and 29.34°C in 2016, which was quite eminent with an average gain in surface temperature of 4.13°C over 30 years study period. Additionally, an analysis using a Pearson correlation (r) between (LST) and the biophysical indices, normalized difference vegetation index (NDVI) and a normalized difference built-up Index (NDBI) has revealed a negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. Which implies that an increase in the NDVI value can reduce the LST intensity; conversely increase in NDBI value may strengthen LST intensity in the study area. Although Landsat data were found efficient in assessing the thermal environment in Conakry, however, the method needs to be refined with in situ measurements of LST in the future studies. The results of this study may assist urban planners, scientists and policies makers concerned about climate variability to make decisions that will enhance sustainable environmental practices in Conakry.

Keywords: Conakry, land surface temperature, urban heat island, geography information system, remote sensing, land use/cover change

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Authors: B. Atli-Veltin, A. Vosteen, D. Megan, A. Jedynska, L. K. Cheng

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Composite materials combine the advantages of being lightweight and possessing high strength. This is in particular of interest for the development of large constructions, e.g., aircraft, space applications, wind turbines, etc. One of the shortcomings of using composite materials is the complex nature of the failure mechanisms which makes it difficult to predict the remaining lifetime. Therefore, condition and health monitoring are essential for using composite material for critical parts of a construction. Different types of sensors are used/developed to monitor composite structures. These include ultrasonic, thermography, shearography and fiber optic. The first 3 technologies are complex and mostly used for measurement in laboratory or during maintenance of the construction. Optical fiber sensor can be surface mounted or embedded in the composite construction to provide the unique advantage of in-operation measurement of mechanical strain and other parameters of interest. This is identified to be a promising technology for Structural Health Monitoring (SHM) or Prognostic Health Monitoring (PHM) of composite constructions. Among the different fiber optic sensing technologies, Fiber Bragg Grating (FBG) sensor is the most mature and widely used. FBG sensors can be realized in an array configuration with many FBGs in a single optical fiber. In the current project, different aspects of using embedded FBG for composite wind turbine monitoring are investigated. The activities are divided into two parts. Firstly, FBG embedded carbon composite laminate is subjected to tensile and bending loading to investigate the response of FBG which are placed in different orientations with respect to the fiber. Secondly, the demonstration of using FBG sensor array for temperature and strain sensing and monitoring of a 5 m long scale model of a glass fiber mono-pile is investigated. Two different FBG types are used; special in-house fibers and off-the-shelf ones. The results from the first part of the study are showing that the FBG sensors survive the conditions during the production of the laminate. The test results from the tensile and the bending experiments are indicating that the sensors successfully response to the change of strain. The measurements from the sensors will be correlated with the strain gauges that are placed on the surface of the laminates.

Keywords: Fiber Bragg Gratings, embedded sensors, health monitoring, wind turbine towers

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Authors: Ye Wang, Ickjai Lee

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Due to the widespread of mobile sensing, there is a strong need to handle trails of moving objects, trajectories. This paper proposes three visual analytic approaches for higher order information of trajectory data sets based on the higher order Voronoi diagram data structure. Proposed approaches reveal geometrical information, topological, and directional information. Experimental results demonstrate the applicability and usefulness of proposed three approaches.

Keywords: visual analytics, higher order information, trajectory datasets, spatio-temporal data

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Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Mohamed Gouda

Abstract:

Antibacterial wound dressings based on cellulose nanofibers containing different metal nanoparticles (CMC-MNPs) were synthesized using an electrospinning technique. First, the composite of carboxymethyl cellulose containing different metal nanoparticles (CMC/MNPs), such as copper nanoparticles (CuNPs), iron nanoparticles (FeNPs), zinc nanoparticles (ZnNPs), cadmium nanoparticles (CdNPs) and cobalt nanoparticles (CoNPs) were synthesized, and finally, these composites were transferred to the electrospinning process. Synthesized CMC-MNPs were characterized using scanning electron microscopy (SEM) coupled with high-energy dispersive X-ray (EDX) and UV-visible spectroscopy used to confirm nanoparticle formation. The SEM images clearly showed regular flat shapes with semi-porous surfaces. All MNPs were well distributed inside the backbone of the cellulose without aggregation. The average particle diameters were 29-39 nm for ZnNPs, 29-33 nm for CdNPs, 25-33 nm for CoNPs, 23-27 nm for CuNPs and 22-26 nm for FeNPs. Surface morphology, water uptake and release of MNPs from the nanofibers in water and antimicrobial efficacy were studied. SEM images revealed that electrospun CMC-MNPs nanofibers are smooth and uniformly distributed without bead formation with average fiber diameters in the range of 300 to 450 nm. Fiber diameters were not affected by the presence of MNPs. TEM images showed that MNPs are present in/on the electrospun CMC-MNPs nanofibers. The diameter of the electrospun nanofibers containing MNPs was in the range of 300–450 nm. The MNPs were observed to be spherical in shape. The CMC-MNPs nanofibers showed good hydrophilic properties and had excellent antibacterial activity against the Gram-negative bacteria Escherichia coli and the Gram-positive bacteria Staphylococcus aureus.

Keywords: electrospinning technique, metal nanoparticles, cellulosic nanofibers, wound dressing

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Authors: Iliya Dimitrov Stoev, Benjamin Seelbinder, Elena Erben, Nicola Maghelli, Moritz Kreysing

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Despite the revolutionizing impact of optical tweezers in materials science and cell biology up to the present date, trapping has so far extensively relied on specific material properties of the probe and local heating has limited applications related to investigating dynamic processes within living systems. To overcome these limitations while maintaining high sensitivity, here we present a new optofluidic approach that can be used to gently trap microscopic particles and measure femtoNewton forces in a contact-free manner and with thermally limited precision.

Keywords: optofluidics, force measurements, microrheology, FLUCS, thermoviscous flows

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Authors: Julian Wise

Abstract:

Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Weijing Zhou, Yuting Lei, Francis Nolan

Abstract:

In the domain of second language acquisition, whenever pronunciation errors or acquisition difficulties are found, researchers habitually attribute them to the negative transfer of the native language or local dialect. To what extent do Mandarin and local dialects affect English phonological acquisition for Chinese learners of English as a foreign language (EFL)? Little evidence, however, has been found via empirical research in China. To address this core issue, the present study conducted phonetic experiments to explore the roles of local dialects and Mandarin in Chinese EFL learners’ acquisition of L2 English consonants. Besides Mandarin, the sole national language in China, Suzhou dialect was selected as the target local dialect because of its distinct phonology from Mandarin. The experimental group consisted of 30 junior English majors at Yangzhou University, who were born and lived in Suzhou, acquired Suzhou Dialect since their early childhood, and were able to communicate freely and fluently with each other in Suzhou Dialect, Mandarin as well as English. The consonantal target segments were all the consonants of English, Mandarin and Suzhou Dialect in typical carrier words embedded in the carrier sentence Say again. The control group consisted of two Suzhou Dialect experts, two Mandarin radio broadcasters, and two British RP phoneticians, who served as the standard speakers of the three languages. The reading corpus was recorded and sampled in the phonetic laboratories at Yangzhou University, Soochow University and Cambridge University, respectively, then transcribed, segmented and analyzed acoustically via Praat software, and finally analyzed statistically via EXCEL and SPSS software. The main findings are as follows: First, in terms of correct acquisition rates (CARs) of all the consonants, Mandarin ranked top (92.83%), English second (74.81%) and Suzhou Dialect last (70.35%), and significant differences were found only between the CARs of Mandarin and English and between the CARs of Mandarin and Suzhou Dialect, demonstrating Mandarin was overwhelmingly more robust than English or Suzhou Dialect in subjects’ multilingual phonological ecology. Second, in terms of typical acoustic features, the average duration of all the consonants plus the voice onset time (VOT) of plosives, fricatives, and affricatives in 3 languages were much longer than those of standard speakers; the intensities of English fricatives and affricatives were higher than RP speakers but lower than Mandarin and Suzhou Dialect standard speakers; the formants of English nasals and approximants were significantly different from those of Mandarin and Suzhou Dialects, illustrating the inconsistent acoustic variations between the 3 languages. Thirdly, in terms of typical pronunciation variations or errors, there were significant interlingual interactions between the 3 consonant systems, in which Mandarin consonants were absolutely dominant, accounting for the strong transfer from L1 Mandarin to L2 English instead of from earlier-acquired L1 local dialect to L2 English. This is largely because the subjects were knowingly exposed to Mandarin since their nursery and were strictly required to speak in Mandarin through all the formal education periods from primary school to university.

Keywords: acquisition of L2 English consonants, role of Mandarin, role of local dialect, Chinese EFL learners from Suzhou Dialect areas

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

Abstract:

Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

Procedia PDF Downloads 95