Search results for: subsurface sensing

Authors: Rasaq Bello, Grace Akintola Sunday, Yemi Sikiru Onifade

Abstract:

Groundwater is required for the continuity of life and sustainability of the ecosystem. Hence, this research was purposed to assess groundwater quality for domestic use in Kaltungo Local Government Area, Gombe State. The work was also aimed at determining the thickness and resistivity of the topsoil, areas suitable for borehole construction, quality and potentials of groundwater in the study area. The study area extends from latitude N10015’38” - E11008’01” and longitude N10019’29” - E11013’05”. The data was acquired using the Vertical Electrical Sounding (VES) method and processed using IP12win software. Twenty (20) Vertical Electrical Soundings were carried out with a maximum current electrode separation (AB) of 150m. The VES curves generated from the data reveal that all the VES points have five to six subsurface layers. The first layer has a resistivity value of 7.5 to 364.1 Ωm and a thickness ranging from 0.8 to 7.4m, and the second layer has a resistivity value of 1.8 to 600.3 Ωm thickness ranging from 2.6 to 31.4m, the third layer has resistivity value of 23.3 to 564.4 Ωm thickness ranging from 10.3 to 77.8m, the fourth layer has resistivity value of 19.7 to 640.2 Ωm thickness ranging from 8.2m to 120.0m, the fifth layer has resistivity value of 27 to 234 Ωm thickness ranging from 8.2 to 53.7m and the six-layer is the layer that extended beyond the probing depth. The VES curves generated from the data revealed KQHA curve type for VES 1, HKQQ curve for VES 4, HKQ curve for VES 5, KHA curve for VES 11, QQHK curve for VES 12, HAA curve for VES 6 and VES 19, HAKH curve for VES 7, VES 8, VES 10 and VES 18, HKH curve for VES 2, VES 3, VES 9, VES 13, VES 14, VES 15, VES 16, VES 17 and VES 20. Values of the Coefficient of Anisotropy, Reflection Coefficient, and Resistivity Contrast obtained from the Dar-Zarrouk parameters indicated good water prospects for all the VES points in this study, with VES points 4, 9 and 18 having the highest prospects for groundwater exploration.

Keywords: formation parameters, groundwater, resistivity, resistivity contrast, vertical electrical sounding

Procedia PDF Downloads 52

Authors: K. Graniczkowska, N. Beloglazova, S. De Saeger

Abstract:

The threat of synthetic drugs is one of the most significant current drug problems worldwide. The use of drugs of abuse has increased dramatically during the past three decades. Among others, Amphetamine-Type Stimulants (ATS) are globally the second most widely used drugs after cannabis, exceeding the use of cocaine and heroin. ATS are potent central nervous system (CNS) stimulants, capable of inducing euphoric static similar to cocaine. Recreational use of ATS is widespread, even though warnings of irreversible damage of the CNS were reported. ATS pose a big problem and their production contributes to the pollution of the environment by discharging big volumes of liquid waste to sewage system. Therefore, there is a demand to develop robust and sensitive sensors that can detect ATS and their intermediates in environmental water samples. A rapid and simple test is required. Analysis of environmental water samples (which sometimes can be a harsh environment) using antibody-based tests cannot be applied. Therefore, molecular imprinted polymers (MIPs), which are known as synthetic antibodies, have been chosen for that approach. MIPs are characterized with a high mechanical and thermal stability, show chemical resistance in a broad pH range and various organic or aqueous solvents. These properties make them the preferred type of receptors for application in the harsh conditions imposed by environmental samples. To the best of our knowledge, there are no existing MIPs-based sensors toward amphetamine and its intermediates. Also not many commercial MIPs for this application are available. Therefore, the aim of this study was to compare different techniques to obtain MIPs with high specificity towards ATS and characterize them for following use in a sensing unit. MIPs against amphetamine and its intermediates were synthesized using a few different techniques, such as electro-, thermo- and UV-initiated polymerization. Different monomers, cross linkers and initiators, in various ratios, were tested to obtain the best sensitivity and polymers properties. Subsequently, specificity and selectivity were compared with commercially available MIPs against amphetamine. Different linkers, such as lipoic acid, 3-mercaptopioponic acid and tyramine were examined, in combination with several immobilization techniques, to select the best procedure for attaching particles on sensor surface. Performed experiments allowed choosing an optimal method for the intended sensor application. Stability of MIPs in extreme conditions, such as highly acidic or basic was determined. Obtained results led to the conclusion about MIPs based sensor applicability in sewage system testing.

Keywords: amphetamine type stimulants, environment, molecular imprinted polymers, MIPs, sensor

Procedia PDF Downloads 250

Authors: Kayode Festus Oyedele, Sunday Oladele, Adaora Chibundu Nduka

Abstract:

The subsurface of a proposed site for building development in Mowe, Nigeria, using Standard Penetration Test (SPT) and Cone Penetrometer Test (CPT) supplemented with Horizontal Electrical Profiling (HEP) was investigated with the aim of evaluating the suitability of the strata for foundation materials. Four SPT and CPT were implemented using 10 tonnes hammer. HEP utilizing Wenner array were performed with inter-electrode spacing of 10 – 60 m along four traverses coincident with each of the SPT and CPT. The HEP data were processed using DIPRO software and textural filtering of the resulting resistivity sections was implemented to enable delineation of hidden layers. Sandy lateritic clay, silty lateritic clay, clay, clayey sand and sand horizons were delineated. The SPT “N” value defined very soft to soft sandy lateritic (<4), stiff silty lateritic clay (7 – 12), very stiff silty clay (12 - 15), clayey sand (15- 20) and sand (27 – 37). Sandy lateritic clay (5-40 kg/cm2) and silty lateritic clay (25 - 65 kg/cm2) were defined from the CPT response. Sandy lateritic clay (220-750 Ωm), clay (< 50 Ωm) and sand (415-5359 Ωm) were delineated from the resistivity sections with two thin layers of silty lateritic clay and clayey sand defined in the texturally filtered resistivity sections. This study concluded that the presence of incompetent thick clayey materials (18 m) beneath the study area makes it unsuitable for shallow foundation. Deep foundation involving piling through the clayey layers to the competent sand at 20 m depth was recommended.

Keywords: cone penetrometer, foundation, lithologic texture, resistivity section, standard penetration test

Procedia PDF Downloads 265

Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

Abstract:

One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

Procedia PDF Downloads 424

Authors: Yu Zhang, Mingxue Lang, Li Dong

Abstract:

The hundreds of years of slow succession of living environment in rural area is a crucial carrier of China’s long history of culture and national wisdom. In recent years, the space evolution of traditional rural settlements has been promoted by the intervention of tourism development, among which the public architecture and outdoor activity areas together served as the major places for villagers, and tourists’ social activities are an important characterization for settlement spatial evolution. Traditional public space upgrade and layout study of new public space can effectively promote the tourism industry development of traditional rural settlements. This article takes Qi County, one China Traditional Culture Village as the exemplification and uses the technology of Remote Sensing (RS), Geographic Information System (GIS) and Space Syntax, studies the evolution features of public space of tourism-oriented traditional rural settlements in four steps. First, acquire the 2003 and 2016 image data of Qi County, using the remote sensing application EDRAS8.6. Second, vectorize the basic maps of Qi County including its land use map with the application of ArcGIS 9.3 meanwhile, associating with architectural and site information concluded from field research. Third, analyze the accessibility and connectivity of the inner space of settlements using space syntax; run cross-correlation with the public space data of 2003 and 2016. Finally, summarize the evolution law of the public space of settlements; study the upgrade pattern of traditional public space and location plan for new public space. Major findings of this paper including: first, location layout of traditional public space has a larger association with the calculation results of space syntax and further confirmed the objective value of space syntax in expressing the space and social relations. Second, the intervention of tourism development generates remarkable impact on public space location of tradition rural settlements. Third, traditional public space produces the symbols of both strengthening and decline and forms a diversified upgrade pattern for the purpose of meeting the different tourism functional needs. Finally, space syntax provides an objective basis for location plan of new public space that meets the needs of tourism service. Tourism development has a significant impact on the evolution of public space of traditional rural settlements. Two types of public space, architecture, and site are both with changes seen from the perspective of quantity, location, dimension and function after the intervention of tourism development. Function upgrade of traditional public space and scientific layout of new public space are two important ways in achieving the goal of sustainable development of tourism-oriented traditional rural settlements.

Keywords: public space evolution, Qi county, space syntax, tourism oriented, traditional rural settlements

Procedia PDF Downloads 341

Authors: Vivek Kumar, Alexander M. Zaitsev

Abstract:

A study on chemical sensing properties of carbon nanofilms on diamond for developing all-carbon chemical sensors is presented. The films were obtained by high temperature graphitization of diamond followed by successive plasma etchings. Characterization of the films was done by Raman spectroscopy, atomic force microscopy, and electrical measurements. Fast and selective response to common organic vapors as seen as sensitivity of electrical conductance was observed. The phenomenological description of the chemical sensitivity is proposed as a function of the surface and bulk material properties of the films.

Keywords: chemical sensor, carbon nanofilm, graphitization of diamond, plasma etching, Raman spectroscopy, atomic force microscopy

Procedia PDF Downloads 446

Authors: Lahcen Daoudi, Fatima Zahra Omdi, Abldelali Gourfi

Abstract:

In Morocco, as in most Mediterranean countries, water scarcity is a common situation because of low and unevenly distributed rainfall. The expansions of irrigated lands, as well as the growth of urban and industrial areas and tourist resorts, contribute to an increase of water demand. Therefore in the 1960s Morocco embarked on an ambitious program to increase the number of dams to boost water retention capacity. However, the decrease in the capacity of these reservoirs caused by sedimentation is a major problem; it is estimated at 75 million m3/year. Dams and reservoirs became unusable for their intended purposes due to sedimentation in large rivers that result from soil erosion. Soil erosion presents an important driving force in the process affecting the landscape. It has become one of the most serious environmental problems that raised much interest throughout the world. Monitoring soil erosion risk is an important part of soil conservation practices. The estimation of soil loss risk is the first step for a successful control of water erosion. The aim of this study is to estimate the soil loss risk and its spatial distribution in the different fields of Morocco and to prioritize areas for soil conservation interventions. The approach followed is the Revised Universal Soil Loss Equation (RUSLE) using remote sensing and GIS, which is the most popular empirically based model used globally for erosion prediction and control. This model has been tested in many agricultural watersheds in the world, particularly for large-scale basins due to the simplicity of the model formulation and easy availability of the dataset. The spatial distribution of the annual soil loss was elaborated by the combination of several factors: rainfall erosivity, soil erodability, topography, and land cover. The average annual soil loss estimated in several basins watershed of Morocco varies from 0 to 50t/ha/year. Watersheds characterized by high-erosion-vulnerability are located in the North (Rif Mountains) and more particularly in the Central part of Morocco (High Atlas Mountains). This variation of vulnerability is highly correlated to slope variation which indicates that the topography factor is the main agent of soil erosion within these basin catchments. These results could be helpful for the planning of natural resources management and for implementing sustainable long-term management strategies which are necessary for soil conservation and for increasing over the projected economic life of the dam implemented.

Keywords: soil loss, RUSLE, GIS-remote sensing, watershed, Morocco

Procedia PDF Downloads 461

Authors: P. Selva, B. Lorraina, J. Alexis, A. Seror, A. Longuet, C. Mary, F. Denard

Abstract:

Over the past four decades, the fatigue behavior of nickel-based alloys has been widely studied. However, in recent years, significant advances in the fabrication process leading to grain size reduction have been made in order to improve fatigue properties of aircraft turbine discs. Indeed, a change in particle size affects the initiation mode of fatigue cracks as well as the fatigue life of the material. The present study aims to investigate the fatigue behavior of a newly developed nickel-based superalloy under biaxial-planar loading. Low Cycle Fatigue (LCF) tests are performed at different stress ratios so as to study the influence of the multiaxial stress state on the fatigue life of the material. Full-field displacement and strain measurements as well as crack initiation detection are obtained using Digital Image Correlation (DIC) techniques. The aim of this presentation is first to provide an in-depth description of both the experimental set-up and protocol: the multiaxial testing machine, the specific design of the cruciform specimen and performances of the DIC code are introduced. Second, results for sixteen specimens related to different load ratios are presented. Crack detection, strain amplitude and number of cycles to crack initiation vs. triaxial stress ratio for each loading case are given. Third, from fractographic investigations by scanning electron microscopy it is found that the mechanism of fatigue crack initiation does not depend on the triaxial stress ratio and that most fatigue cracks initiate from subsurface carbides.

Keywords: cruciform specimen, multiaxial fatigue, nickel-based superalloy

Procedia PDF Downloads 295

Authors: Muhamad Iqbal Mubarak Faharul Azman, Azim Hilmy Mohd Yusof, Nur Azwin Ismail, Noer El Hidayah Ismail

Abstract:

Landslides and rock falls are the examples of environmental and engineering problems in Malaysia. There are various methods that can be applied for the environmental and engineering problems but geophysical methods are seldom applied as the main investigation technique. This paper aims to study the slope stability by using 2-D resistivity method at Jalan Tun Sardon and Sungai Batu, Pulau Pinang. These areas are considered as highly potential for unstable slope in Penang Island based on recent cases of rockfall and landslide reported especially during raining season. At both study areas, resistivity values greater than 5000 ohm-m are detected and considered as the fresh granite. The weathered granite is indicated by resistivity value of 750-1500 ohm-m with depth of < 14 meters at Sungai Batu area while at Jalan Tun Sardon area, the weathered granite with resistivity values of 750-2000 ohm-m is found at depth < 14 meter at distance 0-90 meter but at distance of 95-150 meter, the weathered granite is found at depth < 26 meter. Saturated zone is detected only at Sungai Batu with resistivity value <250 ohm-m at distance 100-120 meter. A fracture is detected at distance about 70 meter at Jalan Tun Sardon area. Unstable slope is expected to be affected by the weathered granite that dominates the subsurface of the study areas along with triggering factor such as heavy rainfall.

Keywords: 2-D resistivity, environmental issue, landslide, slope stability

Procedia PDF Downloads 228

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

Procedia PDF Downloads 67

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 167

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 447

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

Procedia PDF Downloads 479

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

Procedia PDF Downloads 30

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

Procedia PDF Downloads 265

Authors: Samim Khair Mohammad, Takeshi Tsuji, Chanmaly Chhun

Abstract:

The Afghan Tajik (foreland) basin, located in the depression zone between mountain axes, is under compression and deformation during the collision of India with the Eurasian plate. The southern part of the Afghan Tajik basin in the Northern part of Afghanistan has not been well studied and explored, but considered for the significant potential for oil and gas resources. The Afghan Tajik basin depositional environments (< 8km) resulted from mixing terrestrial and marine systems, which has potential prospects of Jurrasic (deep) and Tertiary (shallow) petroleum systems. We used 2D regional seismic profiles with a total length of 674.8 km (or over an area of 2500 km²) in the southern part of the basin. To characterize hydrocarbon systems and structures in this study area, we applied advanced seismic attributes such as spectral decomposition (10 - 60Hz) based on time-frequency analysis with continuous wavelet transform. The spectral decomposition results yield the (averaging 20 - 30Hz group) spectral amplitude anomaly. Based on this anomaly result, seismic, and structural interpretation, the potential hydrocarbon accumulations were inferred around the main thrust folds in the tertiary (Paleogene+Neogene) petroleum systems, which appeared to be accumulated around the central study area. Furthermore, it seems that hydrocarbons dominantly migrated along the main thrusts and then concentrated around anticline fold systems which could be sealed by mudstone/carbonate rocks.

Keywords: The Afghan Tajik basin, seismic lines, spectral decomposition, thrust folds, hydrocarbon reservoirs

Procedia PDF Downloads 112

Authors: Fathi Ali Swaid

Abstract:

Soil salinization is one of the most hazardous phenomenons accelerating the land degradation processes. It either occurs naturally or is human-induced. High levels of soil salinity negatively affect crop growth and productivity leading land degradation ultimately. Thus, it is important to monitor and map soil salinity at an early stage to enact effective soil reclamation program that helps lessen or prevent future increase in soil salinity. Geophysical method has outperformed the traditional method for assessing soil salinity offering more informative and professional rapid assessment techniques for monitoring and mapping soil salinity. Soil sampling, EM38 and 2D conductivity imaging have been evaluated for their ability to delineate and map the level of salinity variations at Second Ponds Creek. The three methods have shown that the subsoil in the study area is saline. Salt variations were successfully observed under either method. However, EM38 reading and 2D inversion data show a clear spatial structure comparing to EC1:5 of soil samples in spite of that all soil samples, EM38 and 2D imaging were collected from the same location. Because EM38 readings and 2D imaging data are a weighted average of electrical soil conductance, it is more representative of soil properties than the soil samples method. The mapping of subsurface soil at the study area has been successful and the resistivity imaging has proven to be an advantage. The soil salinity analysis (EC1:5) correspond well to the true resistivity bringing together a good result of soil salinity. Soil salinity clearly indicated by previous investigation EM38 have been confirmed by the interpretation of the true resistivity at study area.

Keywords: 2D conductivity imaging, EM38 readings, soil salinization, true resistivity, urban salinity

Procedia PDF Downloads 376

Authors: Mourad Bédir, Sami Khomsi, Hakim Gabtni, Hajer Azaiez, Ramzi Gharsalli, Riadh Chebbi

Abstract:

Eastern Tunisia is a semi-arid area; located in the northern Africa plate; southern Mediterranean side. It is facing water scarcity, overexploitation, and decreasing of water quality of phreatic water table. Water supply and storage will not respond to the demographic and economic growth and demand. In addition, only 5 109 m3 of rainwater from 35 109 m3 per year renewable rain water supply can be retained and remobilized. To remediate this water deficiency, researches had been focused to near new subsurface deep aquifers resources. Among them, Upper Miocene sandstone deposits of Béglia, Saouaf, and Somaa Formations. These sandstones are known for their proven Hydrogeologic and hydrocarbon reservoir characteristics in the Tunisian margin. They represent semi-confined to confined aquifers. This work is based on new integrated approaches of seismic stratigraphy, seismic tectonics, and hydrogeology, to highlight and characterize these reservoirs levels for aquifer exploitation in semi-arid area. As a result, five to six third order sequence deposits had been highlighted. They are composed of multi-layered extended sandstones reservoirs; separated by shales packages. These reservoir deposits represent lowstand and highstand system tracts of these sequences, which represent lowstand and highstand system tracts of these sequences. They constitute important strategic water resources volumes for the region.

Keywords: Tunisia, Hydrogeology, sandstones, basin, seismic, aquifers, modeling

Procedia PDF Downloads 177

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

Procedia PDF Downloads 63

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 59

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

Procedia PDF Downloads 151

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

Procedia PDF Downloads 148

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

Abstract:

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

Procedia PDF Downloads 100

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

Procedia PDF Downloads 407

Authors: Sofiane Bourchak, Sébastien Bridier

Abstract:

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 436

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

Procedia PDF Downloads 57

Authors: Mehrnaz Mostafavi

Abstract:

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

Procedia PDF Downloads 95

Authors: Nisha Dhariwal, Anupama Sharma

Abstract:

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

Procedia PDF Downloads 301

Authors: Ruixia Liu

Abstract:

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

Procedia PDF Downloads 234

Authors: Lucas Barbosa Da Silva, Jun Okamoto Jr.

Abstract:

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 175