Search results for: spatial data base

Authors: Junaid Asimiyu Mohammed, Olakunle Docas Tosin

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The housing environment in many developing countries is fraught with risks that have potential negative impacts on the lives of the residents. The study examined the risk factors in residential areas of two neighborhoods in Bosso Local Government Areas of Minna in Nigeria with a view to determining the level of their potential impacts. A sample of 378 households was drawn from the estimated population of 22,751 household heads. The questionnaire and direct observation were used as instruments for data collection. The data collected were analyzed using the Relative Importance Index (RII) rule to determine the level of the potential impact of the risk factors while ArcGIS was used for mapping the spatial distribution of the risks. The study established that the housing environment of Angwan Biri and El-Waziri areas of Bosso is poor and vulnerable as 26% of the houses were not habitable and 57% were only fairly habitable. The risks of epidemics, building collapse and rainstorms were evident in the area as 53% of the houses had poor ventilation; 20% of residents had no access to toilets; 47% practiced open waste dumping; 46% of the houses had cracked walls while 52% of the roofs were weak and sagging. The results of the analysis of the potential impact of the risk factors indicate a RII score of 0.528 for building collapse, 0.758 for rainstorms and 0.830 for epidemics, indicating a moderate to very high level of potential impacts. The mean RII score of 0.639 shows a significant potential impact of the risk factors. The study recommends the implementation of sanitation measures, provision of basic urban facilities and neighborhood revitalization through housing infrastructure retrofitting as measures to mitigate the risks of disasters and improve the living conditions of the residents of the study area.

Keywords: assessment, risk, residential, Nigeria

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Authors: A. Anis, W. Bekheet, A. El Hakim

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Implementing a Road Safety Management System (SMS) in a crowded developing country such as Egypt is a necessity. Beginning a sustainable SMS requires a comprehensive reliable data system for all information pertinent to road crashes. In this paper, a survey for the available data in Egypt and validating it for using in an SMS in Egypt. The research provides some missing data, and refer to the unavailable data in Egypt, looking forward to the contribution of the scientific society, the authorities, and the public in solving the problem of missing or unreliable crash data. The required data for implementing an SMS in Egypt are divided into three categories; the first is available data such as fatality and injury rates and it is proven in this research that it may be inconsistent and unreliable, the second category of data is not available, but it may be estimated, an example of estimating vehicle cost is available in this research, the third is not available and can be measured case by case such as the functional and geometric properties of a facility. Some inquiries are provided in this research for the scientific society, such as how to improve the links among stakeholders of road safety in order to obtain a consistent, non-biased, and reliable data system.

Keywords: road safety management system, road crash, road fatality, road injury

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Authors: Rama Umesh Pandey, Jyoti Yadav

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Flooding is one of the waterborne disasters that causes extensive destruction in urban areas. Developing countries are at a higher risk of such damage and more than half of the global flooding events take place in Asian countries including India. Urban flooding is more of a human-induced disaster rather than natural. This is highly influenced by the anthropogenic factors, besides metrological and hydrological causes. Unplanned urbanization and poor management of cities enhance the impact manifold and cause huge loss of life and property in urban areas. It is an irony that urban areas have been facing water scarcity in summers and flooding during monsoon. This paper is an attempt to highlight the factors responsible for flooding in a city especially from an urban planning perspective and to suggest mitigating measures through spatial planning interventions. Analysis has been done in two stages; first is to assess the impacts of previous flooding events and second to analyze the factors responsible for flooding at macro and micro level in cities. Bhopal, a city in Central India having nearly two million population, has been selected for the study. The city has been experiencing flooding during heavy rains in monsoon. The factors responsible for urban flooding were identified through literature review as well as various case studies from different cities across the world and India. The factors thus identified were analyzed for both macro and micro level influences. For macro level, the previous flooding events that have caused huge destructions were analyzed and the most affected areas in Bhopal city were identified. Since the identified area was falling within the catchment of a drain so the catchment area was delineated for the study. The factors analyzed were: rainfall pattern to calculate the return period using Weibull’s formula; imperviousness through mapping in ArcGIS; runoff discharge by using Rational method. The catchment was divided into micro watersheds and the micro watershed having maximum impervious surfaces was selected to analyze the coverage and effect of physical infrastructure such as: storm water management; sewerage system; solid waste management practices. The area was further analyzed to assess the extent of violation of ‘building byelaws’ and ‘development control regulations’ and encroachment over the natural water streams. Through analysis, the study has revealed that the main issues have been: lack of sewerage system; inadequate storm water drains; inefficient solid waste management in the study area; violation of building byelaws through extending building structures ether on to the drain or on the road; encroachments by slum dwellers along or on to the drain reducing the width and capacity of the drain. Other factors include faulty culvert’s design resulting in back water effect. Roads are at higher level than the plinth of houses which creates submersion of their ground floors. The study recommends spatial planning interventions for mitigating urban flooding and strategies for management of excess rain water during monsoon season. Recommendations have also been made for efficient land use management to mitigate water logging in areas vulnerable to flooding.

Keywords: mitigating strategies, spatial planning interventions, urban flooding, violation of development control regulations

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Authors: Ibrahim Gomaa, Hoda M. O. Mokhtar

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Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Keywords: continuous query processing, dynamic database, moving object, skyline queries

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Authors: Abraham Addo-Bediako, Sophy Nukeri, Tebatso Mmako

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Many freshwater ecosystems have been subjected to prolonged and cumulative pollution as a result of human activities such as mining, agricultural, industrial and human settlements in their catchments. The objective of this study was to investigate spatial variability of heavy metal pollution of sediments and possible sources of pollutants in two streams of the Olifants River System, South Africa. Stream sediments were collected and analysed for Arsenic (As), Cadmium (Cd), Chromium (Cr), Copper (Cu), Lead (Pb), Nickel (Ni) and Zinc (Zn) concentrations using inductively coupled plasma-mass mass spectrometry (ICP-MS). In both rivers, As, Cd, Cu, Pb and Zn fell within the concentration ranges recommended by CCME and ANZECC, while the concentrations of Cr and Ni exceeded the standards; the results indicated that Cr and Ni in the sediments originated from human activities and not from natural geological background. The index of geo-accumulation (Igeo) was used to assess the degree of pollution. The results of the geo-accumulation index evaluation showed that Cr and Ni were present in the sediments of the rivers at moderately to extremely polluted levels, while As, Cd, Cu, Pb and Zn existed at unpolluted to moderately polluted levels. Generally, heavy metal concentrations increased along the gradient in the rivers. The high concentrations of Cr and Ni in both rivers are of great concern, as previously these two rivers were classified to be supplying the Olifants River with water of good quality. There is a critical need, therefore to monitor heavy metal concentrations and distributions, as well as a comprehensive plan to prevent health risks, especially those communities still reliant on untreated water from the rivers, as sediment pollution may pose a risk of secondary water pollution under sediment disturbance and/or changes in the geo-chemistry of sediments.

Keywords: geo-accumulation index, heavy metals, sediment pollution, water quality

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: James Brown, Stella Kortekaas, Ian Finnie, George Zhang, Christine Devine, Neil Healy

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The use of GIS as an analysis tool for engineering decision making is now best practice in the offshore industry. GIS enables multidisciplinary data integration, analysis and visualisation which allows the presentation of large and intricate datasets in a simple map-interface accessible to all project stakeholders. Presenting integrated geoscience and geotechnical data in GIS enables decision makers to be well-informed. This paper is a successful case study of how GIS spatial analysis techniques were applied to help select the most favourable pipeline route. Routing a pipeline through any natural environment has numerous obstacles, whether they be topographical, geological, engineering or financial. Where the pipeline is subjected to external hydrostatic water pressure and is carrying pressurised hydrocarbons, the requirement to safely route the pipeline through hazardous terrain becomes absolutely paramount. This study illustrates how the application of modern, GIS-based pipeline routing techniques enabled the identification of a single most-favourable pipeline route crossing of a challenging seabed terrain. Conventional approaches to pipeline route determination focus on manual avoidance of primary constraints whilst endeavouring to minimise route length. Such an approach is qualitative, subjective and is liable to bias towards the discipline and expertise that is involved in the routing process. For very short routes traversing benign seabed topography in shallow water this approach may be sufficient, but for deepwater geohazardous sites, the need for an automated, multi-criteria, and quantitative approach is essential. This study combined multiple routing constraints using modern least-cost-routing algorithms deployed in GIS, hitherto unachievable with conventional approaches. The least-cost-routing procedure begins with the assignment of geocost across the study area. Geocost is defined as a numerical penalty score representing hazard posed by each routing constraint (e.g. slope angle, rugosity, vulnerability to debris flows) to the pipeline. All geocosted routing constraints are combined to generate a composite geocost map that is used to compute the least geocost route between two defined terminals. The analyses were applied to select the most favourable pipeline route for a potential gas development in deep water. The study area is geologically complex with a series of incised, potentially active, canyons carved into a steep escarpment, with evidence of extensive debris flows. A similar debris flow in the future could cause significant damage to a poorly-placed pipeline. Protruding inter-canyon spurs offer lower-gradient options for ascending an escarpment but the vulnerability of periodic failure of these spurs is not well understood. Close collaboration between geoscientists, pipeline engineers, geotechnical engineers and of course the gas export pipeline operator guided the analyses and assignment of geocosts. Shorter route length, less severe slope angles, and geohazard avoidance were the primary drivers in identifying the most favourable route.

Keywords: geocost, geohazard, pipeline route determination, pipeline route optimisation, spatial analysis

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Authors: Ibrahim Baba

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The work examines the nature and causes of differential politics in Africa with particular reference to the sub-Saharan region of the continent. It also among other objectives provides alternative panacea to gender discrimination in African politics and offers solutions on how to promote political inclusion of all citizens in respect of gender differences in Africa. The work is conducted using library base documentation analysis.

Keywords: gender, political, participation, differential politics, sub-Saharan Africa

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Authors: Xu Du, Aparna S. Varde

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In this research, we propose to conduct diagnostic and predictive analysis about the key factors and consequences of urban population relocation. To achieve this goal, urban simulation models extract the urban development trends as land use change patterns from a variety of data sources. The results are treated as part of urban big data with other information such as population change and economic conditions. Multiple data mining methods are deployed on this data to analyze nonlinear relationships between parameters. The result determines the driving force of population relocation with respect to urban sprawl and urban sustainability and their related parameters. Experiments so far reveal that data mining methods discover useful knowledge from the multicity urban data. This work sets the stage for developing a comprehensive urban simulation model for catering to specific questions by targeted users. It contributes towards achieving sustainability as a whole.

Keywords: data mining, environmental modeling, sustainability, urban planning

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Authors: Heribert R. Kaijage, Samuel N. A. Codjoe, Simon H. D. Mamuya, Mangi J. Ezekiel

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There is strong evidence that climate has changed significantly affecting various sectors including public health. The recommended feasible solution is adopting development trajectories which combine both mitigation and adaptation measures for improving resilience pathways. This approach demands a consideration for complex interactions between climate and social-ecological systems. While other sectors such as agriculture and water have developed climate resilience indices, the public health sector in Tanzania is still lagging behind. The aim of this study was to find out how can we use Demographic and Health Surveys (DHS) linked with Remote Sensing (RS) technology and metrological information as tools to inform climate change resilient development and evaluation for the health sector. Methodological review was conducted whereby a number of studies were content analyzed to find appropriate indicators and indices for climate resilience household and their integration approach. These indicators were critically reviewed, listed, filtered and their sources determined. Preliminary identification and ranking of indicators were conducted using participatory approach of pairwise weighting by selected national stakeholders from meeting/conferences on human health and climate change sciences in Tanzania. DHS datasets were retrieved from Measure Evaluation project, processed and critically analyzed for possible climate change indicators. Other sources for indicators of climate change exposure were also identified. For the purpose of preliminary reporting, operationalization of selected indicators was discussed to produce methodological approach to be used in resilience comparative analysis study. It was found that household climate resilient index depends on the combination of three indices namely Household Adaptive and Mitigation Capacity (HC), Household Health Sensitivity (HHS) and Household Exposure Status (HES). It was also found that, DHS alone cannot complement resilient evaluation unless integrated with other data sources notably flooding data as a measure of vulnerability, remote sensing image of Normalized Vegetation Index (NDVI) and Metrological data (deviation from rainfall pattern). It can be concluded that if these indices retrieved from DHS data sets are computed and scientifically integrated can produce single climate resilience index and resilience maps could be generated at different spatial and time scales to enhance targeted interventions for climate resilient development and evaluations. However, further studies are need to test for the sensitivity of index in resilience comparative analysis among selected regions.

Keywords: climate change, resilience, remote sensing, demographic and health surveys

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Authors: Munenari Inoguchi, Keiko Tamura

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In Japan, we were suffered by earthquake, typhoon, and flood disaster in 2019. Especially, 38 of 47 prefectures were affected by typhoon #1919 occurred in October 2019. By this disaster, 99 people were dead, three people were missing, and 484 people were injured as human damage. Furthermore, 3,081 buildings were totally collapsed, 24,998 buildings were half-collapsed. Once disaster occurs, local responders have to inspect damage level of each building by themselves in order to certificate building damage for survivors for starting their life reconstruction process. At that disaster, the total number to be inspected was so high. Based on this situation, Cabinet Office of Japan approved the way to detect building damage level efficiently, that is collectively detection. However, they proposed a just guideline, and local responders had to establish the concrete and infallible method by themselves. Against this issue, we decided to establish the effective and efficient methodology to detect building damage level collectively with flood depth. Besides, we thought that the flood depth was relied on the land height, and we decided to utilize GIS (Geographic Information System) for analyzing the elevation spatially. We focused on the analyzing tool of spatial interpolation, which is utilized to survey the ground water level usually. In establishing the methodology, we considered 4 key-points: 1) how to satisfy the condition defined in the guideline approved by Cabinet Office for detecting building damage level, 2) how to satisfy survivors for the result of building damage level, 3) how to keep equitability and fairness because the detection of building damage level was executed by public institution, 4) how to reduce cost of time and human-resource because they do not have enough time and human-resource for disaster response. Then, we proposed a methodology for detecting building damage level collectively with flood depth utilizing GIS with five steps. First is to obtain the boundary of flooded area. Second is to collect the actual flood depth as sampling over flooded area. Third is to execute spatial analysis of interpolation with sampled flood depth to detect two-dimensional flood depth extent. Fourth is to divide to blocks by four categories of flood depth (non-flooded, over the floor to 100 cm, 100 cm to 180 cm and over 180 cm) following lines of roads for getting satisfaction from survivors. Fifth is to put flood depth level to each building. In Koriyama city of Fukushima prefecture, we proposed the methodology of collectively detection for building damage level as described above, and local responders decided to adopt our methodology at typhoon #1919 in 2019. Then, we and local responders detect building damage level collectively to over 1,000 buildings. We have received good feedback that the methodology was so simple, and it reduced cost of time and human-resources.

Keywords: building damage inspection, flood, geographic information system, spatial interpolation

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Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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Authors: Xia Luo, Cheng Zeng

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Under the promotion of the Central Committee of the Communist Party of China and the State Council in 2017, Xiong'an New Area is the third crucial new area in China established after Shenzhen and Shanghai. Its constructions' significance lies in mitigating Beijing's non-capital functions and exploring a new mode of optimizing development in densely populated and economically intensive areas. For this purpose, developing underground logistics can assume the role of goods distribution in the capital, relieve the road transport pressure in Beijing-Tianjin-Hebei Urban Agglomeration, adjust and optimize the urban layout and spatial structure of it. Firstly, the construction planning of Xiong'an New Area and underground logistics development are summarized, especially the development status abroad, the development trend, and bottlenecks of underground logistics in China. This paper explores the technicality, feasibility, and necessity of four modes of transportation. There are pneumatic capsule pipeline (PCP) technology, the CargoCap technology, cable hauled mule, and automatic guided vehicle (AGV). The above technical parameters and characteristics are introduced to relevant experts or scholars. Through establishing an indicator system, carrying out a questionnaire survey with the Delphi method, the final suggestion is obtained: China should develop logistics vehicles similar to CargoCap, adopting rail mode and driverless mode. Based on China's temporal and spatial logistics demand and the geographical pattern of Xiong'an New Area, the construction scale, technical parameters, node location, and other vital parameters of underground logistics are planned. In this way, we hope to speed up the new area's construction and the logistics industry's innovation.

Keywords: the Xiong'an new area, underground logistics, contrastive analysis, CargoCap, logistics planning

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Authors: Thuan Nguyen

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In the present time, data to a data-driven knowledge-based economy is the same as oil to the industrial age hundreds of years ago. Data is everywhere in vast volumes! Big data analytics is expected to help firms not only efficiently improve performance but also completely transform how they should run their business. However, employing the emergent technology successfully is not easy, and assessing the roles of big data in improving firm performance is even much harder. There was a lack of studies that have examined the impacts of big data analytics on organizational performance. This study aimed to fill the gap. The present study suggested using firms’ intellectual capital as a proxy for big data in evaluating its impact on organizational performance. The present study employed the Value Added Intellectual Coefficient method to measure firm intellectual capital, via its three main components: human capital efficiency, structural capital efficiency, and capital employed efficiency, and then used the structural equation modeling technique to model the data and test the models. The financial fundamental and market data of 100 randomly selected publicly listed firms were collected. The results of the tests showed that only human capital efficiency had a significant positive impact on firm profitability, which highlighted the prominent human role in the impact of big data technology.

Keywords: big data, big data analytics, intellectual capital, organizational performance, value added intellectual coefficient

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Authors: Hitesh Tahbildar

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The cost of test data generation for a program is computationally very high. In general case, no algorithm to generate test data for all types of algorithms has been found. The cost of generating test data for different types of algorithm is different. Till date, people are emphasizing the need to generate test data for different types of programming constructs rather than different types of algorithms. The test data generation methods have been implemented to find heuristics for different types of algorithms. Some algorithms that includes divide and conquer, backtracking, greedy approach, dynamic programming to find the minimum cost of test data generation have been tested. Our experimental results say that some of these types of algorithm can be used as a necessary condition for selecting heuristics and programming constructs are sufficient condition for selecting our heuristics. Finally we recommend the different heuristics for test data generation to be selected for different types of algorithms.

Keywords: ongest path, saturation point, lmax, kL, kS

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Authors: Mokrani Mohamed Amine

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In this paper, we have implemented successive interference cancellation algorithms in the 5G downlink. We have calculated the maximum throughput in Frequency Division Duplex (FDD) mode in the downlink, where we have obtained a value equal to 836932 b/ms. The transmitter is of type Multiple Input Multiple Output (MIMO) with eight transmitting and receiving antennas. Each antenna among eight transmits simultaneously a data rate of 104616 b/ms that contains the binary messages of the three users; in this case, the Cyclic Redundancy Check CRC is negligible, and the MIMO category is the spatial diversity. The technology used for this is called Non-Orthogonal Multiple Access (NOMA) with a Quadrature Phase Shift Keying (QPSK) modulation. The transmission is done in a Rayleigh fading channel with the presence of obstacles. The MIMO Successive Interference Cancellation (SIC) receiver with two transmitting and receiving antennas recovers its binary message without errors for certain values of transmission power such as 50 dBm, with 0.054485% errors when the transmitted power is 20dBm and with 0.00286763% errors for a transmitted power of 32 dBm(in the case of user 1) as well as with 0.0114705% errors when the transmitted power is 20 dBm also with 0.00286763% errors for a power of 24 dBm(in the case of user2) by applying the steps involved in SIC.

Keywords: 5G, NOMA, QPSK, TBS, LDPC, SIC, capacity

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Authors: Sher Muhammad, Mirza Muhammad Waqar

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It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79 to 24.85 degree in latitude and 66.91 to 66.97 degree in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image preprocessing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end-member extraction. Well-distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (white mangroves) and Avicennia Germinans (black mangroves) have been observed throughout the study area.

Keywords: mangrove, hyperspectral, hyperion, SAM, SFF, SID

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Authors: Katerina Koliou, Scott Parr, Evangelos Kaisar

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The surface transportation of freight is particularly vulnerable to storm and hurricane disasters, while at the same time, it is the primary transportation mode for delivering medical supplies, fuel, water, and other essential goods. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The research investigation used Florida's statewide continuous-count station traffic volumes, where then compared between years, to identify locations where traffic was moving differently during the evacuation. The data was then used to identify days on which traffic was significantly different between years. While the literature on auto-based evacuations is extensive, the consideration of freight travel is lacking. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The goal of this research was to investigate the movement of vehicles by classification, with an emphasis on freight during two major evacuation events: hurricanes Irma (2017) and Michael (2018). The methodology of the research was divided into three phases: data collection and management, spatial analysis, and temporal comparisons. Data collection and management obtained continuous-co station data from the state of Florida for both 2017 and 2018 by vehicle classification. The data was then processed into a manageable format. The second phase used geographic information systems (GIS) to display where and when traffic varied across the state. The third and final phase was a quantitative investigation into which vehicle classifications were statistically different and on which dates statewide. This phase used a two-sample, two-tailed t-test to compare sensor volume by classification on similar days between years. Overall, increases in freight movement between years prevented a more precise paired analysis. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm reentry. Of the more significant findings, the research results showed that commercial-use vehicles may have underutilized rest areas during the evacuation, or perhaps these rest areas were closed. This may suggest that truckers are driving longer distances and possibly longer hours before hurricanes. Another significant finding of this research was that changes in traffic patterns for commercial-use vehicles occurred earlier and lasted longer than changes for personal-use vehicles. This finding suggests that commercial vehicles are perhaps evacuating in a fashion different from personal use vehicles. This paper may serve as the foundation for future research into commercial travel during evacuations and explore additional factors that may influence freight movements during evacuations.

Keywords: evacuation, freight, travel time, evacuation

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Authors: Olumuyiwa Idowu Ojo, Oluwatobi Peter Olowo

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The study developed a Geographical Information Systems (GIS) database and mapped inter-annual changes in crop yields of cassava, cowpea, maize, rice, melon and yam as a response to inter-annual rainfall and temperature variability in Southwest, Nigeria. The aim of this project is to study the comparative analysis of the weather variability impact of six crops yield (Rice, melon, yam, cassava, Maize and cowpea) in South Western States of Nigeria (Oyo, Osun, Ekiti, Ondo, Ogun and Lagos) from 1991 – 2007. The data was imported and analysed in the Arch GIS 9 – 3 software environment. The various parameters (temperature, rainfall, crop yields) were interpolated using the kriging method. The results generated through interpolation were clipped to the study area. Geographically weighted regression was chosen from the spatial statistics toolbox in Arch GIS 9.3 software to analyse and predict the relationship between temperature, rainfall and the different crops (Cowpea, maize, rice, melon, yam, and cassava).

Keywords: GIS, crop yields, comparative analysis, temperature, rainfall, weather variability

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Authors: Hatice Kübra Koç

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For academia, collecting reliable and valid data is one of the most significant issues for researchers. However, it is not the same procedure for all different target groups; meanwhile, during data collection from teenagers, young adults, or adults, researchers can use common data collection tools such as questionnaires, interviews, and semi-structured interviews; yet, for young learners and very young ones, these reliable and valid data collection tools cannot be easily designed or applied by the researchers. In this study, firstly, common data collection tools are examined for ‘very young’ and ‘young learners’ participant groups since it is thought that the quality and efficiency of an academic study is mainly based on its valid and correct data collection and data analysis procedure. Secondly, two different data collection instruments for very young and young learners are stated as discussing the efficacy of them. Finally, a suggested data collection tool – a performance-based questionnaire- which is specifically developed for ‘very young’ and ‘young learners’ participant groups in the field of teaching English to young learners as a foreign language is presented in this current study. The designing procedure and suggested items/factors for the suggested data collection tool are accordingly revealed at the end of the study to help researchers have studied with young and very learners.

Keywords: data collection instruments, performance-based questionnaire, young learners, very young learners

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Authors: M. A. Hernández-Ceballos, E. G. San Miguel, C. Galán, J. P. Bolívar

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The evolution of 7Be and 210Pb activity concentrations in surface air along the Guadalquivir valley (southern Iberian Peninsula) is presented in this study. Samples collected for 48 h, every fifteen days, from September 2012 to November 2013 at two sampling sites (Huelva city in the mouth and Cordoba city in the middle (located 250 km far away)), are used to 1) analysing the spatial variability and 2) understanding the influence of wind conditions on 7Be and 210Pb. Similar average concentrations were registered along the valley. The mean 7Be activity concentration was 4.46 ± 0.21 mBq/m3 at Huelva and 4.33 ± 0.20 mBq/m3 at Cordoba, although registering higher maximum and minimum values at Cordoba (9.44 mBq/m3 and 1.80 mBq/m3) than at Huelva (7.95 mBq/m3 and 1.04 mBq/m3). No significant differences were observed in the 210Pb mean activity concentrations between Cordoba (0.40 ± 0.04 mBq/m3) and Huelva (0.35 ± 0.04 mBq/m3), although the maximum (1.10 mBq/m3 and 0.87 mBq/m3) and minimum (0.02 mBq/m3 and 0.04 mBq/m3) values were recorded in Cordoba. Although similar average concentrations were obtained in both sites, the temporal evolution of both natural radionuclides presents differences between them. The meteorological analysis of two sampling periods, in which large differences on 7Be and 210Pb concentrations are observed, indicates the different impact of surface and upper wind dynamics. The analysis reveals the different impact of the two sea-land breeze patterns usually observed along the valley (pure and non-pure) and the corresponding air masses at higher layers associated with each one. The pure, with short development (around 30 km inland) and increasing accumulation process, favours high concentrations of both radionuclides in Huelva (coastal site), while the non-pure, with winds sweeping the valley until arrive to Cordoba (250 km far away), causes high activity values at this site. These results reveal the impact of mesoscale conditions on these two natural radionuclides, and the importance of these circulations on its spatial and temporal variability.

Keywords: 7Be, 210Pb, air masses, mesoscale process

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Authors: Sergio Perez Rodriguez

Abstract:

Coltan Artisanal and Small-Scale Mining (ASM) production from Africa's Great Lakes region has previously been addressed at large scales, notably from regional to country levels. The current findings address the unresolved issue of a production model of ASM of coltan ore by an average Democratic Republic of Congo (DRC) mineworker, which can be used as a reference for a similar characterization of the daily labor of counterparts from other countries in the region. To that end, the Fundamental Equation of Mineral Production has been applied, considering a miner's average daily output of coltan, estimated in the base of gross statistical data gathered from reputable sources. Results indicate daily yields of individual miners in the order of 300 g of coltan ore, with hourly peaks of production in the range of 30 to 40 g of the mineral. Yields are expected to be in the order of 5 g or less during the least productive hours. These outputs are expected to be achieved during the halves of the eight to ten hours of daily working sessions that these artisanal laborers can attend during the mining season.

Keywords: coltan, mineral production, production to reserve ratio, artisanal mining, small-scale mining, ASM, human work, Great Lakes region, Democratic Republic of Congo

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Authors: Yaxin Bi

Abstract:

Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.

Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors

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Authors: Fethi Bouksila, Nessrine Zemni, Fairouz Slama, Magnus Persson, Ronny Berndasson, Akissa Bahri

Abstract:

Electromagnetic sensor EM 38 was used to predict and map soil salinity (ECe) in arid oasis. Despite the high spatial variation of soil moisture and shallow watertable, significant ECe-EM relationships were developed. The low drainage network efficiency is the main factor of soil salinization

Keywords: soil salinity map, electromagnetic induction, EM38, oasis, shallow watertable

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Authors: S. Vavias, T. R. Brewer, T. S. Farewell

Abstract:

Coastal floods have been identified as an important natural hazard that can cause significant damage to the populated built-up areas, related infrastructure and also ecosystems and habitats. This study attempts to fill the gap associated with the development of preliminary assessments of coastal flood vulnerability for compliance with the EU Directive on the Assessment and Management of Flood Risks (2007/60/EC). In this context, a methodology has been created by taking into account three major parameters; the maximum wave run-up modelled from historical weather observations, the highest tide according to historic time series, and the sea level rise projections due to climate change. A high resolution digital terrain model (DTM) derived from LIDAR data has been used to integrate the estimated flood events in a GIS environment. The flood vulnerability map created shows potential risk areas and can play a crucial role in the coastal zone planning process. The proposed method has the potential to be a powerful tool for policy and decision makers for spatial planning and strategic management.

Keywords: coastal floods, vulnerability mapping, climate change, extreme weather events

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Authors: Hyun-Woo Cho

Abstract:

For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

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Authors: M. Amparo Nunez-Andres, Nieves Lantada

Abstract:

One of the most harmful geological risks is rockfalls. They cause both economic lost, damaged in buildings and infrastructures, and personal ones. Therefore, in order to estimate the risk of the exposed elements, it is necessary to know the mechanism of this kind of events, since the characteristics of the rock walls, to the propagation of fragments generated by the initial detached rock mass. In the framework of the research RockModels project, several inventories of rockfalls were carried out along the northeast of the Spanish peninsula and the Mallorca island. These inventories have general information about the events, although the important fact is that they contained detailed information about fragmentation. Specifically, the IBSD (Insitu Block Size Distribution) is obtained by photogrammetry from drone or TLS (Terrestrial Laser Scanner) and the RBSD (Rock Block Size Distribution) from the volume of the fragment in the deposit measured by hand. In order to share all this information with other scientists, engineers, members of civil protection, and stakeholders, it is necessary a platform accessible from the internet and following interoperable standards. In all the process, open-software have been used: PostGIS 2.1., Geoserver, and OpenLayers library. In the first step, a spatial database was implemented to manage all the information. We have used the data specifications of INSPIRE for natural risks adding specific and detailed data about fragmentation distribution. The next step was to develop a WMS with Geoserver. A previous phase was the creation of several views in PostGIS to show the information at different scales of visualization and with different degrees of detail. In the first view, the sites are identified with a point, and basic information about the rockfall event is facilitated. In the next level of zoom, at medium scale, the convex hull of the rockfall appears with its real shape and the source of the event and fragments are represented by symbols. The queries at this level offer a major detail about the movement. Eventually, the third level shows all elements: deposit, source, and blocks, in their real size, if it is possible, and in their real localization. The last task was the publication of all information in a web mapping site (www.rockdb.upc.edu) with data classified by levels using libraries in JavaScript as OpenLayers.

Keywords: geological risk, web mapping, WMS, rockfalls

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Authors: S. Vaibhav Kant Sahu, Surabhi Bipin Seth

Abstract:

Human well-being has multiple constituents including the basic material for a good life, freedom and choice, health, good social relations, and security. Poverty is also multidimensional and has been defined as the pronounced deprivation of well-being. Dhurwa tribe of Bastar (India) have symbiotic relation with nature, it provisions ecosystem service such as food, fuel and fiber; regulating services such as climate regulation and non-material benefits such as spiritual or aesthetic benefits and they are managing their forest from ages. The demand for ecosystem services is now so great that trade-off among services become rule. Aim of study to explore evidences for linkages between ecosystem services and well-being of indigenous community, how much it helps them in poverty reduction and interaction between them. Objective of study was to find drivers of change and evidence concerning link between ecosystem, human development and sustainability, evidence in decision making does it opt for multi sectoral objectives. Which means human well-being as the central focus for assessment, while recognizing that biodiversity and ecosystems also have intrinsic value. Ecosystem changes that may have little impact on human well-being over days or weeks may have pronounced impacts over years or decades; so assessments needed to be conducted at spatial and temporal scales under social, political, economic scales to have high-resolution data. Researcher used framework developed by Millennium ecosystem assessment; since human action now directly or unknowingly virtually alter ecosystem. Researcher used ethnography study to get primary qualitative data, secondary data collected from panchayat office. The responses were transcribed and translated into English, as interview held in Hindi and local indigenous language. Focus group discussion were held with group of 10 women at Tiriya village. Researcher concluded with well-being is not just gap between ecosystem service supply but also increases vulnerability. Decision can have consequences external to the decision framework these consequences are called externalities because they are not part of the decision-making calculus.

Keywords: Bastar, Dhurwa tribe, ecosystem services, millennium ecosystem assessment, sustainability

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Authors: Hsien-Tsen Wang

Abstract:

Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

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Authors: Tawfig Alghbaili

Abstract:

LP3D Field is located near the center of the Sirt Basin in the Marada Trough approximately 215 km south Marsa Al Braga City. The Marada Trough is bounded on the west by a major fault, which forms the edge of the Beda Platform, while on the east, a bounding fault marks the edge of the Zelten Platform. The main reservoir in the LP3D Field is Upper Paleocene Beda Formation. The Beda Formation is mainly limestone interbedded with shale. The reservoir average thickness is 117.5 feet. To develop a better understanding of the characterization and distribution of the Beda reservoir, quantitative seismic data interpretation has been done, and also, well logs data were analyzed. Six reflectors corresponding to the tops of the Beda, Hagfa Shale, Gir, Kheir Shale, Khalifa Shale, and Zelten Formations were picked and mapped. Special work was done on fault interpretation part because of the complexities of the faults at the structure area. Different attribute analyses were done to build up more understanding of structures lateral extension and to view a clear image of the fault blocks. Time to depth conversion was computed using velocity modeling generated from check shot and sonic data. The simplified stratigraphic cross-section was drawn through the wells A1, A2, A3, and A4-LP3D. The distribution and the thickness variations of the Beda reservoir along the study area had been demonstrating. Petrophysical analysis of wireline logging also was done and Cross plots of some petrophysical parameters are generated to evaluate the lithology of reservoir interval. Structure and Stratigraphic Framework was designed and run to generate different model like faults, facies, and petrophysical models and calculate the reservoir volumetric. This study concluded that the depth structure map of the Beda formation shows the main structure in the area of study, which is north to south faulted anticline. Based on the Beda reservoir models, volumetric for the base case has been calculated and it has STOIIP of 41MMSTB and Recoverable oil of 10MMSTB. Seismic attributes confirm the structure trend and build a better understanding of the fault system in the area.

Keywords: LP3D Field, Beda Formation, reservoir models, Seismic attributes

Procedia PDF Downloads 204