Search results for: vapor sensors
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1642

Search results for: vapor sensors

292 Monodisperse Quaternary Cobalt Chromium Ferrite Nanoparticles Synthesised from a Single Source Precursor

Authors: Khadijat O. Abdulwahab, Mohammad A. Malik, Paul O’Brien, Grigore A. Timco, Floriana Tuna

Abstract:

The synthesis of spinel ferrite nanoparticles with a narrow size distribution is very crucial in their numerous applications including information storage, hyperthermia treatment, drug delivery, contrast agent in magnetic resonance imaging, catalysis, sensors, and environmental remediation. Ferrites have the general formula MFe2O4 (M = Fe, Co, Mn, Ni, Zn etc.) and possess remarkable electrical and magnetic properties which depend on the cations, method of preparation, size and their site occupancies. To the best of our knowledge, there are no reports on the use of a single source precursor to synthesise quaternary ferrite nanoparticles. Herein, we demonstrated the use of trimetallic iron pivalate cluster [CrCoFeO(O2CtBu)6(HO2CtBu)3] as a single source precursor to synthesise monodisperse cobalt chromium ferrite (FeCoCrO4) nanoparticles by the hot injection thermolysis method. The precursor was thermolysed in oleylamine, oleic acid, with diphenyl ether as solvent at its boiling point (260°C). The effect of concentration on the stoichiometry, phases or morphology of the nanoparticles was studied. The p-XRD patterns of the nanoparticles obtained at both concentrations were matched with cubic iron cobalt chromium ferrite (FeCoCrO4). TEM showed that a more monodispersed spherical ferrite nanoparticles of average diameter 4.0 ± 0.4 nm were obtained at higher precursor concentration. Magnetic measurements revealed that all the ferrite particles are superparamagnetic at room temperature. The nanoparticles were characterised by Powder X-ray Diffraction (p-XRD), Transmission Electron Microscopy (TEM), Inductively Coupled Plasma (ICP), Electron Probe Microanalysis (EPMA), Energy Dispersive Spectroscopy (EDS) and Super Conducting Quantum Interference Device (SQUID).

Keywords: quaternary ferrite nanoparticles, single source precursor, monodisperse, cobalt chromium ferrite, colloidal, hot injection thermolysis

Procedia PDF Downloads 252
291 Survey of Communication Technologies for IoT Deployments in Developing Regions

Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

Abstract:

The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

Procedia PDF Downloads 62
290 Energy Efficiency of Secondary Refrigeration with Phase Change Materials and Impact on Greenhouse Gases Emissions

Authors: Michel Pons, Anthony Delahaye, Laurence Fournaison

Abstract:

Secondary refrigeration consists of splitting large-size direct-cooling units into volume-limited primary cooling units complemented by secondary loops for transporting and distributing cold. Such a design reduces the refrigerant leaks, which represents a source of greenhouse gases emitted into the atmosphere. However, inserting the secondary circuit between the primary unit and the ‘users’ heat exchangers (UHX) increases the energy consumption of the whole process, which induces an indirect emission of greenhouse gases. It is thus important to check whether that efficiency loss is sufficiently limited for the change to be globally beneficial to the environment. Among the likely secondary fluids, phase change slurries offer several advantages: they transport latent heat, they stabilize the heat exchange temperature, and the formerly evaporators still can be used as UHX. The temperature level can also be adapted to the desired cooling application. Herein, the slurry {ice in mono-propylene-glycol solution} (melting temperature Tₘ of 6°C) is considered for food preservation, and the slurry {mixed hydrate of CO₂ + tetra-n-butyl-phosphonium-bromide in aqueous solution of this salt + CO₂} (melting temperature Tₘ of 13°C) is considered for air conditioning. For the sake of thermodynamic consistency, the analysis encompasses the whole process, primary cooling unit plus secondary slurry loop, and the various properties of the slurries, including their non-Newtonian viscosity. The design of the whole process is optimized according to the properties of the chosen slurry and under explicit constraints. As a first constraint, all the units must deliver the same cooling power to the user. The other constraints concern the heat exchanges areas, which are prescribed, and the flow conditions, which prevent deposition of the solid particles transported in the slurry, and their agglomeration. Minimization of the total energy consumption leads to the optimal design. In addition, the results are analyzed in terms of exergy losses, which allows highlighting the couplings between the primary unit and the secondary loop. One important difference between the ice-slurry and the mixed-hydrate one is the presence of gaseous carbon dioxide in the latter case. When the mixed-hydrate crystals melt in the UHX, CO₂ vapor is generated at a rate that depends on the phase change kinetics. The flow in the UHX, and its heat and mass transfer properties are significantly modified. This effect has never been investigated before. Lastly, inserting the secondary loop between the primary unit and the users increases the temperature difference between the refrigerated space and the evaporator. This results in a loss of global energy efficiency, and therefore in an increased energy consumption. The analysis shows that this loss of efficiency is not critical in the first case (Tₘ = 6°C), while the second case leads to more ambiguous results, partially because of the higher melting temperature.The consequences in terms of greenhouse gases emissions are also analyzed.

Keywords: exergy, hydrates, optimization, phase change material, thermodynamics

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289 Mitigating Food Insecurity and Malnutrition by Promoting Carbon Farming via a Solar-Powered Enzymatic Composting Bioreactor with Arduino-Based Sensors

Authors: Molin A., De Ramos J. M., Cadion L. G., Pico R. L.

Abstract:

Malnutrition and food insecurity represent significant global challenges affecting millions of individuals, particularly in low-income and developing regions. The researchers created a solar-powered enzymatic composting bioreactor with an Arduino-based monitoring system for pH, humidity, and temperature. It manages mixed municipal solid wastes incorporating industrial enzymes and whey additives for accelerated composting and minimized carbon footprint. Within 15 days, the bioreactor yielded 54.54% compost compared to 44.85% from traditional methods, increasing yield by nearly 10%. Tests showed that the bioreactor compost had 4.84% NPK, passing metal analysis standards, while the traditional pit compost had 3.86% NPK; both are suitable for agriculture. Statistical analyses, including ANOVA and Tukey's HSD test, revealed significant differences in agricultural yield across different compost types based on leaf length, width, and number of leaves. The study compared the effects of different composts on Brassica rapa subsp. Chinesis (Petchay) and Brassica juncea (Mustasa) plant growth. For Pechay, significant effects of compost type on plant leaf length (F(5,84) = 62.33, η² = 0.79) and leaf width (F(5,84) = 12.35, η² = 0.42) were found. For Mustasa, significant effects of compost type on leaf length (F(4,70) = 20.61, η² = 0.54), leaf width (F(4,70) = 19.24, η² = 0.52), and number of leaves (F(4,70) = 13.17, η² = 0.43) were observed. This study explores the effectiveness of the enzymatic composting bioreactor and its viability in promoting carbon farming as a solution to food insecurity and malnutrition.

Keywords: malnutrition, food insecurity, enzymatic composting bioreactor, arduino-based monitoring system, enzymes, carbon farming, whey additive, NPK level

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288 Evaluation of IMERG Performance at Estimating the Rainfall Properties through Convective and Stratiform Rain Events in a Semi-Arid Region of Mexico

Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

Abstract:

Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

Procedia PDF Downloads 48
287 Hedgerow Detection and Characterization Using Very High Spatial Resolution SAR DATA

Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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286 Sizing and Thermal Analysis of Mechanically Pumped Fluid Loop Thermal Control Technique for Small Satellite Scientific Applications

Authors: Shanmugasundaram Selvadurai, Amal Chandran

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Small satellites have become an alternative low-cost solution for several missions to accomplish specific missions such as Earth imaging, Technology demonstration, Education, and other commercial purposes. Small satellite missions focusing on Infrared imaging applications require lower temperature for scientific instruments and such low temperature can be achieved only using external cryocoolers but the disadvantage is that they generate a large amount of waste heat. Existing passive thermal control techniques are not capable to handle such large thermal loads and hence one of the traditional active Thermal Control System (TCS) is studied for a small satellite configuration. This work aims to downscale the existing Mechanically Pumped Fluid Loop (MPFL) TCS to a 27U CubeSat platform for an imaginary scientific instrument. The temperature-sensitive detector in the instrument considered to be maintained between 130K and 150K to reduce dark current noise and increase the data quality. A Single-Phase fluid based MPFL is chosen for this system-level study and this TCS consists of a microfluid pump, a micro-cryocooler, a fluid accumulator, external heaters, flow regulators, and sensors. This work also explains the thermal control system architecture with a conceptual design, arrangement of all the components, and thermal analysis for different low orbit conditions. Sizing and extensive trade studies for the components are conducted and the results have shown that the Single-phase MPFL system is able to handle the given thermal loads and maintain the satellite’s interface temperature within the desired limit.

Keywords: active thermal control system, satellite thermal, mechanically pumped fluid loop system, cryogenics, cryocooler

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285 Depth Camera Aided Dead-Reckoning Localization of Autonomous Mobile Robots in Unstructured GNSS-Denied Environments

Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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284 Validity of a Timing System in the Alpine Ski Field: A Magnet-Based Timing System Using the Magnetometer Built into an Inertial Measurement Units

Authors: Carla Pérez-Chirinos Buxadé, Bruno Fernández-Valdés, Mónica Morral-Yepes, Sílvia Tuyà Viñas, Josep Maria Padullés Riu, Gerard Moras Feliu

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There is a long way to explore all the possible applications inertial measurement units (IMUs) have in the sports field. The aim of this study was to evaluate the validity of a new application on the use of these wearable sensors, specifically it was to evaluate a magnet-based timing system (M-BTS) for timing gate-to-gate in an alpine ski slalom using the magnetometer embedded in an IMU. This was a validation study. The criterion validity of time measured by the M-BTS was assessed using the 95% error range against actual time obtained from photocells. The experiment was carried out with first-and second-year junior skiers performing a ski slalom on a ski training slope. Eight alpine skiers (17.4 ± 0.8 years, 176.4 ± 4.9 cm, 67.7 ± 2.0 kg, 128.8 ± 26.6 slalom FIS-Points) participated in the study. An IMU device was attached to the skier’s lower back. Skiers performed a 40-gate slalom from which four gates were assessed. The M-BTS consisted of placing four bar magnets buried into the snow surface on the inner side of each gate’s turning pole; the magnetometer built into the IMU detected the peak-shaped magnetic field when passing near the magnets at a certain speed. Four magnetic peaks were detected. The time compressed between peaks was calculated. Three inter-gate times were obtained for each system: photocells and M-BTS. The total time was defined as the time sum of the inter-gate times. The 95% error interval for the total time was 0.050 s for the ski slalom. The M-BTS is valid for timing gate-to-gate in an alpine ski slalom. Inter-gate times can provide additional data for analyzing a skier’s performance, such as asymmetries between left and right foot.

Keywords: gate crossing time, inertial measurement unit, timing system, wearable sensor

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283 Empirical Investigations on Speed Differentiations of Traffic Flow: A Case Study on a Basic Freeway Segment of O-2 in Istanbul

Authors: Hamed Rashid Sarand, Kemal Selçuk Öğüt

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Speed is one of the fundamental variables of road traffic flow that stands as an important evaluation criterion for traffic analyses in several aspects. In particular, varieties of speed variable, such as average speed, free flow speed, optimum speed (capacity speed), acceleration/deceleration speed and so on, have been explicitly considered in the analysis of not only road safety but also road capacity. In the purpose of realizing 'road speed – maximum speed difference across lanes' and 'road flow rate – maximum speed difference across lanes' relations on freeway traffic, this study presents a case study conducted on a basic freeway segment of O-2 in Istanbul. The traffic data employed in this study have been obtained from 5 remote traffic microwave sensors operated by Istanbul Metropolitan Municipality. The study stretch is located between two successive freeway interchanges: Ümraniye and Kavacık. Daily traffic data of 4 years (2011-2014) summer months, July and August are used. The speed data are analyzed into two main flow areas such as uncongested and congested flows. In this study, the regression analyses were carried out in order to examine the relationship between maximum speed difference across lanes and road speed. These investigations were implemented at uncongested and congested flows, separately. Moreover, the relationship between maximum speed difference across lanes and road flow rate were evaluated by applying regression analyses for both uncongested and congested flows separately. It is concluded that there is the moderate relationship between maximum speed difference across lanes and road speed in 50% cases. Additionally, it is indicated that there is the moderate relationship between maximum speed difference across lanes and road flow rate in 30% cases. The maximum speed difference across lanes decreases as the road flow rate increases.

Keywords: maximum speed difference, regression analysis, remote traffic microwave sensor, speed differentiation, traffic flow

Procedia PDF Downloads 341
282 Earth Observations and Hydrodynamic Modeling to Monitor and Simulate the Oil Pollution in the Gulf of Suez, Red Sea, Egypt

Authors: Islam Abou El-Magd, Elham Ali, Moahmed Zakzouk, Nesreen Khairy, Naglaa Zanaty

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Maine environment and coastal zone are wealthy with natural resources that contribute to the local economy of Egypt. The Gulf of Suez and Red Sea area accommodates diverse human activities that contribute to the local economy, including oil exploration and production, touristic activities, export and import harbors, etc, however, it is always under the threat of pollution due to human interaction and activities. This research aimed at integrating in-situ measurements and remotely sensed data with hydrodynamic model to map and simulate the oil pollution. High-resolution satellite sensors including Sentinel 2 and Plantlab were functioned to trace the oil pollution. Spectral band ratio of band 4 (infrared) over band 3 (red) underpinned the mapping of the point source pollution from the oil industrial estates. This ratio is supporting the absorption windows detected in the hyperspectral profiles. ASD in-situ hyperspectral device was used to measure experimentally the oil pollution in the marine environment. The experiment used to measure water behavior in three cases a) clear water without oil, b) water covered with raw oil, and c) water after a while from throwing the raw oil. The spectral curve is clearly identified absorption windows for oil pollution, particularly at 600-700nm. MIKE 21 model was applied to simulate the dispersion of the oil contamination and create scenarios for crises management. The model requires precise data preparation of the bathymetry, tides, waves, atmospheric parameters, which partially obtained from online modeled data and other from historical in-situ stations. The simulation enabled to project the movement of the oil spill and could create a warning system for mitigation. Details of the research results will be described in the paper.

Keywords: oil pollution, remote sensing, modelling, Red Sea, Egypt

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281 Information Visualization Methods Applied to Nanostructured Biosensors

Authors: Osvaldo N. Oliveira Jr.

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The control of molecular architecture inherent in some experimental methods to produce nanostructured films has had great impact on devices of various types, including sensors and biosensors. The self-assembly monolayers (SAMs) and the electrostatic layer-by-layer (LbL) techniques, for example, are now routinely used to produce tailored architectures for biosensing where biomolecules are immobilized with long-lasting preserved activity. Enzymes, antigens, antibodies, peptides and many other molecules serve as the molecular recognition elements for detecting an equally wide variety of analytes. The principles of detection are also varied, including electrochemical methods, fluorescence spectroscopy and impedance spectroscopy. In this presentation an overview will be provided of biosensors made with nanostructured films to detect antibodies associated with tropical diseases and HIV, in addition to detection of analytes of medical interest such as cholesterol and triglycerides. Because large amounts of data are generated in the biosensing experiments, use has been made of computational and statistical methods to optimize performance. Multidimensional projection techniques such as Sammon´s mapping have been shown more efficient than traditional multivariate statistical analysis in identifying small concentrations of anti-HIV antibodies and for distinguishing between blood serum samples of animals infected with two tropical diseases, namely Chagas´ disease and Leishmaniasis. Optimization of biosensing may include a combination of another information visualization method, the Parallel Coordinate technique, with artificial intelligence methods in order to identify the most suitable frequencies for reaching higher sensitivity using impedance spectroscopy. Also discussed will be the possible convergence of technologies, through which machine learning and other computational methods may be used to treat data from biosensors within an expert system for clinical diagnosis.

Keywords: clinical diagnosis, information visualization, nanostructured films, layer-by-layer technique

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280 Controlled Nano Texturing in Silicon Wafer for Excellent Optical and Photovoltaic Properties

Authors: Deb Kumar Shah, M. Shaheer Akhtar, Ha Ryeon Lee, O-Bong Yang, Chong Yeal Kim

Abstract:

The crystalline silicon (Si) solar cells are highly renowned photovoltaic technology and well-established as the commercial solar technology. Most of the solar panels are globally installed with the crystalline Si solar modules. At the present scenario, the major photovoltaic (PV) market is shared by c-Si solar cells, but the cost of c-Si panels are still very high as compared with the other PV technology. In order to reduce the cost of Si solar panels, few necessary steps such as low-cost Si manufacturing, cheap antireflection coating materials, inexpensive solar panel manufacturing are to be considered. It is known that the antireflection (AR) layer in c-Si solar cell is an important component to reduce Fresnel reflection for improving the overall conversion efficiency. Generally, Si wafer exhibits the 30% reflection because it normally poses the two major intrinsic drawbacks such as; the spectral mismatch loss and the high Fresnel reflection loss due to the high contrast of refractive indices between air and silicon wafer. In recent years, researchers and scientists are highly devoted to a lot of researches in the field of searching effective and low-cost AR materials. Silicon nitride (SiNx) is well-known AR materials in commercial c-Si solar cells due to its good deposition and interaction with passivated Si surfaces. However, the deposition of SiNx AR is usually performed by expensive plasma enhanced chemical vapor deposition (PECVD) process which could have several demerits like difficult handling and damaging the Si substrate by plasma when secondary electrons collide with the wafer surface for AR coating. It is very important to explore new, low cost and effective AR deposition process to cut the manufacturing cost of c-Si solar cells. One can also be realized that a nano-texturing process like the growth of nanowires, nanorods, nanopyramids, nanopillars, etc. on Si wafer can provide a low reflection on the surface of Si wafer based solar cells. The above nanostructures might be enhanced the antireflection property which provides the larger surface area and effective light trapping. In this work, we report on the development of crystalline Si solar cells without using the AR layer. The Silicon wafer was modified by growing nanowires like Si nanostructures using the wet controlled etching method and directly used for the fabrication of Si solar cell without AR. The nanostructures over Si wafer were optimized in terms of sizes, lengths, and densities by changing the etching conditions. Well-defined and aligned wires like structures were achieved when the etching time is 20 to 30 min. The prepared Si nanostructured displayed the minimum reflectance ~1.64% at 850 nm with the average reflectance of ~2.25% in the wavelength range from 400-1000 nm. The nanostructured Si wafer based solar cells achieved the comparable power conversion efficiency in comparison with c-Si solar cells with SiNx AR layer. From this study, it is confirmed that the reported method (controlled wet etching) is an easy, facile method for preparation of nanostructured like wires on Si wafer with low reflectance in the whole visible region, which has greater prospects in developing c-Si solar cells without AR layer at low cost.

Keywords: chemical etching, conversion efficiency, silicon nanostructures, silicon solar cells, surface modification

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279 Energy Efficient Autonomous Lower Limb Exoskeleton for Human Motion Enhancement

Authors: Nazim Mir-Nasiri, Hudyjaya Siswoyo Jo

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The paper describes conceptual design, control strategies, and partial simulation for a new fully autonomous lower limb wearable exoskeleton system for human motion enhancement that can support its weight and increase strength and endurance. Various problems still remain to be solved where the most important is the creation of a power and cost efficient system that will allow an exoskeleton to operate for extended period without batteries being frequently recharged. The designed exoskeleton is enabling to decouple the weight/mass carrying function of the system from the forward motion function which reduces the power and size of propulsion motors and thus the overall weight, cost of the system. The decoupling takes place by blocking the motion at knee joint by placing passive air cylinder across the joint. The cylinder is actuated when the knee angle has reached the minimum allowed value to bend. The value of the minimum bending angle depends on usual walk style of the subject. The mechanism of the exoskeleton features a seat to rest the subject’s body weight at the moment of blocking the knee joint motion. The mechanical structure of each leg has six degrees of freedom: four at the hip, one at the knee, and one at the ankle. Exoskeleton legs are attached to subject legs by using flexible cuffs. The operation of all actuators depends on the amount of pressure felt by the feet pressure sensors and knee angle sensor. The sensor readings depend on actual posture of the subject and can be classified in three distinct cases: subject stands on one leg, subject stands still on both legs and subject stands on both legs but transit its weight from one leg to other. This exoskeleton is power efficient because electrical motors are smaller in size and did not participate in supporting the weight like in all other existing exoskeleton designs.

Keywords: energy efficient system, exoskeleton, motion enhancement, robotics

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278 Remote Vital Signs Monitoring in Neonatal Intensive Care Unit Using a Digital Camera

Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

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Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The RMSE between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition

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277 pH and Temperature Triggered Release of Doxorubicin from Hydogen Bonded Multilayer Films of Polyoxazolines

Authors: Meltem Haktaniyan, Eda Cagli, Irem Erel Goktepe

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Polymers that change their properties in response to different stimuli (e.g. light, temperature, pH, ionic strength or magnetic field) are called ‘smart’ or ‘stimuli-responsive polymers’. These polymers have been widely used in biomedical applications such as sensors, gene delivery, drug delivery or tissue engineering. Temperature-responsive polymers have been studied extensively for controlled drug delivery applications. As regard of pseudo-peptides, poly (2-alky-2-oxazoline)s are considered as good candidates for delivery systems due to their stealth behavior and nontoxicity. In order to build responsive multilayer films for controlled drug release applications from surface, Layer by layer technique (LBL) is a powerful technique with an advantage of nanometer scale control over spatial architecture and morphology. Multilayers can be constructed on surface where non-covalent interactions including electrostatic interactions, hydrogen bonding, and charge-transfer or hydrophobic-hydrophobic interactions. In the present study, hydrogen bounded multilayer films of poly (2-alky-2-oxazoline) s with tannic acid were prepared in order to use as a platform to release Doxorubicin (DOX) from surface with pH and thermal triggers. For this purpose, poly (2-isopropyl-2-oxazoline) (PIPOX) and poly (2-ethyl-2-oxazoline) (PETOX) were synthesized via cationic ring opening polymerization (CROP) with hydroxyl end groups. Two polymeric multilayer systems ((PETOX)/(DOX)-(TA) complexes and (PIPOX)/(DOX)-(TA) complexes) were designed to investigate of controlled release of Doxorubicin (DOX) from surface with pH and thermal triggers. The drug release profiles from the multilayer thin films with alterations of pH and temperature will been examined with UV-Vis Spectroscopy and Fluorescence Spectroscopy.

Keywords: temperature responsive polymers, h-bonded multilayer films, drug release, polyoxazoline

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276 The AI Method and System for Analyzing Wound Status in Wound Care Nursing

Authors: Ho-Hsin Lee, Yue-Min Jiang, Shu-Hui Tsai, Jian-Ren Chen, Mei-Yu XU, Wen-Tien Wu

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This project presents an AI-based method and system for wound status analysis. The system uses a three-in-one sensor device to analyze wound status, including color, temperature, and a 3D sensor to provide wound information up to 2mm below the surface, such as redness, heat, and blood circulation information. The system has a 90% accuracy rate, requiring only one manual correction in 70% of cases, with a one-second delay. The system also provides an offline application that allows for manual correction of the wound bed range using color-based guidance to estimate wound bed size with 96% accuracy and a maximum of one manual correction in 96% of cases, with a one-second delay. Additionally, AI-assisted wound bed range selection achieves 100% of cases without manual intervention, with an accuracy rate of 76%, while AI-based wound tissue type classification achieves an 85.3% accuracy rate for five categories. The AI system also includes similar case search and expert recommendation capabilities. For AI-assisted wound range selection, the system uses WIFI6 technology, increasing data transmission speeds by 22 times. The project aims to save up to 64% of the time required for human wound record keeping and reduce the estimated time to assess wound status by 96%, with an 80% accuracy rate. Overall, the proposed AI method and system integrate multiple sensors to provide accurate wound information and offer offline and online AI-assisted wound bed size estimation and wound tissue type classification. The system decreases delay time to one second, reduces the number of manual corrections required, saves time on wound record keeping, and increases data transmission speed, all of which have the potential to significantly improve wound care and management efficiency and accuracy.

Keywords: wound status analysis, AI-based system, multi-sensor integration, color-based guidance

Procedia PDF Downloads 85
275 Corrosion Protective Coatings in Machines Design

Authors: Cristina Diaz, Lucia Perez, Simone Visigalli, Giuseppe Di Florio, Gonzalo Fuentes, Roberto Canziani, Paolo Gronchi

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During the last 50 years, the selection of materials is one of the main decisions in machine design for different industrial applications. It is due to numerous physical, chemical, mechanical and technological factors to consider in it. Corrosion effects are related with all of these factors and impact in the life cycle, machine incidences and the costs for the life of the machine. Corrosion affects the deterioration or destruction of metals due to the reaction with the environment, generally wet. In food industry, dewatering industry, concrete industry, paper industry, etc. corrosion is an unsolved problem and it might introduce some alterations of some characteristics in the final product. Nowadays, depending on the selected metal, its surface and its environment of work, corrosion prevention might be a change of metal, use a coating, cathodic protection, use of corrosion inhibitors, etc. In the vast majority of the situations, use of a corrosion resistant material or in its defect, a corrosion protection coating is the solution. Stainless steels are widely used in machine design, because of their strength, easily cleaned capacity, corrosion resistance and appearance. Typical used are AISI 304 and AISI 316. However, their benefits don’t fit every application, and some coatings are required against corrosion such as some paintings, galvanizing, chrome plating, SiO₂, TiO₂ or ZrO₂ coatings, etc. In this work, some coatings based in a bilayer made of Titanium-Tantalum, Titanium-Niobium, Titanium-Hafnium or Titanium-Zirconium, have been developed used magnetron sputtering configuration by PVD (Physical Vapor Deposition) technology, for trying to reduce corrosion effects on AISI 304, AISI 316 and comparing it with Titanium alloy substrates. Ti alloy display exceptional corrosion resistance to chlorides, sour and oxidising acidic media and seawater. In this study, Ti alloy (99%) has been included for comparison with coated AISI 304 and AISI 316 stainless steel. Corrosion tests were conducted by a Gamry Instrument under ASTM G5-94 standard, using different electrolytes such as tomato salsa, wine, olive oil, wet compost, a mix of sand and concrete with water and NaCl for testing corrosion in different industrial environments. In general, in all tested environments, the results showed an improvement of corrosion resistance of all coated AISI 304 and AISI 316 stainless steel substrates when they were compared to uncoated stainless steel substrates. After that, comparing these results with corrosion studies on uncoated Ti alloy substrate, it was observed that in some cases, coated stainless steel substrates, reached similar current density that uncoated Ti alloy. Moreover, Titanium-Zirconium and Titanium-Tantalum coatings showed for all substrates in study including coated Ti alloy substrates, a reduction in current density more than two order in magnitude. As conclusion, Ti-Ta, Ti-Zr, Ti-Nb and Ti-Hf coatings have been developed for improving corrosion resistance of AISI 304 and AISI 316 materials. After corrosion tests in several industry environments, substrates have shown improvements on corrosion resistance. Similar processes have been carried out in Ti alloy (99%) substrates. Coated AISI 304 and AISI 316 stainless steel, might reach similar corrosion protection on the surface than uncoated Ti alloy (99%). Moreover, coated Ti Alloy (99%) might increase its corrosion resistance using these coatings.

Keywords: coatings, corrosion, PVD, stainless steel

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274 Multi-Functional Metal Oxides as Gas Sensors, Photo-Catalysts and Bactericides

Authors: Koyar Rane

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Nano- to submicron size particles of narrow particle size distribution of semi-conducting TiO₂, ZnO, NiO, CuO, Fe₂O₃ have been synthesized by novel hydrazine method and tested for their gas sensing, photocatalytic and bactericidal activities and the behavior found to be enhanced when the oxides in the thin film forms, that obtained in a specially built spray pyrolysis reactor. Hydrazine method is novel in the sense, say, the UV absorption edge of the white pigment grade wide band gap (~3.2eV) TiO₂ and ZnO shifted to the visible region turning into yellowish particles, indicating modification occurring the band structure. The absorption in the visible region makes these oxides visible light sensitive photocatalysis in degrading pollutants, especially the organic dyes which otherwise increase the chemical oxygen demand of the drinking water, enabling the process feasible not under the harsh energetic UV radiation regime. The electromagnetic radiations on irradiation produce electron-hole pairs Semiconductor + hν → e⁻ + h⁺ The electron-hole pairs thus produced form Reactive Oxygen Species, ROS, on the surface of the semiconductors, O₂(adsorbed)+e⁻ → O₂• - superoxide ion OH-(surface)+h⁺ →•OH - Hydroxyl radical The ROS attack the organic material and micro-organisms. Our antibacterial studies indicate the metal oxides control the Biological Oxygen Demand (BOD) of drinking water which had beyond the safe level normally found in the municipal supply. Metal oxides in the thin film form show overall enhanced properties and the films are reusable. The results of the photodegradation and antibactericidal studies are discussed. Gas sensing studies too have been done to find the versatility of the multifunctional metal oxides.

Keywords: hydrazine method, visible light sensitive, photo-degradation of dyes, water/airborne pollutant

Procedia PDF Downloads 142
273 A Deep Learning Approach to Real Time and Robust Vehicular Traffic Prediction

Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

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Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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272 Control Strategy for a Solar Vehicle Race

Authors: Francois Defay, Martim Calao, Jean Francois Dassieu, Laurent Salvetat

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Electrical vehicles are a solution for reducing the pollution using green energy. The shell Eco-Marathon provides rules in order to minimize the battery use for the race. The use of solar panel combined with efficient motor control and race strategy allow driving a 60kg vehicle with one pilot using only the solar energy in the best case. This paper presents a complete modelization of a solar vehicle used for the shell eco-marathon. This project called Helios is cooperation between non-graduated students, academic institutes, and industrials. The prototype is an ultra-energy-efficient vehicle based on one-meter square solar panel and an own-made brushless controller to optimize the electrical part. The vehicle is equipped with sensors and embedded system to provide all the data in real time in order to evaluate the best strategy for the course. A complete modelization with Matlab/Simulink is used to test the optimal strategy to increase the global endurance. Experimental results are presented to validate the different parts of the model: mechanical, aerodynamics, electrical, solar panel. The major finding of this study is to provide solutions to identify the model parameters (Rolling Resistance Coefficient, drag coefficient, motor torque coefficient, etc.) by means of experimental results combined with identification techniques. One time the coefficients are validated, the strategy to optimize the consumption and the average speed can be tested first in simulation before to be implanted for the race. The paper describes all the simulation and experimental parts and provides results in order to optimize the global efficiency of the vehicle. This works have been started four years ago and evolved many students for the experimental and theoretical parts and allow to increase the knowledge on electrical self-efficient vehicle.

Keywords: electrical vehicle, endurance, optimization, shell eco-marathon

Procedia PDF Downloads 240
271 Stroke Rehabilitation via Electroencephalogram Sensors and an Articulated Robot

Authors: Winncy Du, Jeremy Nguyen, Harpinder Dhillon, Reinardus Justin Halim, Clayton Haske, Trent Hughes, Marissa Ortiz, Rozy Saini

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Stroke often causes death or cerebro-vascular (CV) brain damage. Most patients with CV brain damage lost their motor control on their limbs. This paper focuses on developing a reliable, safe, and non-invasive EEG-based robot-assistant stroke rehabilitation system to help stroke survivors to rapidly restore their motor control functions for their limbs. An electroencephalogram (EEG) recording device (EPOC Headset) and was used to detect a patient’s brain activities. The EEG signals were then processed, classified, and interpreted to the motion intentions, and then converted to a series of robot motion commands. A six-axis articulated robot (AdeptSix 300) was employed to provide the intended motions based on these commends. To ensure the EEG device, the computer, and the robot can communicate to each other, an Arduino microcontroller is used to physically execute the programming codes to a series output pins’ status (HIGH or LOW). Then these “hardware” commends were sent to a 24 V relay to trigger the robot’s motion. A lookup table for various motion intensions and the associated EEG signal patterns were created (through training) and installed in the microcontroller. Thus, the motion intention can be direct determined by comparing the EEG patterns obtaibed from the patient with the look-up table’s EEG patterns; and the corresponding motion commends are sent to the robot to provide the intended motion without going through feature extraction and interpretation each time (a time-consuming process). For safety sake, an extender was designed and attached to the robot’s end effector to ensure the patient is beyond the robot’s workspace. The gripper is also designed to hold the patient’s limb. The test results of this rehabilitation system show that it can accurately interpret the patient’s motion intension and move the patient’s arm to the intended position.

Keywords: brain waves, EEG sensor, motion control, robot-assistant stroke rehabilitation

Procedia PDF Downloads 363
270 Seasonal Assessment of Snow Cover Dynamics Based on Aerospace Multispectral Data on Livingston Island, South Shetland Islands in Antarctica and on Svalbard in Arctic

Authors: Temenuzhka Spasova, Nadya Yanakieva

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Snow modulates the hydrological cycle and influences the functioning of ecosystems and is a significant resource for many populations whose water is harvested from cold regions. Snow observations are important for validating climate models. The accumulation and rapid melt of snow are two of the most dynamical seasonal environmental changes on the Earth’s surface. The actuality of this research is related to the modern tendencies of the remote sensing application in the solution of problems of different nature in the ecological monitoring of the environment. The subject of the study is the dynamic during the different seasons on Livingstone Island, South Shetland Islands in Antarctica and on Svalbard in Arctic. The objects were analyzed and mapped according to the Еuropean Space Agency data (ESA), acquired by sensors Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel 2 MSI and GIS. Results have been obtained for changes in snow coverage during the summer-winter transition and its dynamics in the two hemispheres. The data used is of high time-spatial resolution, which is an advantage when looking at the snow cover. The MSI images are with different spatial resolution at the Earth surface range. The changes of the environmental objects are shown with the SAR images and different processing approaches. The results clearly show that snow and snow melting can be best registered by using SAR data via hh- horizontal polarization. The effect of the researcher on aerospace data and technology enables us to obtain different digital models, structuring and analyzing results excluding the subjective factor. Because of the large extent of terrestrial snow coverage and the difficulties in obtaining ground measurements over cold regions, remote sensing and GIS represent an important tool for studying snow areas and properties from regional to global scales.

Keywords: climate changes, GIS, remote sensing, SAR images, snow coverage

Procedia PDF Downloads 197
269 Genetic Algorithm for In-Theatre Military Logistics Search-and-Delivery Path Planning

Authors: Jean Berger, Mohamed Barkaoui

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Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Keywords: search path planning, false alarm, search-and-delivery, entropy, genetic algorithm

Procedia PDF Downloads 343
268 Cooperative Agents to Prevent and Mitigate Distributed Denial of Service Attacks of Internet of Things Devices in Transportation Systems

Authors: Borhan Marzougui

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Road and Transport Authority (RTA) is moving ahead with the implementation of the leader’s vision in exploring all avenues that may bring better security and safety services to the community. Smart transport means using smart technologies such as IoT (Internet of Things). This technology continues to affirm its important role in the context of Information and Transportation Systems. In fact, IoT is a network of Internet-connected objects able to collect and exchange different data using embedded sensors. With the growth of IoT, Distributed Denial of Service (DDoS) attacks is also growing exponentially. DDoS attacks are the major and a real threat to various transportation services. Currently, the defense mechanisms are mainly passive in nature, and there is a need to develop a smart technique to handle them. In fact, new IoT devices are being used into a botnet for DDoS attackers to accumulate for attacker purposes. The aim of this paper is to provide a relevant understanding of dangerous types of DDoS attack related to IoT and to provide valuable guidance for the future IoT security method. Our methodology is based on development of the distributed algorithm. This algorithm manipulates dedicated intelligent and cooperative agents to prevent and to mitigate DDOS attacks. The proposed technique ensure a preventive action when a malicious packets start to be distributed through the connected node (Network of IoT devices). In addition, the devices such as camera and radio frequency identification (RFID) are connected within the secured network, and the data generated by it are analyzed in real time by intelligent and cooperative agents. The proposed security system is based on a multi-agent system. The obtained result has shown a significant reduction of a number of infected devices and enhanced the capabilities of different security dispositives.

Keywords: IoT, DDoS, attacks, botnet, security, agents

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267 Building Atmospheric Moisture Diagnostics: Environmental Monitoring and Data Collection

Authors: Paula Lopez-Arce, Hector Altamirano, Dimitrios Rovas, James Berry, Bryan Hindle, Steven Hodgson

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Efficient mould remediation and accurate moisture diagnostics leading to condensation and mould growth in dwellings are largely untapped. Number of factors are contributing to the rising trend of excessive moisture in homes mainly linked with modern living, increased levels of occupation and rising fuel costs, as well as making homes more energy efficient. Environmental monitoring by means of data collection though loggers sensors and survey forms has been performed in a range of buildings from different UK regions. Air and surface temperature and relative humidity values of residential areas affected by condensation and/or mould issues were recorded. Additional measurements were taken through different trials changing type, location, and position of loggers. In some instances, IR thermal images and ventilation rates have also been acquired. Results have been interpreted together with environmental key parameters by processing and connecting data from loggers and survey questionnaires, both in buildings with and without moisture issues. Monitoring exercises carried out during Winter and Spring time show the importance of developing and following accurate protocols for guidance to obtain consistent, repeatable and comparable results and to improve the performance of environmental monitoring. A model and a protocol are being developed to build a diagnostic tool with the goal of performing a simple but precise residential atmospheric moisture diagnostics to distinguish the cause entailing condensation and mould generation, i.e., ventilation, insulation or heating systems issue. This research shows the relevance of monitoring and processing environmental data to assign moisture risk levels and determine the origin of condensation or mould when dealing with a building atmospheric moisture excess.

Keywords: environmental monitoring, atmospheric moisture, protocols, mould

Procedia PDF Downloads 119
266 Effect of Spermidine on Physicochemical Properties of Protein Based Films

Authors: Mohammed Sabbah, Prospero Di Pierro, Raffaele Porta

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Protein-based edible films and coatings have attracted an increasing interest in recent years since they might be used to protect pharmaceuticals or improve the shelf life of different food products. Among them, several plant proteins represent an abundant, inexpensive and renewable raw source. These natural biopolymers are used as film forming agents, being able to form intermolecular linkages by various interactions. However, without the addition of a plasticizing agent, many biomaterials are brittle and, consequently, very difficult to be manipulated. Plasticizers are generally small and non-volatile organic additives used to increase film extensibility and reduce its crystallinity, brittleness and water vapor permeability. Plasticizers normally act by decreasing the intermolecular forces along the polymer chains, thus reducing the relative number of polymer-polymer contacts, producing a decrease in cohesion and tensile strength and thereby increasing film flexibility allowing its deformation without rupture. The most commonly studied plasticizers are polyols, like glycerol (GLY) and some mono or oligosaccharides. In particular, GLY not only increases film extensibility but also migrates inside the film network often causing the loss of desirable mechanical properties of the material. Therefore, replacing GLY with a different plasticizer might help to improve film characteristics allowing potential industrial applications. To improve film properties, it seemed of interest to test as plasticizers some cationic small molecules like polyamines (PAs). Putrescine, spermidine (SPD), and spermine are PAs widely distributed in nature and of particular interest for their biological activities that may have some beneficial health effects. Since PAs contains amino instead of hydroxyl functional groups, they are able to trigger ionic interactions with negatively charged proteins. Bitter vetch (Vicia ervilia; BV) is an ancient grain legume crop, originated in the Mediterranean region, which can be found today in many countries around the world. This annual Vicia genus shows several favorable features, being their seeds a cheap and abundant protein source. The main objectives of this study were to investigate the effect of different concentrations of SPD on the mechanical and permeability properties of films prepared with native or heat denatured BV proteins in the presence of different concentrations of SPD and/or GLY. Therefore, a BV seed protein concentrate (BVPC), containing about 77% proteins, was used to prepare film forming solutions (FFSs), whereas GLY and SPD were added as film plasticizers, either singly or in combination, at various concentrations. Since a primary plasticizer is generally defined as a molecule that when added to a material makes it softer, more flexible and easier to be processed, our findings lead to consider SPD as a possible primary plasticizer of protein-based films. In fact, the addition of millimolar concentrations of SPD to BVPC FFS allowed obtaining handleable biomaterials with improved properties. Moreover, SPD can be also considered as a secondary plasticizer, namely an 'extender', because of its ability even to enhance the plasticizing performance of GLY. In conclusion, our studies indicate that innovative edible protein-based films and coatings can be obtained by using PAs as new plasticizers.

Keywords: edible films, glycerol, plasticizers, polyamines, spermidine

Procedia PDF Downloads 175
265 Recycling of Spent Mo-Co Catalyst for the Recovery of Molybdenum Using Cyphos IL 104

Authors: Harshit Mahandra, Rashmi Singh, Bina Gupta

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Molybdenum is widely used in thermocouples, anticathode of X-ray tubes and in the production of alloys of steels. Molybdenum compounds are extensively used as a catalyst in petroleum-refining industries for hydrodesulphurization. Activity of the catalysts decreases gradually with time and are dumped as hazardous waste due to contamination with toxic materials during the process. These spent catalysts can serve as a secondary source for metal recovery and help to sort out environmental and economical issues. In present study, extraction and separation of molybdenum from a Mo-Co spent catalyst leach liquor containing 0.870 g L⁻¹ Mo, 0.341 g L⁻¹ Co, 0.422 ×10⁻¹ g L⁻¹ Fe and 0.508 g L⁻¹ Al in 3 mol L⁻¹ HCl has been investigated using solvent extraction technique. The extracted molybdenum has been finally recovered as molybdenum trioxide. Leaching conditions used were- 3 mol L⁻¹ HCl, 90°C temperature, solid to liquid ratio (w/v) of 1.25% and reaction time of 60 minutes. 96.45% molybdenum was leached under these conditions. For the extraction of molybdenum from leach liquor, Cyphos IL 104 [trihexyl(tetradecyl)phosphonium bis(2,4,4-trimethylpentyl)phosphinate] in toluene was used as an extractant. Around 91% molybdenum was extracted with 0.02 mol L⁻¹ Cyphos IL 104, and 75% of molybdenum was stripped from the loaded organic phase with 2 mol L⁻¹ HNO₃ at A/O=1/1. McCabe Thiele diagrams were drawn to determine the number of stages required for the extraction and stripping of molybdenum. According to McCabe Thiele plots, two stages are required for both extraction and stripping of molybdenum at A/O=1/1 which were also confirmed by countercurrent simulation studies. Around 98% molybdenum was extracted in two countercurrent extraction stages with no co-extraction of cobalt and aluminum. Iron was removed from the loaded organic phase by scrubbing with 0.01 mol L⁻¹ HCl. Quantitative recovery of molybdenum is achieved in three countercurrent stripping stages at A/O=1/1. Trioxide of molybdenum was obtained from strip solution and was characterized by XRD, FE-SEM and EDX techniques. Molybdenum trioxide due to its distinctive electrochromic, thermochromic and photochromic properties is used as a smart material for sensors, lubricants, and Li-ion batteries. Molybdenum trioxide finds application in various processes such as methanol oxidation, metathesis, propane oxidation and in hydrodesulphurization. It can also be used as a precursor for the synthesis of MoS₂ and MoSe₂.

Keywords: Cyphos IL 104, molybdenum, spent Mo-Co catalyst, recovery

Procedia PDF Downloads 181
264 Drought Detection and Water Stress Impact on Vegetation Cover Sustainability Using Radar Data

Authors: E. Farg, M. M. El-Sharkawy, M. S. Mostafa, S. M. Arafat

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Mapping water stress provides important baseline data for sustainable agriculture. Recent developments in the new Sentinel-1 data which allow the acquisition of high resolution images and varied polarization capabilities. This study was conducted to detect and quantify vegetation water content from canopy backscatter for extracting spatial information to encourage drought mapping activities throughout new reclaimed sandy soils in western Nile delta, Egypt. The performance of radar imagery in agriculture strongly depends on the sensor polarization capability. The dual mode capabilities of Sentinel-1 improve the ability to detect water stress and the backscatter from the structure components improves the identification and separation of vegetation types with various canopy structures from other features. The fieldwork data allowed identifying of water stress zones based on land cover structure; those classes were used for producing harmonious water stress map. The used analysis techniques and results show high capability of active sensors data in water stress mapping and monitoring especially when integrated with multi-spectral medium resolution images. Also sub soil drip irrigation systems cropped areas have lower drought and water stress than center pivot sprinkler irrigation systems. That refers to high level of evaporation from soil surface in initial growth stages. Results show that high relationship between vegetation indices such as Normalized Difference Vegetation Index NDVI the observed radar backscattering. In addition to observational evidence showed that the radar backscatter is highly sensitive to vegetation water stress, and essentially potential to monitor and detect vegetative cover drought.

Keywords: canopy backscatter, drought, polarization, NDVI

Procedia PDF Downloads 121
263 A Benchmark System for Testing Medium Voltage Direct Current (MVDC-CB) Robustness Utilizing Real Time Digital Simulation and Hardware-In-Loop Theory

Authors: Ali Kadivar, Kaveh Niayesh

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The integration of green energy resources is a major focus, and the role of Medium Voltage Direct Current (MVDC) systems is exponentially expanding. However, the protection of MVDC systems against DC faults is a challenge that can have consequences on reliable and safe grid operation. This challenge reveals the need for MVDC circuit breakers (MVDC CB), which are in infancies of their improvement. Therefore will be a lack of MVDC CBs standards, including thresholds for acceptable power losses and operation speed. To establish a baseline for comparison purposes, a benchmark system for testing future MVDC CBs is vital. The literatures just give the timing sequence of each switch and the emphasis is on the topology, without in-depth study on the control algorithm of DCCB, as the circuit breaker control system is not yet systematic. A digital testing benchmark is designed for the Proof-of-concept of simulation studies using software models. It can validate studies based on real-time digital simulators and Transient Network Analyzer (TNA) models. The proposed experimental setup utilizes data accusation from the accurate sensors installed on the tested MVDC CB and through general purpose input/outputs (GPIO) from the microcontroller and PC Prototype studies in the laboratory-based models utilizing Hardware-in-the-Loop (HIL) equipment connected to real-time digital simulators is achieved. The improved control algorithm of the circuit breaker can reduce the peak fault current and avoid arc resignation, helping the coordination of DCCB in relay protection. Moreover, several research gaps are identified regarding case studies and evaluation approaches.

Keywords: DC circuit breaker, hardware-in-the-loop, real time digital simulation, testing benchmark

Procedia PDF Downloads 54