Search results for: in situ sensing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1824

Search results for: in situ sensing

984 Nanocomposite Metal Material: Study of Antimicrobial and Catalytic Properties

Authors: Roman J. Jedrzejczyk, Damian K. Chlebda, Anna Dziedzicka, Rafal Wazny, Agnieszka Domka, Maciej Sitarz, Przemyslaw J. Jodlowski

Abstract:

The aim of this study was to obtain antimicrobial material based on thin zirconium dioxide coatings on structured reactors doped with metal nanoparticles using the sonochemical sol-gel method. As a result, dense, uniform zirconium dioxide films were obtained on the kanthal sheets which can be used as support materials in antimicrobial converters with sophisticated shapes. The material was characterised by physicochemical methods, such as AFM, SEM, EDX, XRF, XRD, XPS and in situ Raman and DRIFT spectroscopy. In terms of antimicrobial activity, the material was tested by ATP/AMP method using model microbes isolated from the real systems. The results show that the material can be potentially used in the market as a good candidate for active package and as active bulkheads of climatic systems. The mechanical tests showed that the developed method is an efficient way to obtain durable converters with high antimicrobial activity against fungi and bacteria.

Keywords: antimicrobial properties, kanthal steel, nanocomposite, zirconium oxide

Procedia PDF Downloads 190
983 Identification and Characterization of Novel Genes Involved in Quinone Synthesis in the Odoriferous Defensive Stink Glands of the Red Flour Beetle, Tribolium castaneum

Authors: B. Atika, S. Lehmann, E. Wimmer

Abstract:

The defense strategy is very common in the insect world. Defensive substances play a wide variety of functions for beetles, such as repellents, toxicants, insecticides, and antimicrobics. Beetles react to predators, invaders, and parasitic microbes with the release of toxic and repellent substances. Defensive substances are directed against a large array of potential target organisms or may function for boiling bombardment or as surfactants. Usually, Coleoptera biosynthesize and store their defensive compounds in a complex secretory organ, known as odoriferous defensive stink glands. The red flour beetle, Tribolium castaneum (Coleoptera: Tenebrionidae), uses these glands to produce antimicrobial p-benzoquinones and 1-alkenes. In the past, the morphology of stink gland has been studied in detail in tenebrionid beetles; however, very little is known about the genes that are involved in the production of gland secretion. In this study, we studied a subset of genes that are essential for the benzoquinone production in red flour beetle. In the first phase, we selected 74 potential candidate genes from a genome-wide RNA interference (RNAi) knockdown screen named 'iBeetle.' All these 74 candidate genes were functionally characterized by RNAi-mediated gene knockdown. Therefore, they were selected for a subsequent gas chromatography-mass spectrometry (GC-MS) analysis of secretion volatiles in respective RNAi knockdown glands. 33 of them were observed to alter the phenotype of stink gland. In the GC-MS analysis, 7 candidate genes were noted to display a strongly altered gland, in terms of secretion color and chemical composition, upon knockdown, showing their key role in the biosynthesis of gland secretion. Morphologically altered stink glands were found for odorant receptor and protein kinase superfamily. Subsequent GC-MS analysis of secretion volatiles revealed reduced benzoquinone levels in LIM domain, PDZ domain, PBP/GOBP family knockdowns and a complete lack of benzoquinones in the knockdown of sulfatase-modifying factor enzyme 1, sulfate transporter family. Based on stink gland transcriptome data, we analyzed the function of sulfatase-modifying factor enzyme 1 and sulfate transporter family via RNAi-mediated gene knockdowns, GC-MS, in situ hybridization, and enzymatic activity assays. Morphologically altered stink glands were noted in knockdown of both these genes. Furthermore, GC-MS analysis of secretion volatiles showed a complete lack of benzoquinones in the knockdown of these two genes. In situ hybridization showed that these two genes are expressed around the vesicle of certain subgroup of secretory stink gland cells. Enzymatic activity assays on stink gland tissue showed that these genes are involved in p-benzoquinone biosynthesis. These results suggest that sulfatase-modifying factor enzyme 1 and sulfate transporter family play a role specifically in benzoquinone biosynthesis in red flour beetles.

Keywords: Red Flour Beetle, defensive stink gland, benzoquinones, sulfate transporter, sulfatase-modifying factor enzyme 1

Procedia PDF Downloads 147
982 Modelling of Cavity Growth in Underground Coal Gasification

Authors: Preeti Aghalayam, Jay Shah

Abstract:

Underground coal gasification (UCG) is the in-situ gasification of unmineable coals to produce syngas. In UCG, gasifying agents are injected into the coal seam, and a reactive cavity is formed due to coal consumption. The cavity formed is typically hemispherical, and this report consists of the MATLAB model of the UCG cavity to predict the composition of the output gases. There are seven radial and two time-variant ODEs. A MATLAB solver (ode15s) is used to solve the radial ODEs from the above equations. Two for-loops are implemented in the model, i.e., one for time variations and another for radial variation. In the time loop, the radial odes are solved using the MATLAB solver. The radial loop is nested inside the time loop, and the density odes are numerically solved using the Euler method. The model is validated by comparing it with the literature results of laboratory-scale experiments. The model predicts the radial and time variation of the product gases inside the cavity.

Keywords: gasification agent, MATLAB model, syngas, underground coal gasification (UCG)

Procedia PDF Downloads 190
981 Investigating the Aerosol Load of Eastern Mediterranean Basin with Sentinel-5p Satellite

Authors: Deniz Yurtoğlu

Abstract:

Aerosols directly affect the radiative balance of the earth by absorbing and/or scattering the sun rays reaching the atmosphere and indirectly affect the balance by acting as a nucleus in cloud formation. The composition, physical, and chemical properties of aerosols vary depending on their sources and the time spent in the atmosphere. The Eastern Mediterranean Basin has a high aerosol load that is formed from different sources; such as anthropogenic activities, desert dust outbreaks, and the spray of sea salt; and the area is subjected to atmospheric transport from other locations on the earth. This region, which includes the deserts of Africa, the Middle East, and the Mediterranean sea, is one of the most affected areas by climate change due to its location and the chemistry of the atmosphere. This study aims to investigate the spatiotemporal deviation of aerosol load in the Eastern Mediterranean Basin between the years 2018-2022 with the help of a new pioneer satellite of ESA (European Space Agency), Sentinel-5P. The TROPOMI (The TROPOspheric Monitoring Instrument) traveling on this low-Earth orbiting satellite is a UV (Ultraviolet)-sensing spectrometer with a resolution of 5.5 km x 3.5 km, which can make measurements even in a cloud-covered atmosphere. By using Absorbing Aerosol Index data produced by this spectrometer and special scripts written in Python language that transforms this data into images, it was seen that the majority of the aerosol load in the Eastern Mediterranean Basin is sourced from desert dust and anthropogenic activities. After retrieving the daily data, which was separated from the NaN values, seasonal analyses match with the normal aerosol variations expected, which are high in warm seasons and lower in cold seasons. Monthly analyses showed that in four years, there was an increase in the amount of Absorbing Aerosol Index in spring and winter by 92.27% (2019-2021) and 39.81% (2019-2022), respectively. On the other hand, in the summer and autumn seasons, a decrease has been observed by 20.99% (2018-2021) and 0.94% (2018-2021), respectively. The overall variation of the mean absorbing aerosol index from TROPOMI between April 2018 to April 2022 reflects a decrease of 115.87% by annual mean from 0.228 to -0.036. However, when the data is analyzed by the annual mean values of the years which have the data from January to December, meaning from 2019 to 2021, there was an increase of 57.82% increase (0.108-0.171). This result can be interpreted as the effect of climate change on the aerosol load and also, more specifically, the effect of forest fires that happened in the summer months of 2021.

Keywords: aerosols, eastern mediterranean basin, sentinel-5p, tropomi, aerosol index, remote sensing

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980 Evaluation of Microstructure, Mechanical and Abrasive Wear Response of in situ TiC Particles Reinforced Zinc Aluminum Matrix Alloy Composites

Authors: Mohammad M. Khan, Pankaj Agarwal

Abstract:

The present investigation deals with the microstructures, mechanical and detailed wear characteristics of in situ TiC particles reinforced zinc aluminum-based metal matrix composites. The composites have been synthesized by liquid metallurgy route using vortex technique. The composite was found to be harder than the matrix alloy due to high hardness of the dispersoid particles therein. The former was also lower in ultimate tensile strength and ductility as compared to the matrix alloy. This could be explained to be due to the use of coarser size dispersoid and larger interparticle spacing. Reasonably uniform distribution of the dispersoid phase in the alloy matrix and good interfacial bonding between the dispersoid and matrix was observed. The composite exhibited predominantly brittle mode of fracture with microcracking in the dispersoid phase indicating effective easy transfer of load from matrix to the dispersoid particles. To study the wear behavior of the samples three different types of tests were performed namely: (i) sliding wear tests using a pin on disc machine under dry condition, (ii) high stress (two-body) abrasive wear tests using different combinations of abrasive media and specimen surfaces under the conditions of varying abrasive size, traversal distance and load, and (iii) low-stress (three-body) abrasion tests using a rubber wheel abrasion tester at various loads and traversal distances using different abrasive media. In sliding wear test, significantly lower wear rates were observed in the case of base alloy over that of the composites. This has been attributed to the poor room temperature strength as a result of increased microcracking tendency of the composite over the matrix alloy. Wear surfaces of the composite revealed the presence of fragmented dispersoid particles and microcracking whereas the wear surface of matrix alloy was observed to be smooth with shallow grooves. During high-stress abrasion, the presence of the reinforcement offered increased resistance to the destructive action of the abrasive particles. Microcracking tendency was also enhanced because of the reinforcement in the matrix. The negative effect of the microcracking tendency was predominant by the abrasion resistance of the dispersoid. As a result, the composite attained improved wear resistance than the matrix alloy. The wear rate increased with load and abrasive size due to a larger depth of cut made by the abrasive medium. The wear surfaces revealed fine grooves, and damaged reinforcement particles while subsurface regions revealed limited plastic deformation and microcracking and fracturing of the dispersoid phase. During low-stress abrasion, the composite experienced significantly less wear rate than the matrix alloy irrespective of the test conditions. This could be explained to be due to wear resistance offered by the hard dispersoid phase thereby protecting the softer matrix against the destructive action of the abrasive medium. Abraded surfaces of the composite showed protrusion of dispersoid phase. The subsurface regions of the composites exhibited decohesion of the dispersoid phase along with its microcracking and limited plastic deformation in the vicinity of the abraded surfaces.

Keywords: abrasive wear, liquid metallurgy, metal martix composite, SEM

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979 Synthesis, Characterization and Gas Sensing Applications of Perovskite CaZrO3 Nanoparticles

Authors: B. M. Patil

Abstract:

Calcium Zirconate (CaZrO3) has high protonic conductivities at elevated temperature in water or hydrogen atmosphere. Undoped calcium zirconate acts as a p-type semiconductor in air. In this paper, we reported synthesis of CaZrO3 nanoparticles via modified molecular precursor method. The precursor calcium zirconium oxalate (CZO) was synthesized by exchange reaction between freshly generated aqueous solution of sodium zirconyl oxalate and calcium acetate at room temperature. The controlled pyrolysis of CZO in air at 700°C for one hour resulted in the formation nanocrystalline CaZrO3 powder. CaZrO3 obtained by the present method was characterized by Simultaneous thermogravimetry and differential thermogravimetry (TG-DTA), X-ray diffraction (XRD), infra-red spectroscopy and transmission electron microscopy (TEM). The pellets of synthesized CaZrO3 fabricated, sintered at 1000°C for 5 hr and tested as sensors for NO2 and NH3 gases.

Keywords: CaZrO3, CZO, NO2, NH3

Procedia PDF Downloads 155
978 Learning Compression Techniques on Smart Phone

Authors: Farouk Lawan Gambo, Hamada Mohammad

Abstract:

Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques.

Keywords: data compression, learning preference, mobile learning, multimedia

Procedia PDF Downloads 433
977 Generalized Mean-Field Theory of Phase Unwrapping via Multiple Interferograms

Authors: Yohei Saika

Abstract:

On the basis of Bayesian inference using the maximizer of the posterior marginal estimate, we carry out phase unwrapping using multiple interferograms via generalized mean-field theory. Numerical calculations for a typical wave-front in remote sensing using the synthetic aperture radar interferometry, phase diagram in hyper-parameter space clarifies that the present method succeeds in phase unwrapping perfectly under the constraint of surface- consistency condition, if the interferograms are not corrupted by any noises. Also, we find that prior is useful for extending a phase in which phase unwrapping under the constraint of the surface-consistency condition. These results are quantitatively confirmed by the Monte Carlo simulation.

Keywords: Bayesian inference, generalized mean-field theory, phase unwrapping, multiple interferograms, statistical mechanics

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976 Mapping Forest Biodiversity Using Remote Sensing and Field Data in the National Park of Tlemcen (Algeria)

Authors: Bencherif Kada

Abstract:

In forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects, and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction and area of an object, etc.) and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants and bare soils. Texture attributes seem to provide no useful information while spatial attributes of shape, compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, biodiversity, shrublands

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975 Off-Grid Sparse Inverse Synthetic Aperture Imaging by Basis Shift Algorithm

Authors: Mengjun Yang, Zhulin Zong, Jie Gao

Abstract:

In this paper, a new and robust algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework. Traditional CS based methods have to assume that unknown scatters exactly lie on the pre-divided grids; otherwise, their reconstruction performance dropped significantly. In this processing algorithm, several basis shifts are utilized to achieve the same effect as grid refinement does. The detailed implementation of the basis shift algorithm is presented in this paper. From the simulation we can see that using the basis shift algorithm, imaging precision can be improved. The effectiveness and feasibility of the proposed method are investigated by the simulation results.

Keywords: ISAR imaging, sparse reconstruction, off-grid, basis shift

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974 Sclerobiont Assemblages on Macro-Invertebrates from the Cenomanian Strata of Djebel Bouarif (Aurès Range, Algeria)

Authors: Salmi-laouar Sihem, Kara Ahmed Imad

Abstract:

The ichnological study of the Djebel BouarifCenomaniandeposits(Northern Aurès Range, Algeria) revealed relatively abundant and diverse sclerobiont communities that are preserved in corals, bivalves, and gastropods ; all are described herein. Fossil traces are dominated by exceptionally preserved Gastrochaenolitesoften with tracemakers (bivalves), which are preserved in situ, Entobia, and Maeandropolydora. Other borings are rare and are represented by a single specimen of Rogerella, Nihilichnus, and Spirolites. Amongsclerozoans, encrustingjuvenile oysters, and non-oyster bivalves (Pseudolimea?granulata) are the mostabundant groups. Otherepibionts, such as gastropods and polychaetes (Glomerulaserpentina), are lesscommon; dwarfgastropods were located on a single oyster Costagyraolisiponensis, whereas Glomerula specimens were clustered on the lower and upper surfaces of coral Aspidiscuscristatus. Gastrochaenoliteswith original tracemakers and all the epibionts studied herein have not been described from the Djebel BouarifCenomaniandeposits to date. The rare occurrences of Spirolites and Nihilichnus are reported from Algeria for the first time.

Keywords: bioerosion, sclerobionts, upper creataceous, southern tethys, atlasic domain

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973 Learn through AR (Augmented Reality)

Authors: Prajakta Musale, Bhargav Parlikar, Sakshi Parkhi, Anshu Parihar, Aryan Parikh, Diksha Parasharam, Parth Jadhav

Abstract:

AR technology is basically a development of VR technology that harnesses the power of computers to be able to read the surroundings and create projections of digital models in the real world for the purpose of visualization, demonstration, and education. It has been applied to education, fields of prototyping in product design, development of medical models, battle strategy in the military and many other fields. Our Engineering Design and Innovation (EDAI) project focuses on the usage of augmented reality, visual mapping, and 3d-visualization along with animation and text boxes to help students in fields of education get a rough idea of the concepts such as flow and mechanical movements that may be hard to visualize at first glance.

Keywords: spatial mapping, ARKit, depth sensing, real-time rendering

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972 Innovating Electronics Engineering for Smart Materials Marketing

Authors: Muhammad Awais Kiani

Abstract:

The field of electronics engineering plays a vital role in the marketing of smart materials. Smart materials are innovative, adaptive materials that can respond to external stimuli, such as temperature, light, or pressure, in order to enhance performance or functionality. As the demand for smart materials continues to grow, it is crucial to understand how electronics engineering can contribute to their marketing strategies. This abstract presents an overview of the role of electronics engineering in the marketing of smart materials. It explores the various ways in which electronics engineering enables the development and integration of smart features within materials, enhancing their marketability. Firstly, electronics engineering facilitates the design and development of sensing and actuating systems for smart materials. These systems enable the detection and response to external stimuli, providing valuable data and feedback to users. By integrating sensors and actuators into materials, their functionality and performance can be significantly enhanced, making them more appealing to potential customers. Secondly, electronics engineering enables the creation of smart materials with wireless communication capabilities. By incorporating wireless technologies such as Bluetooth or Wi-Fi, smart materials can seamlessly interact with other devices, providing real-time data and enabling remote control and monitoring. This connectivity enhances the marketability of smart materials by offering convenience, efficiency, and improved user experience. Furthermore, electronics engineering plays a crucial role in power management for smart materials. Implementing energy-efficient systems and power harvesting techniques ensures that smart materials can operate autonomously for extended periods. This aspect not only increases their market appeal but also reduces the need for constant maintenance or battery replacements, thus enhancing customer satisfaction. Lastly, electronics engineering contributes to the marketing of smart materials through innovative user interfaces and intuitive control mechanisms. By designing user-friendly interfaces and integrating advanced control systems, smart materials become more accessible to a broader range of users. Clear and intuitive controls enhance the user experience and encourage wider adoption of smart materials in various industries. In conclusion, electronics engineering significantly influences the marketing of smart materials by enabling the design of sensing and actuating systems, wireless connectivity, efficient power management, and user-friendly interfaces. The integration of electronics engineering principles enhances the functionality, performance, and marketability of smart materials, making them more adaptable to the growing demand for innovative and connected materials in diverse industries.

Keywords: electronics engineering, smart materials, marketing, power management

Procedia PDF Downloads 51
971 Carbon Sequestration in Spatio-Temporal Vegetation Dynamics

Authors: Nothando Gwazani, K. R. Marembo

Abstract:

An increase in the atmospheric concentration of carbon dioxide (CO₂) from fossil fuel and land use change necessitates identification of strategies for mitigating threats associated with global warming. Oceans are insufficient to offset the accelerating rate of carbon emission. However, the challenges of oceans as a source of reducing carbon footprint can be effectively overcome by the storage of carbon in terrestrial carbon sinks. The gases with special optical properties that are responsible for climate warming include carbon dioxide (CO₂), water vapors, methane (CH₄), nitrous oxide (N₂O), nitrogen oxides (NOₓ), stratospheric ozone (O₃), carbon monoxide (CO) and chlorofluorocarbons (CFC’s). Amongst these, CO₂ plays a crucial role as it contributes to 50% of the total greenhouse effect and has been linked to climate change. Because plants act as carbon sinks, interest in terrestrial carbon sequestration has increased in an effort to explore opportunities for climate change mitigation. Removal of carbon from the atmosphere is a topical issue that addresses one important aspect of an overall strategy for carbon management namely to help mitigate the increasing emissions of CO₂. Thus, terrestrial ecosystems have gained importance for their potential to sequester carbon and reduce carbon sink in oceans, which have a substantial impact on the ocean species. Field data and electromagnetic spectrum bands were analyzed using ArcGIS 10.2, QGIS 2.8 and ERDAS IMAGINE 2015 to examine the vegetation distribution. Satellite remote sensing data coupled with Normalized Difference Vegetation Index (NDVI) was employed to assess future potential changes in vegetation distributions in Eastern Cape Province of South Africa. The observed 5-year interval analysis examines the amount of carbon absorbed using vegetation distribution. In 2015, the numerical results showed low vegetation distribution, therefore increased the acidity of the oceans and gravely affected fish species and corals. The outcomes suggest that the study area could be effectively utilized for carbon sequestration so as to mitigate ocean acidification. The vegetation changes measured through this investigation suggest an environmental shift and reduced vegetation carbon sink, and that threatens biodiversity and ecosystem. In order to sustain the amount of carbon in the terrestrial ecosystems, the identified ecological factors should be enhanced through the application of good land and forest management practices. This will increase the carbon stock of terrestrial ecosystems thereby reducing direct loss to the atmosphere.

Keywords: remote sensing, vegetation dynamics, carbon sequestration, terrestrial carbon sink

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970 Heat Vulnerability Index (HVI) Mapping in Extreme Heat Days Coupled with Air Pollution Using Principal Component Analysis (PCA) Technique: A Case Study of Amiens, France

Authors: Aiman Mazhar Qureshi, Ahmed Rachid

Abstract:

Extreme heat events are emerging human environmental health concerns in dense urban areas due to anthropogenic activities. High spatial and temporal resolution heat maps are important for urban heat adaptation and mitigation, helping to indicate hotspots that are required for the attention of city planners. The Heat Vulnerability Index (HVI) is the important approach used by decision-makers and urban planners to identify heat-vulnerable communities and areas that require heat stress mitigation strategies. Amiens is a medium-sized French city, where the average temperature has been increasing since the year 2000 by +1°C. Extreme heat events are recorded in the month of July for the last three consecutive years, 2018, 2019 and 2020. Poor air quality, especially ground-level ozone, has been observed mainly during the same hot period. In this study, we evaluated the HVI in Amiens during extreme heat days recorded last three years (2018,2019,2020). The Principal Component Analysis (PCA) technique is used for fine-scale vulnerability mapping. The main data we considered for this study to develop the HVI model are (a) socio-economic and demographic data; (b) Air pollution; (c) Land use and cover; (d) Elderly heat-illness; (e) socially vulnerable; (f) Remote sensing data (Land surface temperature (LST), mean elevation, NDVI and NDWI). The output maps identified the hot zones through comprehensive GIS analysis. The resultant map shows that high HVI exists in three typical areas: (1) where the population density is quite high and the vegetation cover is small (2) the artificial surfaces (built-in areas) (3) industrial zones that release thermal energy and ground-level ozone while those with low HVI are located in natural landscapes such as rivers and grasslands. The study also illustrates the system theory with a causal diagram after data analysis where anthropogenic activities and air pollution appear in correspondence with extreme heat events in the city. Our suggested index can be a useful tool to guide urban planners and municipalities, decision-makers and public health professionals in targeting areas at high risk of extreme heat and air pollution for future interventions adaptation and mitigation measures.

Keywords: heat vulnerability index, heat mapping, heat health-illness, remote sensing, urban heat mitigation

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969 Adaptive Environmental Control System Strategy for Cabin Air Quality in Commercial Aircrafts

Authors: Paolo Grasso, Sai Kalyan Yelike, Federico Benzi, Mathieu Le Cam

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The cabin air quality (CAQ) in commercial aircraft is of prime interest, especially in the context of the COVID-19 pandemic. Current Environmental Control Systems (ECS) rely on a prescribed fresh airflow per passenger to dilute contaminants. An adaptive ECS strategy is proposed, leveraging air sensing and filtration technologies to ensure a better CAQ. This paper investigates the CAQ level achieved in commercial aircraft’s cabin during various flight scenarios. The modeling and simulation analysis is performed in a Modelica-based environment describing the dynamic behavior of the system. The model includes the following three main systems: cabin, recirculation loop and air-conditioning pack. The cabin model evaluates the thermo-hygrometric conditions and the air quality in the cabin depending on the number of passengers and crew members, the outdoor conditions and the conditions of the air supplied to the cabin. The recirculation loop includes models of the recirculation fan, ordinary and novel filtration technology, mixing chamber and outflow valve. The air-conditioning pack includes models of heat exchangers and turbomachinery needed to condition the hot pressurized air bled from the engine, as well as selected contaminants originated from the outside or bled from the engine. Different ventilation control strategies are modeled and simulated. Currently, a limited understanding of contaminant concentrations in the cabin and the lack of standardized and systematic methods to collect and record data constitute a challenge in establishing a causal relationship between CAQ and passengers' comfort. As a result, contaminants are neither measured nor filtered during flight, and the current sub-optimal way to avoid their accumulation is their dilution with the fresh air flow. However, the use of a prescribed amount of fresh air comes with a cost, making the ECS the most energy-demanding non-propulsive system within an aircraft. In such a context, this study shows that an ECS based on a reduced and adaptive fresh air flow, and relying on air sensing and filtration technologies, provides promising results in terms of CAQ control. The comparative simulation results demonstrate that the proposed adaptive ECS brings substantial improvements to the CAQ in terms of both controlling the asymptotic values of the concentration of the contaminant and in mitigating hazardous scenarios, such as fume events. Original architectures allowing for adaptive control of the inlet air flow rate based on monitored CAQ will change the requirements for filtration systems and redefine the ECS operation.

Keywords: cabin air quality, commercial aircraft, environmental control system, ventilation

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968 Optimization of Metal Pile Foundations for Solar Power Stations Using Cone Penetration Test Data

Authors: Adrian Priceputu, Elena Mihaela Stan

Abstract:

Our research addresses a critical challenge in renewable energy: improving efficiency and reducing the costs associated with the installation of ground-mounted photovoltaic (PV) panels. The most commonly used foundation solution is metal piles - with various sections adapted to soil conditions and the structural model of the panels. However, direct foundation systems are also sometimes used, especially in brownfield sites. Although metal micropiles are generally the first design option, understanding and predicting their bearing capacity, particularly under varied soil conditions, remains an open research topic. CPT Method and Current Challenges: Metal piles are favored for PV panel foundations due to their adaptability, but existing design methods rely heavily on costly and time-consuming in situ tests. The Cone Penetration Test (CPT) offers a more efficient alternative by providing valuable data on soil strength, stratification, and other key characteristics with reduced resources. During the test, a cone-shaped probe is pushed into the ground at a constant rate. Sensors within the probe measure the resistance of the soil to penetration, divided into cone penetration resistance and shaft friction resistance. Despite some existing CPT-based design approaches for metal piles, these methods are often cumbersome and difficult to apply. They vary significantly due to soil type and foundation method, and traditional approaches like the LCPC method involve complex calculations and extensive empirical data. The method was developed by testing 197 piles on a wide range of ground conditions, but the tested piles were very different from the ones used for PV pile foundations, making the method less accurate and practical for steel micropiles. Project Objectives and Methodology: Our research aims to develop a calculation method for metal micropile foundations using CPT data, simplifying the complex relationships involved. The goal is to estimate the pullout bearing capacity of piles without additional laboratory tests, streamlining the design process. To achieve this, a case study was selected which will serve for the development of an 80ha solar power station. Four testing locations were chosen spread throughout the site. At each location, two types of steel profiles (H160 and C100) were embedded into the ground at various depths (1.5m and 2.0m). The piles were tested for pullout capacity under natural and inundated soil conditions. CPT tests conducted nearby served as calibration points. The results served for the development of a preliminary equation for estimating pullout capacity. Future Work: The next phase involves validating and refining the proposed equation on additional sites by comparing CPT-based forecasts with in situ pullout tests. This validation will enhance the accuracy and reliability of the method, potentially transforming the foundation design process for PV panels.

Keywords: cone penetration test, foundation optimization, solar power stations, steel pile foundations

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967 Non-Contact Digital Music Instrument Using Light Sensing Technology

Authors: Aishwarya Ravichandra, Kirtana Kirtivasan, Adithi Mahesh, Ashwini S.Savanth

Abstract:

A Non-Contact Digital Music System has been conceptualized and implemented to create a new era of digital music. This system replaces the strings of a traditional stringed instrument with laser beams to avoid bruising of the user’s hand. The system consists of seven laser modules, detector modules and distance sensors that form the basic hardware blocks of this instrument. Arduino ATmega2560 microcontroller is used as the primary interface between the hardware and the software. MIDI (Musical Instrument Digital Interface) is used as the protocol to establish communication between the instrument and the virtual synthesizer software.

Keywords: Arduino, detector, laser, MIDI, note on, note off, pitch bend, Sharp IR distance sensor

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966 Phenomenon of Raveling Distress on the Flexible Pavements: An Overview

Authors: Syed Ali Shahbaz Shah

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In the last few years, Bituminous Asphaltic roads are becoming popular day by day in the world. Plenty of research has been carried out to identify many advantages like safety, environmental effects, and comfort. Some other benefits are minimal noise and skid resistance enhancement. Besides the benefits of asphaltic roads, the permeable structure of the road also causes some distress, and raveling is one of the crucial defects. The main reason behind this distress is the failure of adhesion between bitumen mortar, specifically due to excessive load from heavy traffic. The main focus of this study is to identify the root cause and propose both the long-term and the short-term solutions of raveling on a specific road section depicting the overall road situation from the bridge of Kahuta road towards the intersection of the Islamabad express highway. The methodology adopted for this purpose is visual inspections in-situ. It was noted that there were chunks of debris on the road surface, which indicates that the asphalt binder is aged the most probably. Further laboratory testing would confirm that either asphalt binder is aged or inadequate compaction was adept during cold weather paving.

Keywords: asphaltic roads, asphalt binder, distress, raveling

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965 Use of GIS and Remote Sensing for Calculating the Installable Photovoltaic and Thermal Power on All the Roofs of the City of Aix-en-Provence, France

Authors: Sofiane Bourchak, Sébastien Bridier

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The objective of this study is to show how to calculate and map solar energy’s quantity (instantaneous and accumulated global solar radiation during the year) available on roofs in the city Aix-en-Provence which has a population of 140,000 inhabitants. The result is a geographic information system (GIS) layer, which represents hourly and monthly the production of solar energy on roofs throughout the year. Solar energy professionals can use it to optimize implementations and to size energy production systems. The results are presented as a set of maps, tables and histograms in order to determine the most effective costs in Aix-en-Provence in terms of photovoltaic power (electricity) and thermal power (hot water).

Keywords: geographic information system, photovoltaic, thermal, solar potential, solar radiation

Procedia PDF Downloads 420
964 Towards Dynamic Estimation of Residential Building Energy Consumption in Germany: Leveraging Machine Learning and Public Data from England and Wales

Authors: Philipp Sommer, Amgad Agoub

Abstract:

The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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963 Numerical Modelling of a Vacuum Consolidation Project in Vietnam

Authors: Nguyen Trong Nghia, Nguyen Huu Uy Vu, Dang Huu Phuoc, Sanjay Kumar Shukla, Le Gia Lam, Nguyen Van Cuong

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This paper introduces a matching scheme for selection of soil/drain properties in analytical solution and numerical modelling (axisymmetric and plane strain conditions) of a ground improvement project by using Prefabricated Vertical Drains (PVD) in combination with vacuum and surcharge preloading. In-situ monitoring data from a case history of a road construction project in Vietnam was adopted in the back-analysis. Analytical solution and axisymmetric analysis can approximate well the field data meanwhile the horizontal permeability need to be adjusted in plane strain scenario to achieve good agreement. In addition, the influence zone of the ground treatment was examined. The residual settlement was investigated to justify the long-term settlement in compliance with the design code. Moreover, the degree of consolidation of non-PVD sub-layers was also studied by means of two different approaches.

Keywords: numerical modelling, prefabricated vertical drains, vacuum consolidation, soft soil

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962 Role of Artificial Intelligence in Nano Proteomics

Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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961 Indicator-Immobilized, Cellulose Based Optical Sensing Membrane for the Detection of Heavy Metal Ions

Authors: Nisha Dhariwal, Anupama Sharma

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The synthesis of cellulose nanofibrils quaternized with 3‐chloro‐2‐hydroxypropyltrimethylammonium chloride (CHPTAC) in NaOH/urea aqueous solution has been reported. Xylenol Orange (XO) has been used as an indicator for selective detection of Sn (II) ions, by its immobilization on quaternized cellulose membrane. The effects of pH, reagent concentration and reaction time on the immobilization of XO have also been studied. The linear response, limit of detection, and interference of other metal ions have also been studied and no significant interference has been observed. The optical chemical sensor displayed good durability and short response time with negligible leaching of the reagent.

Keywords: cellulose, chemical sensor, heavy metal ions, indicator immobilization

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960 A Spectroscopic Study by Photoluminescence of Erbium in Gallium Nitride

Authors: A. Melouah, M. Diaf

Abstract:

The III-N nitride semiconductors appear to be excellent host materials, in particular, GaN epilayers doped with Erbium ions have shown a highly reduced thermal quenching of the Er luminescence intensity from cryogenic to elevated temperatures. The remarkable stability may be due to the large energy band gap of the material. Two methods are used for doping the Gallium nitride films with Erbium ions; ion implantation in the wafers obtained by (CVDOM) and in-situ incorporation during epitaxial growth of the layers by (MBE). Photoluminescence (PL) spectroscopy has been the main optical technique used to characterize the emission of Er-doped III-N semiconductor materials. This technique involves optical excitation of Er3+ ions and measurement of the spectrum of the light emission as a function of energy (wavelength). Excitation at above band gap energy leads to the creation of Electron-Hole pairs. Some of this pairs may transfer their energy to the Er3+ ions, exciting the 4f-electrons and resulting in optical emission. This corresponds to an indirect excitation of the Er3+ ions by electron-hole pairs. The direct excitation by the optical pumping of the radiation can be obtained.

Keywords: photoluminescence, Erbium, GaN, semiconductor materials

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959 The Effect That the Data Assimilation of Qinghai-Tibet Plateau Has on a Precipitation Forecast

Authors: Ruixia Liu

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Qinghai-Tibet Plateau has an important influence on the precipitation of its lower reaches. Data from remote sensing has itself advantage and numerical prediction model which assimilates RS data will be better than other. We got the assimilation data of MHS and terrestrial and sounding from GSI, and introduced the result into WRF, then got the result of RH and precipitation forecast. We found that assimilating MHS and terrestrial and sounding made the forecast on precipitation, area and the center of the precipitation more accurate by comparing the result of 1h,6h,12h, and 24h. Analyzing the difference of the initial field, we knew that the data assimilating about Qinghai-Tibet Plateau influence its lower reaches forecast by affecting on initial temperature and RH.

Keywords: Qinghai-Tibet Plateau, precipitation, data assimilation, GSI

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958 Estimation of Soil Nutrient Content Using Google Earth and Pleiades Satellite Imagery for Small Farms

Authors: Lucas Barbosa Da Silva, Jun Okamoto Jr.

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Precision Agriculture has long being benefited from crop fields’ aerial imagery. This important tool has allowed identifying patterns in crop fields, generating useful information to the production management. Reflectance intensity data in different ranges from the electromagnetic spectrum may indicate presence or absence of nutrients in the soil of an area. Different relations between the different light bands may generate even more detailed information. The knowledge of the nutrients content in the soil or in the crop during its growth is a valuable asset to the farmer that seeks to optimize its yield. However, small farmers in Brazil often lack the resources to access this kind information, and, even when they do, it is not presented in a comprehensive and/or objective way. So, the challenges of implementing this technology ranges from the sampling of the imagery, using aerial platforms, building of a mosaic with the images to cover the entire crop field, extracting the reflectance information from it and analyzing its relationship with the parameters of interest, to the display of the results in a manner that the farmer may take the necessary decisions more objectively. In this work, it’s proposed an analysis of soil nutrient contents based on image processing of satellite imagery and comparing its outtakes with commercial laboratory’s chemical analysis. Also, sources of satellite imagery are compared, to assess the feasibility of using Google Earth data in this application, and the impacts of doing so, versus the application of imagery from satellites like Landsat-8 and Pleiades. Furthermore, an algorithm for building mosaics is implemented using Google Earth imagery and finally, the possibility of using unmanned aerial vehicles is analyzed. From the data obtained, some soil parameters are estimated, namely, the content of Potassium, Phosphorus, Boron, Manganese, among others. The suitability of Google Earth Imagery for this application is verified within a reasonable margin, when compared to Pleiades Satellite imagery and to the current commercial model. It is also verified that the mosaic construction method has little or no influence on the estimation results. Variability maps are created over the covered area and the impacts of the image resolution and sample time frame are discussed, allowing easy assessments of the results. The final results show that easy and cheaper remote sensing and analysis methods are possible and feasible alternatives for the small farmer, with little access to technological and/or financial resources, to make more accurate decisions about soil nutrient management.

Keywords: remote sensing, precision agriculture, mosaic, soil, nutrient content, satellite imagery, aerial imagery

Procedia PDF Downloads 163
957 BaFe12O19/Polythiophene Nanocomposite as Electrochemical Supercapacitor Electrode

Authors: H. Farokhi, A. Bahadoran

Abstract:

This paper is focused on the absorbance and magnetic properties of a novel nanocomposite based on conducting polymer, carbon black and barium hexaferrite in epoxy resin on the E-glass fibre substrate. The highly conductive nanocomposite was provided by in-situ polymerization of aniline in the presence of carbon black (C) and barium hexaferrite (BaFe12O19) as electromagnetic absorbance material. The structure, morphology, and magnetic properties of samples were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM). SEM images showed the uniformly coated PAni on the surface of carbon black and barium hexaferrite. XRD peaks also verified the presence of carbon black and barium hexaferrite in the nanocomposite. The microwave characteristics determined from the magnetic and dielectric properties of the elastomeric composites obtained from scattering data by fitting the samples in a waveguide, where measured in the frequency in X-band frequency range, the range of 8 to 12 GHz. The reflection losses were evaluated to be less than −5dB over the whole X-band frequency (8–12 GHz) for the thickness of 1.4mm.

Keywords: conductive polymer, magnetic materials, capacitance, electrochemical cell

Procedia PDF Downloads 240
956 Assessment of Chemical and Physical Properties of Surface Water Resources in Flood Affected Area

Authors: Siti Hajar Ya’acob, Nor Sayzwani Sukri, Farah Khaliz Kedri, Rozidaini Mohd Ghazi, Nik Raihan Nik Yusoff, Aweng A/L Eh Rak

Abstract:

Flood event that occurred in mid-December 2014 in East Coast of Peninsular Malaysia has driven attention from the public nationwide. Apart from loss and damage of properties and belongings, the massive flood event has introduced environmental disturbances on surface water resources in such flood affected area. A study has been conducted to measure the physical and chemical composition of Galas River and Pergau River prior to identification the flood impact towards environmental deterioration in surrounding area. Samples that have been collected were analyzed in-situ using YSI portable instrument and also in the laboratory for acid digestion and heavy metals analysis using Atomic Absorption Spectroscopy (AAS). Results showed that range of temperature (0C), DO (mg/L), Ec (µs/cm), TDS (mg/L), turbidity (NTU), pH, and salinity were 25.05-26.65, 1.51-5.85, 0.032-0.054, 0.022-0.035, 23.2-76.4, 3.46-7.31, and 0.01-0.02 respectively. The results from this study could be used as a primary database to evaluate the status of water quality of the respective river after the massive flood.

Keywords: flood, river, heavy metals, AAS

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955 In-Situ Redevelopment in Urban India: Two Case Studies from Delhi and Mumbai

Authors: Ashok Kumar, Anjali Sharma

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As cities grow and expand spatially, redevelopment in urban India is beginning to emerge as a new mode of urban expansion sweeping low-income informal settlements. This paper examines the extent and nature of expanding urban frontier before examining implications for the families living in these settlements. Displacement of these families may appear to be an obvious consequence. However, we have conducted ethnographic studies over the past several months in a Delhi slum named Kathputli Colony, Delhi. In depth analysis of the study for this slum appears to present a variegated set of consequences for the residents of informal settlements including loss of livelihoods, dismantling of family ties, and general anxiety arising out of uncertainty about resettlement. Apart from Delhi case study, we also compare and contrast another redevelopment case from Mumbai located at Bhendi Bazar. These examples from the two mega cities of Mumbai and Delhi are analysed to understand and explore expanding urban frontiers and their consequences for informing future public policy.

Keywords: informal settlements, policy, redevelopment, urban

Procedia PDF Downloads 313