Search results for: landslide susceptibility mapping
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1689

Search results for: landslide susceptibility mapping

1209 Social Vulnerability Mapping in New York City to Discuss Current Adaptation Practice

Authors: Diana Reckien

Abstract:

Vulnerability assessments are increasingly used to support policy-making in complex environments, like urban areas. Usually, vulnerability studies include the construction of aggregate (sub-) indices and the subsequent mapping of indices across an area of interest. Vulnerability studies show a couple of advantages: they are great communication tools, can inform a wider general debate about environmental issues, and can help allocating and efficiently targeting scarce resources for adaptation policy and planning. However, they also have a number of challenges: Vulnerability assessments are constructed on the basis of a wide range of methodologies and there is no single framework or methodology that has proven to serve best in certain environments, indicators vary highly according to the spatial scale used, different variables and metrics produce different results, and aggregate or composite vulnerability indicators that are mapped easily distort or bias the picture of vulnerability as they hide the underlying causes of vulnerability and level out conflicting reasons of vulnerability in space. So, there is urgent need to further develop the methodology of vulnerability studies towards a common framework, which is one reason of the paper. We introduce a social vulnerability approach, which is compared with other approaches of bio-physical or sectoral vulnerability studies relatively developed in terms of a common methodology for index construction, guidelines for mapping, assessment of sensitivity, and verification of variables. Two approaches are commonly pursued in the literature. The first one is an additive approach, in which all potentially influential variables are weighted according to their importance for the vulnerability aspect, and then added to form a composite vulnerability index per unit area. The second approach includes variable reduction, mostly Principal Component Analysis (PCA) that reduces the number of variables that are interrelated into a smaller number of less correlating components, which are also added to form a composite index. We test these two approaches of constructing indices on the area of New York City as well as two different metrics of variables used as input and compare the outcome for the 5 boroughs of NY. Our analysis yields that the mapping exercise yields particularly different results in the outer regions and parts of the boroughs, such as Outer Queens and Staten Island. However, some of these parts, particularly the coastal areas receive the highest attention in the current adaptation policy. We imply from this that the current adaptation policy and practice in NY might need to be discussed, as these outer urban areas show relatively low social vulnerability as compared with the more central parts, i.e. the high dense areas of Manhattan, Central Brooklyn, Central Queens and the Southern Bronx. The inner urban parts receive lesser adaptation attention, but bear a higher risk of damage in case of hazards in those areas. This is conceivable, e.g., during large heatwaves, which would more affect more the inner and poorer parts of the city as compared with the outer urban areas. In light of the recent planning practice of NY one needs to question and discuss who in NY makes adaptation policy for whom, but the presented analyses points towards an under representation of the needs of the socially vulnerable population, such as the poor, the elderly, and ethnic minorities, in the current adaptation practice in New York City.

Keywords: vulnerability mapping, social vulnerability, additive approach, Principal Component Analysis (PCA), New York City, United States, adaptation, social sensitivity

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1208 Rainfall Estimation Using Himawari-8 Meteorological Satellite Imagery in Central Taiwan

Authors: Chiang Wei, Hui-Chung Yeh, Yen-Chang Chen

Abstract:

The objective of this study is to estimate the rainfall using the new generation Himawari-8 meteorological satellite with multi-band, high-bit format, and high spatiotemporal resolution, ground rainfall data at the Chen-Yu-Lan watershed of Joushuei River Basin (443.6 square kilometers) in Central Taiwan. Accurate and fine-scale rainfall information is essential for rugged terrain with high local variation for early warning of flood, landslide, and debris flow disasters. 10-minute and 2 km pixel-based rainfall of Typhoon Megi of 2016 and meiyu on June 1-4 of 2017 were tested to demonstrate the new generation Himawari-8 meteorological satellite can capture rainfall variation in the rugged mountainous area both at fine-scale and watershed scale. The results provide the valuable rainfall information for early warning of future disasters.

Keywords: estimation, Himawari-8, rainfall, satellite imagery

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1207 ARGO: An Open Designed Unmanned Surface Vehicle Mapping Autonomous Platform

Authors: Papakonstantinou Apostolos, Argyrios Moustakas, Panagiotis Zervos, Dimitrios Stefanakis, Manolis Tsapakis, Nektarios Spyridakis, Mary Paspaliari, Christos Kontos, Antonis Legakis, Sarantis Houzouris, Konstantinos Topouzelis

Abstract:

For years unmanned and remotely operated robots have been used as tools in industry research and education. The rapid development and miniaturization of sensors that can be attached to remotely operated vehicles in recent years allowed industry leaders and researchers to utilize them as an affordable means for data acquisition in air, land, and sea. Despite the recent developments in the ground and unmanned airborne vehicles, a small number of Unmanned Surface Vehicle (USV) platforms are targeted for mapping and monitoring environmental parameters for research and industry purposes. The ARGO project is developed an open-design USV equipped with multi-level control hardware architecture and state-of-the-art sensors and payloads for the autonomous monitoring of environmental parameters in large sea areas. The proposed USV is a catamaran-type USV controlled over a wireless radio link (5G) for long-range mapping capabilities and control for a ground-based control station. The ARGO USV has a propulsion control using 2x fully redundant electric trolling motors with active vector thrust for omnidirectional movement, navigation with opensource autopilot system with high accuracy GNSS device, and communication with the 2.4Ghz digital link able to provide 20km of Line of Sight (Los) range distance. The 3-meter dual hull design and composite structure offer well above 80kg of usable payload capacity. Furthermore, sun and friction energy harvesting methods provide clean energy to the propulsion system. The design is highly modular, where each component or payload can be replaced or modified according to the desired task (industrial or research). The system can be equipped with Multiparameter Sonde, measuring up to 20 water parameters simultaneously, such as conductivity, salinity, turbidity, dissolved oxygen, etc. Furthermore, a high-end multibeam echo sounder can be installed in a specific boat datum for shallow water high-resolution seabed mapping. The system is designed to operate in the Aegean Sea. The developed USV is planned to be utilized as a system for autonomous data acquisition, mapping, and monitoring bathymetry and various environmental parameters. ARGO USV can operate in small or large ports with high maneuverability and endurance to map large geographical extends at sea. The system presents state of the art solutions in the following areas i) the on-board/real-time data processing/analysis capabilities, ii) the energy-independent and environmentally friendly platform entirely made using the latest aeronautical and marine materials, iii) the integration of advanced technology sensors, all in one system (photogrammetric and radiometric footprint, as well as its connection with various environmental and inertial sensors) and iv) the information management application. The ARGO web-based application enables the system to depict the results of the data acquisition process in near real-time. All the recorded environmental variables and indices are presented, allowing users to remotely access all the raw and processed information using the implemented web-based GIS application.

Keywords: monitor marine environment, unmanned surface vehicle, mapping bythometry, sea environmental monitoring

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1206 Prevalence, Antimicrobial Susceptibility Pattern and Public Health Significance for Staphylococcus aureus of Isolated From Raw Red Meat at Butchery and Abattoir House in Mekelle, Northern Ethiopia

Authors: Haftay Abraha Tadesse

Abstract:

Background: Staphylococcus is a genus of worldwide distributed bacteria correlated to several infectious of different sites in human and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. Objective: The objective of this study was to determine the isolates, antimicrobial susceptibility patterns and public health significance for Staphylococcus aureus in raw meat from butchery and abattoir houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from April to October 2019. Sociodemographic data and public health significance were collected using predesigned questionnaire. The raw meat samples were collected aseptically in the butchery and abattoir houses and transported using ice box to Mekelle University, College of Veterinary Sciences for isolating and identification of Staphylococcus aureus. Antimicrobial susceptibility tests were determined by disc diffusion method. Data obtained were cleaned and entered in to STATA 22.0 and logistic regression model with odds ratio were calculated to assess the association of risk factors with bacterial contamination. P-value < 0.05 was considered as statistically significant. Results: In present study, 88 out of 250 (35.2%) were found to be contamination with Staphylococcus aureus. Among the raw meat specimens to be positivity rate of Staphylococcus aureus were 37.6% (n=47) and (32.8% (n=41), butchery and abattoir houses, respectively. Among the associated risk factories not using gloves reduces risk was found to (AOR=0.222; 95% CI: 0.104-0.473), Strict Separation b/n clean & dirty (AOR= 1.37; 95% CI: 0.66-2.86) and poor habit of hand washing (AOR=1.08; 95%CI: 0.35-3.35) were found to be statistically significant and ha ve associated with Staphylococcus aureus contamination. All isolates thirty sevevn of Staphyloco ccus aureus were checked displayed (100%) sensitive to doxycycline, trimethoprim, gentamicin, sulphamethoxazole, amikacin, CN, Co trimoxazole and nitrofurantoi. whereas the showed resistance of cefotaxime (100%), ampicillin (87.5%), Penicillin (75%), B (75%), and nalidixic acid (50%) from butchery houses. On the other hand, all isolates of Staphylococcus aur eu isolate 100% (n= 10) showed sensitive chloramphenicol, gentamicin and nitrofurantoin whereas the showed 100% resistance of Penicillin, B, AMX, ceftriaxone, ampicillin and cefotaxime from abattoirs houses. The overall multi drug resistance pattern for Staphylococcus aureus were 90% and 100% of butchery and abattoirs houses, respectively. Conclusion: 35.3% Staphylococcus aureus isolated were recovered from the raw meat samples collected from the butchery and abattoirs houses. More has to be done in the developed of hand washing behavior, and availability of safe water in the butchery houses to reduce burden of bacterial contamination. The results of the present finding highlight the need to implement protective measures against the levels of food contamination and alternative drug options. The development of antimicrobial resistance is nearly always as a result of repeated therapeutic and/or indiscriminate use of them. Regular antimicrobial sensitivity testing helps to select effective antibiotics and to reduce the problems of drug resistance development towards commonly used antibiotics. Key words: abattoir houses, antimicrobial resistance, butchery houses, Ethiopia,

Keywords: abattoir houses, antimicrobial resistance, butchery houses, Ethiopia, staphylococcus aureuse, MDR

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1205 The Application of Mapping, Practicing, Using Strategy with Instructional Materials Based on the School Curriculum toward the English Achievement of Indonesian EFL Students

Authors: Eny Syatriana

Abstract:

English proficiency of Indonesian secondary school students is below standard. The low proficiency may come from poor teaching materials that do not meet the students’ need. The main objective for English teachers is to improve the English proficiency of the students. The purpose of this study is to explore the application Mapping, Practicing, Using (MPU) strategy with Instructional Materials Based on the School Curriculum toward the English achievement of Indonesian EFL Students. This paper is part my dissertation entitles 'Designing instructional materials for secondary school students based on the school curriculum' consisting of need analysis, design, development, implementation, and evaluation; this paper discusses need analysis and creates a model of creating instructional materials through deep discussion among teachers of secondary schools. The subject consisted of six English teachers and students of three classes at three different secondary schools in Makassar, South Sulawesi, Indonesia. Pretest and posttest design were administered to see the effectiveness of the MPU strategy. Questionnaires were administered to see the teachers and students’ perception toward the instructional materials. The result indicates that the MPU strategy is effective in improving the English achievement; instructional materials with different strategies improve the English achievement of the students. Both teachers and students argue that the presented instructional materials are effective to be used in the teaching and learning process to increase the English proficiency of the students.

Keywords: proficiency, development, English for secondary school students, instructional materials

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1204 Enhancing Students’ Academic Engagement in Mathematics through a “Concept+Language Mapping” Approach

Authors: Jodie Lee, Lorena Chan, Esther Tong

Abstract:

Hong Kong students face a unique learning environment. Starting from the 2010/2011 school year, The Education Bureau (EDB) of the Government of the Hong Kong Special Administrative Region implemented the fine-tuned Medium of Instruction (MOI) arrangements for secondary schools. Since then, secondary schools in Hong Kong have been given the flexibility to decide the most appropriate MOI arrangements for their schools and under the new academic structure for senior secondary education, particularly on the compulsory part of the mathematics curriculum. In 2019, Hong Kong Diploma of Secondary Education Examination (HKDSE), over 40% of school day candidates attempted the Mathematics Compulsory Part examination in the Chinese version while the rest took the English version. Moreover, only 14.38% of candidates sat for one of the extended Mathematics modules. This results in a serious of intricate issues to students’ learning in post-secondary education programmes. It is worth to note that when students further pursue to an higher education in Hong Kong or even oversea, they may facing substantial difficulties in transiting learning from learning mathematics in their mother tongue in Chinese-medium instruction (CMI) secondary schools to an English-medium learning environment. Some students understood the mathematics concepts were found to fail to fulfill the course requirements at college or university due to their learning experience in secondary study at CMI. They are particularly weak in comprehending the mathematics questions when they are doing their assessment or attempting the test/examination. A government funded project was conducted with the aims of providing integrated learning context and language support to students with a lower level of numeracy and/or with CMI learning experience. By introducing this “integrated concept + language mapping approach”, students can cope with the learning challenges in the compulsory English-medium mathematics and statistics subjects in their tertiary education. Ultimately, in the hope that students can enhance their mathematical ability, analytical skills, and numerical sense for their lifelong learning. The “Concept + Language Mapping “(CLM) approach was adopted and tried out in the bridging courses for students with a lower level of numeracy and/or with CMI learning experiences. At the beginning of each class, a pre-test was conducted, and class time was then devoted to introducing the concepts by CLM approach. For each concept, the key thematic items and their different semantic relations are presented using graphics and animations via the CLM approach. At the end of each class, a post-test was conducted. Quantitative data analysis was performed to study the effect on students’ learning via the CLM approach. Stakeholders' feedbacks were collected to estimate the effectiveness of the CLM approach in facilitating both content and language learning. The results based on both students’ and lecturers’ feedback indicated positive outcomes on adopting the CLM approach to enhance the mathematical ability and analytical skills of CMI students.

Keywords: mathematics, Concept+Language Mapping, level of numeracy, medium of instruction

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1203 Landslide Hazard Assessment Using Physically Based Mathematical Models in Agricultural Terraces at Douro Valley in North of Portugal

Authors: C. Bateira, J. Fernandes, A. Costa

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The Douro Demarked Region (DDR) is a production Porto wine region. On the NE of Portugal, the strong incision of the Douro valley developed very steep slopes, organized with agriculture terraces, have experienced an intense and deep transformation in order to implement the mechanization of the work. The old terrace system, based on stone vertical wall support structure, replaced by terraces with earth embankments experienced a huge terrace instability. This terrace instability has important economic and financial consequences on the agriculture enterprises. This paper presents and develops cartographic tools to access the embankment instability and identify the area prone to instability. The priority on this evaluation is related to the use of physically based mathematical models and develop a validation process based on an inventory of the past embankment instability. We used the shallow landslide stability model (SHALSTAB) based on physical parameters such us cohesion (c’), friction angle(ф), hydraulic conductivity, soil depth, soil specific weight (ϱ), slope angle (α) and contributing areas by Multiple Flow Direction Method (MFD). A terraced area can be analysed by this models unless we have very detailed information representative of the terrain morphology. The slope angle and the contributing areas depend on that. We can achieve that propose using digital elevation models (DEM) with great resolution (pixel with 40cm side), resulting from a set of photographs taken by a flight at 100m high with pixel resolution of 12cm. The slope angle results from this DEM. In the other hand, the MFD contributing area models the internal flow and is an important element to define the spatial variation of the soil saturation. That internal flow is based on the DEM. That is supported by the statement that the interflow, although not coincident with the superficial flow, have important similitude with it. Electrical resistivity monitoring values which related with the MFD contributing areas build from a DEM of 1m resolution and revealed a consistent correlation. That analysis, performed on the area, showed a good correlation with R2 of 0,72 and 0,76 at 1,5m and 2m depth, respectively. Considering that, a DEM with 1m resolution was the base to model the real internal flow. Thus, we assumed that the contributing area of 1m resolution modelled by MFD is representative of the internal flow of the area. In order to solve this problem we used a set of generalized DEMs to build the contributing areas used in the SHALSTAB. Those DEMs, with several resolutions (1m and 5m), were built from a set of photographs with 50cm resolution taken by a flight with 5km high. Using this maps combination, we modelled several final maps of terrace instability and performed a validation process with the contingency matrix. The best final instability map resembles the slope map from a DEM of 40cm resolution and a MFD map from a DEM of 1m resolution with a True Positive Rate (TPR) of 0,97, a False Positive Rate of 0,47, Accuracy (ACC) of 0,53, Precision (PVC) of 0,0004 and a TPR/FPR ratio of 2,06.

Keywords: agricultural terraces, cartography, landslides, SHALSTAB, vineyards

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1202 Comparison of Seismic Retrofitting Methods for Existing Foundations in Seismological Active Regions

Authors: Peyman Amini Motlagh, Ali Pak

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Seismic retrofitting of important structures is essential in seismological active zones. The importance is doubled when it comes to some buildings like schools, hospitals, bridges etc. because they are required to continue their serviceability even after a major earthquake. Generally, seismic retrofitting codes have paid little attention to retrofitting of foundations due to its construction complexity. In this paper different methods for seismic retrofitting of tall buildings’ foundations will be discussed and evaluated. Foundations are considered in three different categories. First, foundations those are in danger of liquefaction of their underlying soil. Second, foundations located on slopes in seismological active regions. Third, foundations designed according to former design codes and may show structural defects under earthquake loads. After describing different methods used in different countries for retrofitting of the existing foundations in seismological active regions, comprehensive comparison between these methods with regard to the above mentioned categories is carried out. This paper gives some guidelines to choose the best method for seismic retrofitting of tall buildings’ foundations in retrofitting projects.

Keywords: existing foundation, landslide, liquefaction, seismic retrofitting

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1201 Development and Validation of Thermal Stability in Complex System ABDM has two ASIC by NISA and COMSOL Tools

Authors: A. Oukaira, A. Lakhssassi, O. Ettahri

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To make a good thermal management in an ABDM (Adapter Board Detector Module) card, we must first control temperature and its gradient from the first step in the design of integrated circuits ASIC of our complex system. In this paper, our main goal is to develop and validate the thermal stability in order to get an idea of the flow of heat around the ASIC in transient and thus address the thermal issues for integrated circuits at the ABDM card. However, we need heat sources simulations for ABDM card to establish its thermal mapping. This led us to perform simulations at each ASIC that will allow us to understand the thermal ABDM map and find real solutions for each one of our complex system that contains 36 ABDM map, taking into account the different layers around ASIC. To do a transient simulation under NISA, we had to build a function of power modulation in time TIMEAMP. The maximum power generated in the ASIC is 0.6 W. We divided the power uniformly in the volume of the ASIC. This power was applied for 5 seconds to visualize the evolution and distribution of heat around the ASIC. The DBC (Dirichlet Boundary conditions) method was applied around the ABDM at 25°C and just after these simulations in NISA tool we will validate them by COMSOL tool, wich is a numerical calculation software for a modular finite element for modeling a wide variety of physical phenomena characterizing a real problem. It will also be a design tool with its ability to handle 3D geometries for complex systems.

Keywords: ABDM, APD, thermal mapping, complex system

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1200 Assessing the Theoretical Suitability of Sentinel-2 and Worldview-3 Data for Hydrocarbon Mapping of Spill Events, Using Hydrocarbon Spectral Slope Model

Authors: K. Tunde Olagunju, C. Scott Allen, Freek Van Der Meer

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Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization are only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two (2) operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the hydrocarbon spectral slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven (7) different hydrocarbon oils (crude and refined oil) taken on ten (10) different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).

Keywords: hydrocarbon, oil spill, remote sensing, hyperspectral, multispectral, hydrocarbon-substrate combination, Sentinel-2, WorldView-3

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1199 Application of Artificial Neural Network in Assessing Fill Slope Stability

Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

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1198 Artificial Neural Network Approach for GIS-Based Soil Macro-Nutrients Mapping

Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

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Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

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1197 Identification of New Familial Breast Cancer Susceptibility Genes: Are We There Yet?

Authors: Ian Campbell, Gillian Mitchell, Paul James, Na Li, Ella Thompson

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The genetic cause of the majority of multiple-case breast cancer families remains unresolved. Next generation sequencing has emerged as an efficient strategy for identifying predisposing mutations in individuals with inherited cancer. We are conducting whole exome sequence analysis of germ line DNA from multiple affected relatives from breast cancer families, with the aim of identifying rare protein truncating and non-synonymous variants that are likely to include novel cancer predisposing mutations. Data from more than 200 exomes show that on average each individual carries 30-50 protein truncating mutations and 300-400 rare non-synonymous variants. Heterogeneity among our exome data strongly suggest that numerous moderate penetrance genes remain to be discovered, with each gene individually accounting for only a small fraction of families (~0.5%). This scenario marks validation of candidate breast cancer predisposing genes in large case-control studies as the rate-limiting step in resolving the missing heritability of breast cancer. The aim of this study is to screen genes that are recurrently mutated among our exome data in a larger cohort of cases and controls to assess the prevalence of inactivating mutations that may be associated with breast cancer risk. We are using the Agilent HaloPlex Target Enrichment System to screen the coding regions of 168 genes in 1,000 BRCA1/2 mutation-negative familial breast cancer cases and 1,000 cancer-naive controls. To date, our interim analysis has identified 21 genes which carry an excess of truncating mutations in multiple breast cancer families versus controls. Established breast cancer susceptibility gene PALB2 is the most frequently mutated gene (13/998 cases versus 0/1009 controls), but other interesting candidates include NPSR1, GSN, POLD2, and TOX3. These and other genes are being validated in a second cohort of 1,000 cases and controls. Our experience demonstrates that beyond PALB2, the prevalence of mutations in the remaining breast cancer predisposition genes is likely to be very low making definitive validation exceptionally challenging.

Keywords: predisposition, familial, exome sequencing, breast cancer

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1196 GIS Technology for Environmentally Polluted Sites with Innovative Process to Improve the Quality and Assesses the Environmental Impact Assessment (EIA)

Authors: Hamad Almebayedh, Chuxia Lin, Yu wang

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The environmental impact assessment (EIA) must be improved, assessed, and quality checked for human and environmental health and safety. Soil contamination is expanding, and sites and soil remediation activities proceeding around the word which simplifies the answer “quality soil characterization” will lead to “quality EIA” to illuminate the contamination level and extent and reveal the unknown for the way forward to remediate, countifying, containing, minimizing and eliminating the environmental damage. Spatial interpolation methods play a significant role in decision making, planning remediation strategies, environmental management, and risk assessment, as it provides essential elements towards site characterization, which need to be informed into the EIA. The Innovative 3D soil mapping and soil characterization technology presented in this research paper reveal the unknown information and the extent of the contaminated soil in specific and enhance soil characterization information in general which will be reflected in improving the information provided in developing the EIA related to specific sites. The foremost aims of this research paper are to present novel 3D mapping technology to quality and cost-effectively characterize and estimate the distribution of key soil characteristics in contaminated sites and develop Innovative process/procedure “assessment measures” for EIA quality and assessment. The contaminated site and field investigation was conducted by innovative 3D mapping technology to characterize the composition of petroleum hydrocarbons contaminated soils in a decommissioned oilfield waste pit in Kuwait. The results show the depth and extent of the contamination, which has been interred into a developed assessment process and procedure for the EIA quality review checklist to enhance the EIA and drive remediation and risk assessment strategies. We have concluded that to minimize the possible adverse environmental impacts on the investigated site in Kuwait, the soil-capping approach may be sufficient and may represent a cost-effective management option as the environmental risk from the contaminated soils is considered to be relatively low. This research paper adopts a multi-method approach involving reviewing the existing literature related to the research area, case studies, and computer simulation.

Keywords: quality EIA, spatial interpolation, soil characterization, contaminated site

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1195 Identity (Mis)Representation and Ideological Struggles in Discourses on Boko Haram in Nigeria

Authors: Temitope Ogungbemi

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Jama'atu Ahlis Sunna Lidda'awati wal-Jihad (also called Boko Haram) in the North-East of Nigeria has facilitated ideological binarity in discourses on the crisis. Since its proliferation, media representation of the crisis has facilitated identity contamination and ideological struggle through which other critical issues, such as religious intolerance, ethnic diversity and other forms of class conflict in the Nigerian state, are brought to public notice. Though Boko Haram insurgency is ideological laden, the manifestation of the inherent ideologies requires extensive scholarly attention in order deconstruct the veiled ideologies. Therefore, the thrust of this study is to critically investigate identity (mis)representation as a basis for ideological mapping in discourses on Boko Haram in Nigeria, adopting critical discourse analytical tools supported with insights from systemic functional linguistics and critical discourse analysis. The data for this study consist of articles on Boko Haram in Nigerian newspapers published in English. The data selection is purposive and aimed at responding to challenges that are inherent in Nigeria's multifaithism and multiculturalism, and their effects on the construction of narratives on Boko Haram. The study reveals that identity manipulation is a constructive device for ideological mapping, realised through labeling, agency activation, and transitivity. Identity representation in discourses on Boko Haram depicted four dichotomous binarities using exclusion, generalisation, contrasting and attribution.

Keywords: identity representation, ideology, Boko Haram, newspapers

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1194 Quantifying the Methods of Monitoring Timers in Electric Water Heater for Grid Balancing on Demand-Side Management: A Systematic Mapping Review

Authors: Yamamah Abdulrazaq, Lahieb A. Abrahim, Samuel E. Davies, Iain Shewring

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An electric water heater (EWH) is a powerful appliance that uses electricity in residential, commercial, and industrial settings, and the ability to control them properly will result in cost savings and the prevention of blackouts on the national grid. This article discusses the usage of timers in EWH control strategies for demand-side management (DSM). Up to the authors' knowledge, there is no systematic mapping review focusing on the utilisation of EWH control strategies in DSM has yet been conducted. Consequently, the purpose of this research is to identify and examine main papers exploring EWH procedures in DSM by quantifying and categorising information with regard to publication year and source, kind of methods, and source of data for monitoring control techniques. In order to answer the research questions, a total of 31 publications published between 1999 and 2023 were selected depending on specific inclusion and exclusion criteria. The data indicate that direct load control (DLC) has been somewhat more prevalent than indirect load control (ILC). Additionally, the mixing method is much lower than the other techniques, and the proportion of Real-time data (RTD) to non-real-time data (NRTD) is about equal.

Keywords: demand side management, direct load control, electric water heater, indirect load control, non real-time data, real-time data

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1193 Artificial Intelligence Models for Detecting Spatiotemporal Crop Water Stress in Automating Irrigation Scheduling: A Review

Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

Abstract:

Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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1192 The Role of Oral and Intestinal Microbiota in European Badgers

Authors: Emma J. Dale, Christina D. Buesching, Kevin R. Theis, David W. Macdonald

Abstract:

This study investigates the oral and intestinal microbiomes of wild-living European badgers (Meles meles) and will relate inter-individual differences to social contact networks, somatic and reproductive fitness, varying susceptibility to bovine tuberculous (bTB) and to the olfactory advertisement. Badgers are an interesting model for this research, as they have great variation in body condition, despite living in complex social networks and having access to the same resources. This variation in somatic fitness, in turn, affects breeding success, particularly in females. We postulate that microbiota have a central role to play in determining the successfulness of an individual. Our preliminary results, characterising the microbiota of individual badgers, indicate unique compositions of microbiota communities within social groups of badgers. This basal information will inform further questions related to the extent microbiota influence fitness. Hitherto, the potential role of microbiota has not been considered in determining host condition, but also other key fitness variables, namely; communication and resistance to disease. Badgers deposit their faeces in communal latrines, which play an important role in olfactory communication. Odour profiles of anal and subcaudal gland secretions are highly individual-specific and encode information about group-membership and fitness-relevant parameters, and their chemical composition is strongly dependent on symbiotic microbiota. As badgers sniff/ lick (using their Vomeronasal organ) and over-mark faecal deposits of conspecifics, these microbial communities can be expected to vary with social contact networks. However, this is particularly important in the context of bTB, where badgers are assumed to transmit bTB to cattle as well as conspecifics. Interestingly, we have found that some individuals are more susceptible to bTB than are others. As acquired immunity and thus potential susceptibility to infectious diseases are known to depend also on symbiotic microbiota in other members of the mustelids, a role of particularly oral microbiota can currently not be ruled out as a potential explanation for inter-individual differences in infection susceptibility of bTB in badgers. Tri annually badgers are caught in the context of a long-term population study that began in 1987. As all badgers receive an individual tattoo upon first capture, age, natal as well as previous and current social group-membership and other life history parameters are known for all animals. Swabs (subcaudal ‘scent gland’, anal, genital, nose, mouth and ear) and fecal samples will be taken from all individuals, stored at -80oC until processing. Microbial samples will be processed and identified at Wayne State University’s Theis (Host-Microbe Interactions) Lab, using High Throughput Sequencing (16S rRNA-encoding gene amplification and sequencing). Acknowledgments: Gas-Chromatography/ Mass-spectrometry (in the context of olfactory communication) analyses will be performed through an established collaboration with Dr. Veronica Tinnesand at Telemark University, Norway.

Keywords: communication, energetics, fitness, free-ranging animals, immunology

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1191 How Obesity Sparks the Immune System and Lessons from the COVID-19 Pandemic

Authors: Husham Bayazed

Abstract:

Purpose of Presentation: Obesity and overweight are among the biggest health challenges of the 21st century, according to the WHO. Obviously, obese individuals suffer different courses of disease – from infections and allergies to cancer- and even respond differently to some treatment options. Of note, obesity often seems to predispose and triggers several secondary diseases such as diabetes, arteriosclerosis, or heart attacks. Since decades it seems that immunological signals gear inflammatory processes among obese individuals with the aforementioned conditions. This review aims to shed light how obesity sparks or rewire the immune system and predisposes to such unpleasant health outcomes. Moreover, lessons from the Covid-19 pandemic ascertain that people living with pre-existing conditions such as obesity can develop severe acute respiratory syndrome (SARS), which needs to be elucidated how obesity and its adjuvant inflammatory process distortion contribute to enhancing severe COVID-19 consequences. Recent Findings: In recent clinical studies, obesity was linked to alter and sparks the immune system in different ways. Adipose tissue (AT) is considered as a secondary immune organ, which is a reservoir of tissue-resident of different immune cells with mediator release, making it a secondary immune organ. Adipocytes per se secrete several pro-inflammatory cytokines (IL-6, IL-4, MCP-1, and TNF-α ) involved in activation of macrophages resulting in chronic low-grade inflammation. The correlation between obesity and T cells dysregulation is pivotal in rewiring the immune system. Of note, autophagy occurrence in adipose tissues further rewire the immune system due to flush and outburst of leptin and adiponectin, which are cytokines and influencing pro-inflammatory immune functions. These immune alterations among obese individuals are collectively incriminated in triggering several metabolic disorders and playing role in increasing cancers incidence and susceptibility to different infections. During COVID-19 pandemic, it was verified that patients with pre-existing obesity being at greater risk of suffering severe and fatal clinical outcomes. Beside obese people suffer from increased airway resistance and reduced lung volume, ACE2 expression in adipose tissue seems to be high and even higher than that in lungs, which spike infection incidence. In essence, obesity with pre-existence of pro-inflammatory cytokines such as LI-6 is a risk factor for cytokine storm and coagulopathy among COVID-19 patients. Summary: It is well documented that obesity is associated with chronic systemic low-grade inflammation, which sparks and alter different pillars of the immune system and triggers different metabolic disorders, and increases susceptibility of infections and cancer incidence. The pre-existing chronic inflammation in obese patients with the augmented inflammatory response against the viral infection seems to increase the susceptibility of these patients to developing severe COVID-19. Although the new weight loss drugs and bariatric surgery are considered as breakthrough news for obesity treatment, but preventing is easier than treating it once it has taken hold. However, obesity and immune system link new insights dispute the role of immunotherapy and regulating immune cells treating diet-induced obesity.

Keywords: immunity, metabolic disorders, cancer, COVID-19

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1190 Prioritizing Ecosystem Services for South-Central Regions of Chile: An Expert-Based Spatial Multi-Criteria Approach

Authors: Yenisleidy Martinez Martinez, Yannay Casas-Ledon, Jo Dewulf

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The ecosystem services (ES) concept has contributed to draw attention to the benefits ecosystems generate for people and how necessary natural resources are for human well-being. The identification and prioritization of the ES constitute the first steps to undertake conservation and valuation initiatives on behalf of people. Additionally, mapping the supply of ES is a powerful tool to support decision making regarding the sustainable management of landscape and natural resources. In this context, the present study aimed to identify, prioritize and map the primary ES in Biobio and Nuble regions using a methodology that combines expert judgment, multi-attribute evaluation methods, and Geographic Information Systems (GIS). Firstly, scores about the capacity of different land use/cover types to supply ES and the importance attributed to each service were obtained from experts and stakeholders via an online survey. Afterward, the ES assessment matrix was constructed, and the weighted linear combination (WLC) method was applied to mapping the overall capacity of supply of provisioning, regulating and maintenance, and cultural services. Finally, prioritized ES for the study area were selected and mapped. The results suggest that native forests, wetlands, and water bodies have the highest supply capacities of ES, while urban and industrial areas and bare areas have a very low supply of services. On the other hand, fourteen out of twenty-nine services were selected by experts and stakeholders as the most relevant for the regions. The spatial distribution of ES has shown that the Andean Range and part of the Coastal Range have the highest ES supply capacity, mostly regulation and maintenance and cultural ES. This performance is related to the presence of native forests, water bodies, and wetlands in those zones. This study provides specific information about the most relevant ES in Biobio and Nuble according to the opinion of local stakeholders and the spatial identification of areas with a high capacity to provide services. These findings could be helpful as a reference by planners and policymakers to develop landscape management strategies oriented to preserve the supply of services in both regions.

Keywords: ecosystem services, expert judgment, mapping, multi-criteria decision making, prioritization

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1189 Sponge Urbanism as a Resilient City Design to Overcome Urban Flood Risk, for the Case of Aluva, Kerala, India

Authors: Gayathri Pramod, Sheeja K. P.

Abstract:

Urban flooding has been seen rising in cities for the past few years. This rise in urban flooding is the result of increasing urbanization and increasing climate change. A resilient city design focuses on 'living with water'. This means that the city is capable of accommodating the floodwaters without having to risk any loss of lives or properties. The resilient city design incorporates green infrastructure, river edge treatment, open space design, etc. to form a city that functions as a whole for resilience. Sponge urbanism is a recent method for building resilient cities and is founded by China in 2014. Sponge urbanism is the apt method for resilience building for a tropical town like Aluva of Kerala. Aluva is a tropical town that experiences rainfall of about 783 mm per month during the rainy season. Aluva is an urbanized town which faces the risk of urban flooding and riverine every year due to the presence of Periyar River in the town. Impervious surfaces and hard construction and developments contribute towards flood risk by posing as interference for a natural flow and natural filtration of water into the ground. This type of development is seen in Aluva also. Aluva is designed in this research as a town that have resilient strategies of sponge city and which focusses on natural methods of construction. The flood susceptibility of Aluva is taken into account to design the spaces for sponge urbanism and in turn, reduce the flood susceptibility for the town. Aluva is analyzed, and high-risk zones for development are identified through studies. These zones are designed to withstand the risk of flooding. Various catchment areas are identified according to the natural flow of water, and then these catchment areas are designed to act as a public open space and as detention ponds in case of heavy rainfall. Various development guidelines, according to land use, is also prescribed, which help in increasing the green cover of the town. Aluva is then designed to be a completely flood-adapted city or sponge city according to the guidelines and interventions.

Keywords: climate change, flooding, resilient city, sponge city, sponge urbanism, urbanization

Procedia PDF Downloads 147
1188 Multi-Temporal Mapping of Built-up Areas Using Daytime and Nighttime Satellite Images Based on Google Earth Engine Platform

Authors: S. Hutasavi, D. Chen

Abstract:

The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.

Keywords: built-up area extraction, google earth engine, adaptive thresholding method, rapid mapping

Procedia PDF Downloads 118
1187 Mapping Thermal Properties Using Resistivity, Lithology and Thermal Conductivity Measurements

Authors: Riccardo Pasquali, Keith Harlin, Mark Muller

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The ShallowTherm project is focussed on developing and applying a methodology for extrapolating relatively sparsely sampled thermal conductivity measurements across Ireland using mapped Litho-Electrical (LE) units. The primary data used consist of electrical resistivities derived from the Geological Survey Ireland Tellus airborne electromagnetic dataset, GIS-based maps of Irish geology, and rock thermal conductivities derived from both the current Irish Ground Thermal Properties (IGTP) database and a new programme of sampling and laboratory measurement. The workflow has been developed across three case-study areas that sample a range of different calcareous, arenaceous, argillaceous, and volcanic lithologies. Statistical analysis of resistivity data from individual geological formations has been assessed and integrated with detailed lithological descriptions to define distinct LE units. Thermal conductivity measurements from core and hand samples have been acquired for every geological formation within each study area. The variability and consistency of thermal conductivity measurements within each LE unit is examined with the aim of defining a characteristic thermal conductivity (or range of thermal conductivities) for each LE unit. Mapping of LE units, coupled with characteristic thermal conductivities, provides a method of defining thermal conductivity properties at a regional scale and facilitating the design of ground source heat pump closed-loop collectors.

Keywords: thermal conductivity, ground source heat pumps, resistivity, heat exchange, shallow geothermal, Ireland

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1186 Applications of Space Technology in Flood Risk Mapping in Parts of Haryana State, India

Authors: B. S. Chaudhary

Abstract:

The severity and frequencies of different disasters on the globe is increasing in recent years. India is also facing the disasters in the form of drought, cyclone, earthquake, landslides, and floods. One of the major causes of disasters in northern India is flood. There are great losses and extensive damage to the agricultural crops, property, human, and animal life. This is causing environmental imbalances at places. The annual global figures for losses due to floods run into over 2 billion dollar. India is a vast country with wide variations in climate and topography. Due to widespread and heavy rainfall during the monsoon months, floods of varying magnitude occur all over the country during June to September. The magnitude depends upon the intensity of rainfall, its duration and also the ground conditions at the time of rainfall. Haryana, one of the agriculturally dominated northern states is also suffering from a number of disasters such as floods, desertification, soil erosion, land degradation etc. Earthquakes are also frequently occurring but of small magnitude so are not causing much concern and damage. Most of the damage in Haryana is due to floods. Floods in Haryana have occurred in 1978, 1988, 1993, 1995, 1998, and 2010 to mention a few. The present paper deals with the Remote Sensing and GIS applications in preparing flood risk maps in parts of Haryana State India. The satellite data of various years have been used for mapping of flood affected areas. The Flooded areas have been interpreted both visually and digitally and two classes-flooded and receded water/ wet areas have been identified for each year. These have been analyzed in GIS environment to prepare the risk maps. This shows the areas of high, moderate and low risk depending on the frequency of flood witness. The floods leave a trail of suffering in the form of unhygienic conditions due to improper sanitation, water logging, filth littered in the area, degradation of materials and unsafe drinking water making the people prone to many type diseases in short and long run. Attempts have also been made to enumerate the causes of floods. The suggestions are given for mitigating the fury of floods and proper management issues related to evacuation and safe places nearby.

Keywords: flood mapping, GIS, Haryana, India, remote sensing, space technology

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1185 Geophysical Mapping of the Groundwater Aquifer System in Gode Area, Northeastern Hosanna, Ethiopia

Authors: Esubalew Yehualaw Melaku

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In this study, two basic geophysical methods are applied for mapping the groundwater aquifer system in the Gode area along the Guder River, northeast of Hosanna town, near the western margin of the Central Main Ethiopian Rift. The main target of the study is to map the potential aquifer zone and investigate the groundwater potential for current and future development of the resource in the Gode area. The geophysical methods employed in this study include, Vertical Electrical Sounding (VES) and magnetic survey techniques. Electrical sounding was used to examine and map the depth to the potential aquifer zone of the groundwater and its distribution over the area. On the other hand, a magnetic survey was used to delineate contact between lithologic units and geological structures. The 2D magnetic modeling and the geoelectric sections are used for the identification of weak zones, which control the groundwater flow and storage system. The geophysical survey comprises of twelve VES readings collected by using a Schlumberger array along six profile lines and more than four hundred (400) magnetic readings at about 10m station intervals along four profiles and 20m along three random profiles. The study result revealed that the potential aquifer in the area is obtained at a depth range from 45m to 92m. This is the response of the highly weathered/ fractured ignimbrite and pumice layer with sandy soil, which is the main water-bearing horizon. Overall, in the neighborhood of four VES points, VES- 2, VES- 3, VES-10, and VES-11, shows good water-bearing zones in the study area.

Keywords: vertical electrical sounding, magnetic survey, aquifer, groundwater potential

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1184 Fire Effects on Soil Properties of Meshchera Plain, Russia

Authors: Anna Tsibart, Timur Koshovskii

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The properties of soils affected by the wildfires of 2002, 2010, and 2012 in Meshchera plain (Moscow region, Russia) were considered in a current research. The formation of ash horizons instead of organic peat horizons was detected both in histosols and histic podzols. The increase of pH and magnetic susceptibility was observed in soil profiles. Significant burning out of organic matter was observed, but already two years after the fire the new stage of organic matter accumulation started.

Keywords: wildfires, peat soils, organic matter, Meshchera plain

Procedia PDF Downloads 651
1183 Systematic Mapping Study of Digitization and Analysis of Manufacturing Data

Authors: R. Clancy, M. Ahern, D. O’Sullivan, K. Bruton

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The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Keywords: analytics, digitization, industry 4.0, manufacturing

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1182 Cognitive Model of Analogy Based on Operation of the Brain Cells: Glial, Axons and Neurons

Authors: Ozgu Hafizoglu

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Analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with attributional, deep structural, casual relations that are essential to learning, to innovation in artificial worlds, and to discovery in science. Cognitive Model of Analogy (CMA) leads and creates information pattern transfer within and between domains and disciplines in science. This paper demonstrates the Cognitive Model of Analogy (CMA) as an evolutionary approach to scientific research. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions. In this paper, the model of analogical reasoning is created based on brain cells, their fractal, and operational forms within the system itself. Visualization techniques are used to show correspondences. Distinct phases of the problem-solving processes are divided thusly: encoding, mapping, inference, and response. The system is revealed relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain cells: glial cells, axons, axon terminals, and neurons, relative to matching conditions of analogical reasoning and relational information. It’s found that encoding, mapping, inference, and response processes in four-term analogical reasoning are corresponding with the fractal and operational forms of brain cells: glial, axons, and neurons.

Keywords: analogy, analogical reasoning, cognitive model, brain and glials

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1181 Forming for Confirmation of Predicted Epoxy Forming Composition Range in Cr-Zn System

Authors: Foad Saadi

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Aim of this work was to determine the approximate Epoxy forming composition range of Cr-Zn system for the composites produced by forming compositing. It was predicted by MI edema semi-empirical model that the composition had to be in the range of 30-60 wt. % tin, while Cr-32Zn had the most susceptibility to produce amorphous composite. In the next stage, some different compositions of Cr-Zn were foamingly composited, where one of them had the proper predicted composition. Products were characterized by SDM analysis. There was a good agreement between calculation and experiments, in which Cr-32Zn composite had the most amorphization degree.

Keywords: Cr-Zn system, forming compositing, amorphous composite, MI edema model

Procedia PDF Downloads 291
1180 Localization of Frontal and Temporal Speech Areas in Brain Tumor Patients by Their Structural Connections with Probabilistic Tractography

Authors: B.Shukir, H.Woo, P.Barzo, D.Kis

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Preoperative brain mapping in tumors involving the speech areas has an important role to reduce surgical risks. Functional magnetic resonance imaging (fMRI) is the gold standard method to localize cortical speech areas preoperatively, but its availability in clinical routine is difficult. Diffusion MRI based probabilistic tractography is available in head MRI. It’s used to segment cortical subregions by their structural connectivity. In our study, we used probabilistic tractography to localize the frontal and temporal cortical speech areas. 15 patients with left frontal tumor were enrolled to our study. Speech fMRI and diffusion MRI acquired preoperatively. The standard automated anatomical labelling atlas 3 (AAL3) cortical atlas used to define 76 left frontal and 118 left temporal potential speech areas. 4 types of tractography were run according to the structural connection of these regions to the left arcuate fascicle (FA) to localize those cortical areas which have speech functions: 1, frontal through FA; 2, frontal with FA; 3, temporal to FA; 4, temporal with FA connections were determined. Thresholds of 1%, 5%, 10% and 15% applied. At each level, the number of affected frontal and temporal regions by fMRI and tractography were defined, the sensitivity and specificity were calculated. At the level of 1% threshold showed the best results. Sensitivity was 61,631,4% and 67,1523,12%, specificity was 87,210,4% and 75,611,37% for frontal and temporal regions, respectively. From our study, we conclude that probabilistic tractography is a reliable preoperative technique to localize cortical speech areas. However, its results are not feasible that the neurosurgeon rely on during the operation.

Keywords: brain mapping, brain tumor, fMRI, probabilistic tractography

Procedia PDF Downloads 149