Search results for: spatial rainfall prediction

Authors: Ebru Cubukcu, Gozde Eksioglu Cetintahra, Burcin Hepguzel Hatip, Mert Cubukcu

Abstract:

Obesity and overweight cause serious health problems. Public and private organizations aim to encourage walking in various ways in order to cope with the problem of obesity and overweight. This study aims to understand how the spatial characteristics of urban street pattern, connectivity and complexity influence young people’s choice to walk or not. 185 public university students in Izmir, the third largest city in Turkey, participated in the study. Each participant had worn an accelerometer and a global positioning (GPS) device for a week. The accelerometer device records data on the intensity of the participant’s activity at a specified time interval, and the GPS device on the activities’ locations. Combining the two datasets, activity maps are derived. These maps are then used to differentiate the participants’ walk trips and motor vehicle trips. Given that, the frequency of walk and motor vehicle trips are calculated at the street segment level, and the street segments are then categorized into two as ‘preferred by pedestrians’ and ‘preferred by motor vehicles’. Graph Theory-based accessibility indices are calculated to quantify the spatial characteristics of the streets in the sample. Six different indices are used: (I) edge density, (II) edge sinuosity, (III) eta index, (IV) node density, (V) order of a node, and (VI) beta index. T-tests show that the index values for the ‘preferred by pedestrians’ and ‘preferred by motor vehicles’ are significantly different. The findings indicate that the spatial characteristics of the street network have a measurable effect on young people’s choice to walk or not. Policy implications are discussed. This study is funded by the Scientific and Technological Research Council of Turkey, Project No: 116K358.

Keywords: graph theory, walkability, accessibility, street network

Procedia PDF Downloads 208

Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

Abstract:

In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

Procedia PDF Downloads 378

Authors: Ravi Soni, Irfan Pathan, Manish Pande

Abstract:

The current product development process needs simultaneous consideration of different physics. The performance of the product needs to be considered under both structural and fluid loads. Examples include ducts and valves where structural behavior affects fluid motion and vice versa. Simulation of fluid-structure interaction involves modeling interaction between moving components and the fluid flow. In these scenarios, it is difficult to calculate the damping provided by fluid flow because of dynamic motions of components and the transient nature of the flow. Abaqus Explicit offers general capabilities for modeling fluid-structure interaction with the Coupled Eulerian-Lagrangian (CEL) method. The Coupled Eulerian-Lagrangian technique has been used to simulate fluid spillage through fuel valves during dynamic closure events. The technique to simulate pressure drops across Eulerian domains has been developed using stagnation pressure. Also, the fluid flow is calculated considering material flow through elements at the outlet section of the valves. The methodology has been verified on Eaton products and shows a good correlation with the test results.

Keywords: Coupled Eulerian-Lagrangian Technique, fluid structure interaction, spillage prediction, stagnation pressure

Procedia PDF Downloads 361

Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell

Abstract:

A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.

Keywords: crime, narrative, video, neighborhood

Procedia PDF Downloads 223

Authors: Gashaw Gismu Chakilu

Abstract:

Climate and land cover change are very important issues in terms of global context and their responses to environmental and socio-economic drivers. The dynamic of these two factors is currently affecting the environment in unbalanced way including watershed hydrology. In this paper individual and combined impacts of climate change and land use land cover change on hydrological processes were evaluated through applying the model Soil and Water Assessment Tool (SWAT) in Gumara watershed, Upper Blue Nile basin Ethiopia. The regional climate; temperature and rainfall data of the past 40 years in the study area were prepared and changes were detected by using trend analysis applying Mann-Kendall trend test. The land use land cover data were obtained from land sat image and processed by ERDAS IMAGIN 2010 software. Three land use land cover data; 1973, 1986, and 2013 were prepared and these data were used for base line, model calibration and change study respectively. The effects of these changes on high flow and low flow of the catchment have also been evaluated separately. The high flow of the catchment for these two decades was analyzed by using Annual Maximum (AM) model and the low flow was evaluated by seven day sustained low flow model. Both temperature and rainfall showed increasing trend; and then the extent of changes were evaluated in terms of monthly bases by using two decadal time periods; 1973-1982 was taken as baseline and 2004-2013 was used as change study. The efficiency of the model was determined by Nash-Sutcliffe (NS) and Relative Volume error (RVe) and their values were 0.65 and 0.032 for calibration and 0.62 and 0.0051 for validation respectively. The impact of climate change was higher than that of land use land cover change on stream flow of the catchment; the flow has been increasing by 16.86% and 7.25% due to climate and LULC change respectively, and the combined change effect accounted 22.13% flow increment. The overall results of the study indicated that Climate change is more responsible for high flow than low flow; and reversely the land use land cover change showed more significant effect on low flow than high flow of the catchment. From the result we conclude that the hydrology of the catchment has been altered because of changes of climate and land cover of the study area.

Keywords: climate, LULC, SWAT, Ethiopia

Procedia PDF Downloads 367

Authors: M. N. A. Azman, M. S. S. Ahamad

Abstract:

The Construction Industry Development Board of Malaysia has been actively promoting the use of precast manufacturing in the local construction industry over the last decade. In an era of rapid technological changes, precast manufacturing significantly contributes to improving construction activities and ensuring sustainable economic growth. Current studies on the location decision of precast manufacturing plants aimed to enhanced local economic development are scarce. To address this gap, the present research establishes a new set of spatial criteria, such as attribute maps and preference weights, derived from a survey of local industry decision makers. These data represent the input parameters for the MCE-GIS site selection model, for which the weighted linear combination method is used. Verification tests on the model were conducted to determine the potential precast manufacturing sites in the state of Penang, Malaysia. The tests yield a predicted area of 12.87 acres located within a designated industrial zone. Although, the model is developed specifically for precast manufacturing plant but nevertheless it can be employed to other types of industries by following the methodology and guidelines proposed in the present research.

Keywords: geographical information system, multi criteria evaluation, industrialised building system, civil engineering

Procedia PDF Downloads 271

Authors: Vedat Uyak

Abstract:

Seasonal variations of trihalomethanes (THMs) and haloacetic acids (HAAs) concentrations were investigated within three distribution systems of a coastal city of Istanbul, Turkey. Moreover, total trihalomethanes and other organics concentration were also analyzed. The investigation was based on an intensive 16 month (2009-2010) sampling program, undertaken during the spring, summer, fall and winter seasons. Four THM (chloroform, dichlorobromomethane, chlorodibromomethane, bromoform), and nine HAA (the most commonly occurring one being dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA); other compounds are monochloroacetic acid (MCAA), monobromoacetic acid (MBAA), dibromoacetic acid (DBAA), tribromoacetic acid (TBAA), bromochloroacetic acid (BCAA), bromodichloroacetic acid (BDCAA) and chlorodibromoacetic acid (CDBAA)) species and other water quality and operational parameters were monitored at points along the distribution system between the treatment plant and the system’s extremity. The effects of coastal water sources, seasonal variation and spatial variation were examined. The results showed that THMs and HAAs concentrations vary significantly between treated waters and water at the distribution networks. When water temperature exceeds 26°C in summer, the THMs and HAAs levels are 0.8 – 1.1, and 0.4 – 0.9 times higher than treated water, respectively. While when water temperature is below 12°C in the winter, the measured THMs and HAAs concentrations at the system’s extremity were very rarely higher than 100 μg/L, and 60 μg/L, respectively. The highest THM concentrations occurred in the Buyukcekmece distribution system, with an average total HAA concentration of 92 μg/L. Moreover, the lowest THM levels were observed in the Omerli distribution network, with a mean concentration of 7 μg/L. For HAA levels, the maximum concentrations again were observed in the Buyukcekmece distribution system, with an average total HAA concentration of 57 μg/l. High spatial and seasonal variation of disinfection by-products in the drinking water of Istanbul was attributed of illegal wastewater discharges to water supplies of Istanbul city.

Keywords: disinfection byproducts, drinking water, trihalomethanes, haloacetic acids, seasonal variation

Procedia PDF Downloads 135

Authors: I. L. Kim, J. Y. Lee, A. K. Tekile

Abstract:

In consequence of the very high urbanization rate of Korea, the number of traffic noise damages in areas congested with population and facilities is steadily increasing. The current environmental noise levels data in major cities of the country show that the noise levels exceed the standards set for both day and night times. This research was about comparative analysis in search for optimal soundproof panel shape and design factor that can minimize sound reflection noise. In addition to the normal flat-type panel shape, the reflection noise reduction of swelling-type, combined swelling and curved-type, and screen-type were evaluated. The noise source model Nord 2000, which often provides abundant information compared to models for the similar purpose, was used in the study to determine the overall noise level. Based on vehicle categorization in Korea, the noise levels for varying frequency from different heights of the sound source (directivity heights of Harmonize model) have been calculated for simulation. Each simulation has been made using the ray-tracing method. The noise level has also been calculated using the noise prediction program called SoundPlan 7.2, for comparison. The noise level prediction was made at 15m (R1), 30 m (R2) and at middle of the road, 2m (R3) receiving the point. By designing the noise barriers by shape and running the prediction program by inserting the noise source on the 2nd lane to the noise barrier side, among the 6 lanes considered, the reflection noise slightly decreased or increased in all noise barriers. At R1, especially in the cases of the screen-type noise barriers, there was no reduction effect predicted in all conditions. However, the swelling-type showed a decrease of 0.7~1.2 dB at R1, performing the best reduction effect among the tested noise barriers. Compared to other forms of noise barriers, the swelling-type was thought to be the most suitable for reducing the reflection noise; however, since a slight increase was predicted at R2, further research based on a more sophisticated categorization of related design factors is necessary. Moreover, as swellings are difficult to produce and the size of the modules are smaller than other panels, it is challenging to install swelling-type noise barriers. If these problems are solved, its applicable region will not be limited to other types of noise barriers. Hence, when a swelling-type noise barrier is installed at a downtown region where the amount of traffic is increasing every day, it will both secure visibility through the transparent walls and diminish any noise pollution due to the reflection. Moreover, when decorated with shapes and design, noise barriers will achieve a visual attraction than a flat-type one and thus will alleviate any psychological hardships related to noise, other than the unique physical soundproofing functions of the soundproof panels.

Keywords: reflection noise, shaped noise barriers, sound proof panel, traffic noise

Procedia PDF Downloads 497

Authors: Anne C. Richer-De-Forges, Dominique Arrouays, Songchao Chen, Mercedes Roman Dobarco

Abstract:

Most of the digital soil mapping (DSM) products rely on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs. However, many other observations (often qualitative, nominal, or ordinal) could be used as proxies of lab measurements or as input data for ML of PTF predictions. DSM and ML are briefly described with some examples taken from the literature. Then, we explore the potential of an ordinal qualitative variable, i.e., the hand-feel soil texture (HFST) estimating the mineral particle distribution (PSD): % of clay (0-2µm), silt (2-50µm) and sand (50-2000µm) in 15 classes. The PSD can also be measured by lab measurements (LAST) to determine the exact proportion of these particle-sizes. However, due to cost constraints, HFST are much more numerous and spatially dense than LAST. Soil texture (ST) is a very important soil parameter to map as it is controlling many of the soil properties and functions. Therefore, comes an essential question: is it possible to use HFST as a proxy of LAST for calibration and/or validation of DSM predictions of ST? To answer this question, the first step is to compare HFST with LAST on a representative set where both information are available. This comparison was made on ca 17,400 samples representative of a French region (34,000 km2). The accuracy of HFST was assessed, and each HFST class was characterized by a probability distribution function (PDF) of its LAST values. This enables to randomly replace HFST observations by LAST values while respecting the PDF previously calculated and results in a very large increase of observations available for the calibration or validation of PTF and ML predictions. Some preliminary results are shown. First, the comparison between HFST classes and LAST analyses showed that accuracies could be considered very good when compared to other studies. The causes of some inconsistencies were explored and most of them were well explained by other soil characteristics. Then we show some examples applying these relationships and the increase of data to several issues related to DSM. The first issue is: do the PDF functions that were established enable to use HSFT class observations to improve the LAST soil texture prediction? For this objective, we replaced all HFST for topsoil by values from the PDF 100 time replicates). Results were promising for the PTF we tested (a PTF predicting soil water holding capacity). For the question related to the ML prediction of LAST soil texture on the region, we did the same kind of replacement, but we implemented a 10-fold cross-validation using points where we had LAST values. We obtained only preliminary results but they were rather promising. Then we show another example illustrating the potential of using HFST as validation data. As in numerous countries, the HFST observations are very numerous; these promising results pave the way to an important improvement of DSM products in all the countries of the world.

Keywords: digital soil mapping, improvement of digital soil mapping predictions, potential of using hand-feel soil texture, soil texture prediction

Procedia PDF Downloads 207

Authors: Mariya Dayana, Budhmal Jain

Abstract:

Kannur International Airport Ltd. (KIAL) is a new Greenfield airport project with airside development on an undulating terrain with an average height of 90m above Mean Sea Level (MSL) and a maximum height of 142m. To accommodate the desired Runway length and Runway End Safety Area (RESA) at both the ends along the proposed alignment, it resulted in 45.5 million cubic meters in cutting and filling. The insufficient availability of land for the construction of free slope embankment at RESA 07 end resulted in the design and construction of Reinforced Soil Slope (RSS) with a maximum slope of 65 degrees. An embankment fill of average 70m height with steep slopes located in high rainfall area is a unique feature of this project. The design and construction was challenging being asymmetrical with curves and bends. The fill was reinforced with high strength Uniaxial geogrids laid perpendicular to the slope. Weld mesh wrapped with coir mat acted as the facia units to protect it against surface failure. Face anchorage were also provided by wrapping the geogrids along the facia units where the slope angle was steeper than 45 degrees. Considering high rainfall received on this table top airport site, extensive drainage system was designed for the high embankment fill. Gabion wall up to 10m height were also designed and constructed along the boundary to accommodate the toe of the RSS fill beside the jeepable track at the base level. The design of RSS fill was done using ReSSA software and verified in PLAXIS 2D modeling. Both slip surface failure and wedge failure cases were considered in static and seismic analysis for local and global failure cases. The site won excavated laterite soil was used as the fill material for the construction. Extensive field and laboratory tests were conducted during the construction of RSS system for quality assurance. This paper represents a case study detailing the design and construction of a very high embankment using geosynthetics for the provision of Runway length and RESA area.

Keywords: airport, embankment, gabion, high strength uniaxial geogrid, kial, laterite soil, plaxis 2d

Procedia PDF Downloads 146

Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

Abstract:

Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

Procedia PDF Downloads 217

Authors: Yudo Prasetyo, Hana Sugiastu Firdaus, Diyanah Diyanah

Abstract:

The phenomenon of the lack of clean water supply in several big cities in Indonesia is a major problem in the development of urban areas. Moreover, in the city of Semarang, the population density and growth of physical development is very high. Continuous and large amounts of underground water (aquifer) exposure can result in a drastically aquifer supply declining in year by year. Especially, the intensity of aquifer use in the fulfilment of household needs and industrial activities. This is worsening by the land subsidence phenomenon in some areas in the Semarang city. Therefore, special research is needed to know the spatial correlation of the impact of decreasing aquifer capacity on the land subsidence phenomenon. This is necessary to give approve that the occurrence of land subsidence can be caused by loss of balance of pressure on below the land surface. One method to observe the correlation pattern between the two phenomena is the application of remote sensing technology based on radar and optical satellites. Implementation of Differential Interferometric Synthetic Aperture Radar (DINSAR) or Small Baseline Area Subset (SBAS) method in SENTINEL-1A satellite image acquisition in 2014-2017 period will give a proper pattern of land subsidence. These results will be spatially correlated with the aquifer-declining pattern in the same time period. Utilization of survey results to 8 monitoring wells with depth in above 100 m to observe the multi-temporal pattern of aquifer change capacity. In addition, the pattern of aquifer capacity will be validated with 2 underground water cavity maps from observation of ministries of energy and natural resources (ESDM) in Semarang city. Spatial correlation studies will be conducted on the pattern of land subsidence and aquifer capacity using overlapping and statistical methods. The results of this correlation will show how big the correlation of decrease in underground water capacity in influencing the distribution and intensity of land subsidence in Semarang city. In addition, the results of this study will also be analyzed based on geological aspects related to hydrogeological parameters, soil types, aquifer species and geological structures. The results of this study will be a correlation map of the aquifer capacity on the decrease in the face of the land in the city of Semarang within the period 2014-2017. So hopefully the results can help the authorities in spatial planning and the city of Semarang in the future.

Keywords: aquifer, differential interferometric synthetic aperture radar (DINSAR), land subsidence, small baseline area subset (SBAS)

Procedia PDF Downloads 168

Authors: F. Saleh, F. Lyall, A. Abdulsid, L. Marks

Abstract:

Background: Labour in human is a complex biological process that involves interactions of neurological, hormonal and inflammatory pathways, with the placenta being a key regulator of these pathways. It is known that uterine contractions and labour pain cause physiological changes in gene expression in maternal and fetal blood, and in placenta during labour. Oxidative and inflammatory stress pathways are implicated in labour and they may cause alteration of placental gene expression. Additionally, in placental tissues, labour increases the expression of genes involved in placental oxidative stress, inflammatory cytokines, angiogenic regulators and apoptosis. Recently, Hydrogen Sulphide (H2S) has been considered as an endogenous gaseous mediator which promotes vasodilation and exhibits cytoprotective anti-inflammatory properties. The endogenous H2S is synthesised predominantly by two enzymes: cystathionine β-synthase (CBS) and cystathionine γ-lyase (CSE). As the H2S pathway has anti-oxidative and anti-inflammatory characteristics thus, we hypothesised that the expression of CBS and CSE in placental tissues would alter during labour. Methods: CBS and CSE expressions were examined in placentas using western blotting and RT-PCR in inner, middle and outer placental zones in placentas obtained from healthy non labouring women who delivered by caesarian section. These were compared with the equivalent zone of placentas obtained from women who had uncomplicated labour and delivered vaginally. Results: No differences in CBS and CSE mRNA or protein levels were found between the different sites within placentas in either the labour or non-labour group. There were no significant differences in either CBS or CSE expression between the two groups at the inner site and middle site. However, at the outer site there was a highly significant decrease in CBS protein expression in the labour group when compared to the non-labour group (p = 0.002). Conclusion: To the best of author’s knowledge, this is the first report to suggest that, CBS is expressed in a spatial manner within the human placenta. Further work is needed to clarify the precise function and mechanism of this spatial regulation although it is likely that inflammatory pathways regulation is a complex process in which this plays a role.

Keywords: anti-inflammatory, hydrogen sulphide, labour, oxidative stress

Procedia PDF Downloads 232

Authors: Qin Xia

Abstract:

’National New District’ as a regional overall promotion of strategic thinking has become increasingly mature, but its spatial expansion is still chaotic and disorderly, so it is urgent to summarize the complex and unique driving mechanism contained in its spatial expansion to formulate sustainable urban expansion plan. Under the understanding of the general laws of the driving mechanism of China's space expansion, it is found that the existing research on the driving mechanism of the space expansion of national new districts is insufficient. The research area focuses on the research of the driving mechanism of the space expansion of a single new area. In terms of research methods, qualitative description is the main focus. In terms of research content, it is limited to the expansion speed, intensity, and area of the new district itself and does not involve the expansion and utilization efficiency of space and the spillover efficiency to surrounding cities. The specific connotations of social, economic, political, and geographical categories are not thoroughly explored. It is often a general explanation that a certain factor has promoted it. The logic is not rigorous and convincing, and the description is relatively static, with different time and space. There is less literature on scale interaction. Through the reflection on the key and difficult points of the drive mechanism of the space expansion of the national new area, it is clear that the existing research on the drive mechanism of the space expansion of the national new area should be continued to drive the sustainable expansion of space.

Keywords: national new district, space expansion, driving mechanism, existing research

Procedia PDF Downloads 156

Authors: Deniz Peksen

Abstract:

This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

Procedia PDF Downloads 65

Authors: S. Pramanik

Abstract:

Since the early ages, the Hindu temples have been interpreted through various Vedic philosophies. These temples are visited by pilgrims which demonstrate the rituals and religious belief of communities, reflecting a variety of actions and behaviors. Darsana— a direct seeing, is a part of the pilgrimage activity. During the process of Darsana, a devotee is prepared for entry in the temple to realize the cognizing Truth culminating in visualizing the idol of God, placed at the Garbhagriha (sanctum sanctorum). For this, the pilgrim must pass through a sequential arrangement of spaces. During the process of progress, the pilgrims visualize the spaces differently from various points of views. The viewpoints create a variety of spatial patterns in the minds of pilgrims coherent to the Hindu philosophies. The space organization and its order are perceived by various techniques of spatial analysis. A temple, as examples of Kalinga stylistic variations, has been chosen for the study. This paper intends to demonstrate some visual patterns generated during the process of Darsana (visibility) and its accessibility by Point Isovist Studies and Visibility Graph Analysis from the entrance (Simha Dwara) to The Sanctum sanctorum (Garbhagriha).

Keywords: Hindu temple architecture, point isovist, space syntax analysis, visibility graph analysis

Procedia PDF Downloads 109

Authors: Imran Aziz Tunio

Abstract:

Islamkot is an underdeveloped sub-district (Taluka) in the Tharparkar district Sindh province of Pakistan located between latitude 24°25'19.79"N to 24°47'59.92"N and longitude 70° 1'13.95"E to 70°32'15.11"E. The Islamkot has an arid desert climate and the region is generally devoid of perennial rivers, canals, and streams. It is highly dependent on rainfall which is not considered a reliable surface water source and groundwater is the only key source of water for many centuries. To assess groundwater’s potential, an electrical resistivity survey (ERS) was conducted in Islamkot Taluka. Groundwater investigations for 128 Vertical Electrical Sounding (VES) were collected to determine the groundwater potential and obtain qualitatively and quantitatively layered resistivity parameters. The PASI Model 16 GL-N Resistivity Meter was used by employing a Schlumberger electrode configuration, with half current electrode spacing (AB/2) ranging from 1.5 to 100 m and the potential electrode spacing (MN/2) from 0.5 to 10 m. The data was acquired with a maximum current electrode spacing of 200 m. The data processing for the delineation of dune sand aquifers involved the technique of data inversion, and the interpretation of the inversion results was aided by the use of forward modeling. The measured geo-electrical parameters were examined by Interpex IX1D software, and apparent resistivity curves and synthetic model layered parameters were mapped in the ArcGIS environment using the inverse Distance Weighting (IDW) interpolation technique. Qualitative interpretation of vertical electrical sounding (VES) data shows the number of geo-electrical layers in the area varies from three to four with different resistivity values detected. Out of 128 VES model curves, 42 nos. are 3 layered, and 86 nos. are 4 layered. The resistivity of the first subsurface layers (Loose surface sand) varied from 16.13 Ωm to 3353.3 Ωm and thickness varied from 0.046 m to 17.52m. The resistivity of the second subsurface layer (Semi-consolidated sand) varied from 1.10 Ωm to 7442.8 Ωm and thickness varied from 0.30 m to 56.27 m. The resistivity of the third subsurface layer (Consolidated sand) varied from 0.00001 Ωm to 3190.8 Ωm and thickness varied from 3.26 m to 86.66 m. The resistivity of the fourth subsurface layer (Silt and Clay) varied from 0.0013 Ωm to 16264 Ωm and thickness varied from 13.50 m to 87.68 m. The Dar Zarrouk parameters, i.e. longitudinal unit conductance S is from 0.00024 to 19.91 mho; transverse unit resistance T from 7.34 to 40080.63 Ωm2; longitudinal resistance RS is from 1.22 to 3137.10 Ωm and transverse resistivity RT from 5.84 to 3138.54 Ωm. ERS data and Dar Zarrouk parameters were mapped which revealed that the study area has groundwater potential in the subsurface.

Keywords: electrical resistivity survey, GIS & RS, groundwater potential, environmental assessment, VES

Procedia PDF Downloads 79

Authors: Chuan-Ming Tung, Jin-Cheng Fu, Chia-En Feng

Abstract:

In recent years, the rapid development of urban land in Taiwan has led to the constant increase of the areas of impervious surface, which has increased the risk of waterlogging during heavy rainfall. Therefore, in recent years, promoting runoff allocation responsibilities has often been used as a means of reducing regional flooding. In this study, the single catchment area covering both urban and rural land as the study area is discussed. Based on Storm Water Management Model, urban and rural land in a single catchment area was explored to develop the runoff allocation responsibilities according to their respective control regulation on land use. The impacts of runoff increment and reduction in sub-catchment area were studied to understand the impact of highly developed urban land on the reduction of flood risk of rural land at the back end. The results showed that the rainfall with 1 hour short delay of 2 years, 5 years, 10 years, and 25 years return period. If the study area was fully developed, the peak discharge at the outlet would increase by 24.46% -22.97% without runoff allocation responsibilities. The front-end urban land would increase runoff from back-end of rural land by 76.19% -46.51%. However, if runoff allocation responsibilities were carried out in the study area, the peak discharge could be reduced by 58.38-63.08%, which could make the front-end to reduce 54.05% -23.81% of the peak flow to the back-end. In addition, the researchers found that if it was seen from the perspective of runoff allocation responsibilities of per unit area, the residential area of urban land would benefit from the relevant laws and regulations of the urban system, which would have a better effect of reducing flood than the residential land in rural land. For rural land, the development scale of residential land was generally small, which made the effect of flood reduction better than that of industrial land. Agricultural land requires a large area of land, resulting in the lowest share of the flow per unit area. From the point of the planners, this study suggests that for the rural land around the city, its responsibility should be assigned to share the runoff. And setting up rain water storage facilities in the same way as urban land, can also take stock of agricultural land resources to increase the ridge of field for flood storage, in order to improve regional disaster reduction capacity and resilience.

Keywords: runoff allocation responsibilities, land use, flood mitigation, SWMM

Procedia PDF Downloads 86

Authors: T. J. B. van Niekerk, J. Viviers, E. J. Cilliers

Abstract:

Substantial efforts were made in South Africa, stemming from a historic political change in 1994, to remedy the inequality and injustice, resulting from a dispensation where spatial patterns were largely based on racial segregation. Spatially distorted patterns predominantly originated from colonialism in the beginning of the twentieth century, ensuing a physical imprint on South African cities relating to architecture, urban layout and planning, frequently reflecting European norms and standards. As a consequence of physical and land use barriers, and well-established dual cities, attempts to address spatial injustices, apart from limited occurrences in metropolitan areas, gravely failed. Interception of incessant segregated growth, combined with urban sprawl is becoming increasingly evident. Intervention is a prerequisite to duly address the impact of colonial planning and its legacy still prevalent in most urban areas. During 1998, the National Department of Transport prepared the “Moving South Africa” strategy; presenting the Corridor Densification Option Model for the first time, as it was deemed more fitting to the existing South African urban tenure patterns than more familiar planning approaches. Urban planners are progressively contemplating the Corridor Densification Option Model and its attributes, besides its transportation emphasis, as an alternative approach to address spatial imbalances and to attain the physical integration of contemporary urban forms. In attaining a clearer understanding of the Corridor Densification Option Model, its rationale was analysed in greater detail. This research further investigated the provisional applications of the model in spatially segregated cities and illustrated that viable options are present to effectively employ it. Research revealed that the application of the model will, however, be dependent on the occurrence of specific characteristics in spatially segregated cities to warrant augmentation thereof.

Keywords: corridor densification option model, spatially segregated settlements, integration, urban restructuring

Procedia PDF Downloads 202

Authors: Salamatu Shaibu, Jan Hernning Sommer

Abstract:

Integrating biodiversity conservation practices in mining landscapes ensures the continual provision of various ecosystem services to the dependent communities whilst serving as ecological insurance for corporate mining when purchasing reclamation security bonds. Climate hazards such as long dry seasons, erratic rainfall patterns, and extreme weather events contribute to biodiversity loss in addition to the impact due to mining. Both corporate mining and mine-fringe communities perceive the effect of climate on biodiversity from the context of the benefits they accrue, which motivate their conservation practices. In this study, pragmatic approaches including semi-structured interviews, field visual observation, and review were used to collect data on corporate mining employees and households of fringing communities in the southwestern mining hub. The perceived changes in the local climatic conditions and the consequences on environmental management practices that promote biodiversity conservation were examined. Using a thematic content analysis tool, the result shows that best practices such as concurrent land rehabilitation, reclamation ponds, artificial wetlands, land clearance, and topsoil management are directly affected by prolonging long dry seasons and erratic rainfall patterns. Excessive dust and noise generation directly affect both floral and faunal diversity coupled with excessive fire outbreaks in rehabilitated lands and nearby forest reserves. Proposed adaptive measures include engaging national conservation authorities to promote reforestation projects around forest reserves. National government to desist from using permit for mining concessions in forest reserves, engaging local communities through educational campaigns to control forest encroachment and burning, promoting community-based resource management to promote community ownership, and provision of stricter environmental legislation to compel corporate, artisanal, and small scale mining companies to promote biodiversity conservation.

Keywords: biodiversity conservation, climate hazards, corporate mining, mining landscapes

Procedia PDF Downloads 199

Authors: Zenebu Adere Tola

Abstract:

Informal settlements behave dynamically over space and time and the number of people living in such housing areas is growing worldwide. In the cities of developing countries especially in sub-Saharan Africa, poverty, unemployment rate, poor living condition, lack transparency and accountability, lack of good governance are the major factors to contribute for the people to hold land informally and built houses for residential or other purposes. In most of Ethiopian cities informal settlement is highly seen in peripheral areas this is because people can easily to hold land for housing from local farmers, brokers, speculators without permission from concerning bodies. In Adama informal settlement has created risky living conditions and led to environmental problems in natural areas the main reason for this was the lack of sufficient knowledge about informal settlement development. On the other side there is a strong need to transform informal into formal settlements and to gain more control about the actual spatial development of informal settlements. In another hand to tackle the issue it is at least very important to understand the scale of the problem. To understand the scale of the problem it is important to use up-to-date technology. For this specific problem, it is good to use high-resolution imagery to detect informal settlement in Adama city. The main objective of this study is to assess the spatiotemporal dynamics and environmental impacts of informal settlement using OBIA. Specifically, the objective of this study is to; identify informal settlement in the study area, determine the change in the extent and pattern of informal settlement and to assess the environmental and social impacts of informal settlement in the study area. The methods to be used to detect the informal settlement is object-oriented image analysis. Consequently, reliable procedures for detecting the spatial behavior of informal settlements are required in order to react at an early stage to changing housing situations. Thus, obtaining spatial information about informal settlement areas which is up to date is vital for any actions of enhancement in terms of urban or regional planning. Using data for this study aerial photography for growth and change of informal settlements in Adama city. Software ECognition software for classy to built-up and non-built areas. Thus, obtaining spatial information about informal settlement areas which is up to date is vital for any actions of enhancement in terms of urban or regional planning.

Keywords: informal settlement, change detection, environmental impact, object based analysis

Procedia PDF Downloads 57

Authors: Laetitia Lemiere, Marie Gosme, Gerard Subsol, Marc Jaeger

Abstract:

Agroforestry is recognized as a way of developing sustainable and resilient agriculture that can fight against climate change. However, the number of species combinations, spatial configurations, and management options for trees and crops is vast. These choices must be adapted to the pedoclimatic and socio-economic contexts and to the objectives of the farmer, who therefore needs support in designing his system. Participative design workshops are a good way to integrate the knowledge of several experts in order to design such complex systems. The design of agroforestry systems should take into account both spatial aspects (e.g., spacing of trees within the lines and between lines, tree line orientation, tree-crop distance, species spatial patterns) and temporal aspects (e.g., crop rotations, tree thinning and pruning, tree planting in the case of successional agroforestry). Furthermore, the interactions between trees and crops evolve as the trees grow. However, agroforestry design workshops generally emphasize the spatial aspect only through the use of static tokens to represent the different species when designing the spatial configuration of the system. Augmented reality (AR) may overcome this limitation, allowing to visualize dynamic representations of trees and crops, and also their interactions, while at the same time retaining the possibility to physically interact with the system being designed (i.e., move trees, add or remove species, etc.). We propose an ergonomic digital solution capable of assisting a group of agroforestry experts to design an agroforestry system and to represent it. We investigated the use of web-based marker-based AR that does not require specific hardware and does not require specific installation so that all users could use their own smartphones right out of the pocket. We developed a prototype mobilizing the AR.js, ArToolKit.js, and Three.js open source libraries. In our implementation, we gradually build a virtual agroforestry system pattern scene from the users' interactions. A specific set of markers initialize the scene properties, and the various plant species are added and located during the workshop design session. The full virtual scene, including the trees positions with their neighborhood, are saved for further uses, such as virtual, augmented instantiation in the farmer fields. The number of tree species available in the application is gradually increasing; we mobilize 3D digital models for walnut, poplar, wild cherry, and other popular species used in agroforestry systems. The prototype allows shadow computations and the representation of trees at various growth stages, as well as different tree generations, and is thus able to visualize the dynamics of the system over time. Future work will focus on i) the design of complex patterns mobilizing several tree/shrub organizations, not restricted to lines; ii) the design of interfaces related to cultural practices, such as clearing or pruning; iii) the representation of tree-crop interactions. Beside tree shade (light competition), our objective is to represent also below-ground competitions (water, nitrogen) or other variables of interest for the design of agroforestry systems (e.g., predicted crop yield).

Keywords: agroforestry system design, augmented reality, marker-based AR, participative design, web-based AR

Procedia PDF Downloads 155

Authors: Al-Juhaishi Mohammed, Mikael Motelica-Heino, Fabrice Muller, Audrey Guirimand-Dufour, Christian Défarge

Abstract:

This study aims at improving the urban hydrological cycle of the Orléans agglomeration (France) and understanding the relationship between physical and chemical parameters of urban surface runoff and the hydrological conditions. In particular water quality parameters such as pH, conductivity, total dissolved solids, major dissolved cations and anions, and chemical and biological oxygen demands were monitored for three types of urban water discharges (wastewater treatment plant output (WWTP), storm overflow and stormwater outfall) under two hydrologic scenarii (dry and wet weather). The first results were obtained over a period of five months.Each investigated (Ormes and l’Egoutier) outfall represents an urban runoff source that receives water from runoff roads, gutters, the irrigation of gardens and other sources of flow over the Earth’s surface that drains in its catchments and carries it to the Loire River. In wet weather conditions there is rain water runoff and an additional input from the roof gutters that have entered the stormwater system during rainfall. For the comparison the results La Chilesse is a storm overflow that was selected in our study as a potential source of waste water which is located before the (WWTP).The comparison of the physical-chemical parameters (total dissolved solids, turbidity, pH, conductivity, dissolved organic carbon (DOC), concentration of major cations and anions) together with the chemical oxygen demand (COD) and biological oxygen demand (BOD) helped to characterize sources of runoff waters in the different watersheds. It also helped to highlight the infiltration of wastewater in some stormwater systems that reject directly in the Loire River. The values of the conductivity measured in the outflow of Ormes were always higher than those measured in the other two outlets. The results showed a temporal variation for the Ormes outfall of conductivity from 1465 µS cm-1 in the dry weather flow to 650 µS cm-1 in the wet weather flow and also a spatial variation in the wet weather flow from 650 µS cm-1 in the Ormes outfall to 281 μS cm-1 in L’Egouttier outfall. The ultimate BOD (BOD28) showed a significant decrease in La Corne outfall from 210 mg L-1 in the wet weather flow to 75 mg L-1 in the dry weather flow because of the nutrient load that was transported by the runoff.

Keywords: BOD, COD, the Loire River, urban hydrology, urban dry and wet weather discharges, macronutrients

Procedia PDF Downloads 255

Authors: Meng-Cong Zheng

Abstract:

When the public space is in an emergency, how to quickly establish spatial cognition and emergency shelter in the closed underground space is the urgent task. This study takes Taipei Station as the research base and aims to apply the use of Internet of things (IoT) application for underground evacuation mobility design. The first experiment identified passengers' evacuation behaviors and spatial cognition in underground spaces by wayfinding tasks and thinking aloud, then defined the design conditions of User Interface (UI) and proposed the UI design.  The second experiment evaluated the UI design based on passengers' evacuation behaviors by wayfinding tasks and think aloud again as same as the first experiment. The first experiment found that the design conditions that the subjects were most concerned about were "map" and hoping to learn the relative position of themselves with other landmarks by the map and watch the overall route. "Position" needs to be accurately labeled to determine the location in underground space. Each step of the escape instructions should be presented clearly in "navigation bar." The "message bar" should be informed of the next or final target exit. In the second experiment with the UI design, we found that the "spatial map" distinguishing between walking and non-walking areas with shades of color is useful. The addition of 2.5D maps of the UI design increased the user's perception of space. Amending the color of the corner diagram in the "escape route" also reduces the confusion between the symbol and other diagrams. The larger volume of toilets and elevators can be a judgment of users' relative location in "Hardware facilities." Fire extinguisher icon should be highlighted. "Fire point tips" of the UI design indicated fire with a graphical fireball can convey precise information to the escaped person. "Fire point tips" of the UI design indicated fire with a graphical fireball can convey precise information to the escaped person. However, "Compass and return to present location" are less used in underground space.

Keywords: evacuation behaviors, IoT application, map UI design, underground station

Procedia PDF Downloads 184

Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

Abstract:

To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

Procedia PDF Downloads 122

Authors: Priyadarsini Samal, Rajesh Singla

Abstract:

Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

Procedia PDF Downloads 172

Authors: Samaila Muazu Bawa

Abstract:

Hydration process, crack potential and setting time of concrete grade C30, C40 and C50 were separately monitored using non-contact electrical resistivity apparatus, a plastic ring mould and penetration resistance method respectively. The results show highest resistivity of C30 at the beginning until reaching the acceleration point when C50 accelerated and overtaken the others, and this period corresponds to its final setting time range, from resistivity derivative curve, hydration process can be divided into dissolution, induction, acceleration and deceleration periods, restrained shrinkage crack and setting time tests demonstrated the earliest cracking and setting time of C50, therefore, this method conveniently and rapidly determines the concrete’s crack potential. The highest inflection time (ti), the final setting time (tf) were obtained and used with crack time in coming up with mathematical models for the prediction of concrete’s cracking age for the range being considered. Finally, ANSYS numerical simulations supports the experimental findings in terms of the earliest crack age of C50 and the crack location that, highest stress concentration is always beneath the artificially introduced expansion joint of C50.

Keywords: concrete hydration, electrical resistivity, restrained shrinkage crack, ANSYS simulation

Procedia PDF Downloads 225

Authors: Sezen Aslan, N. Aydan Sat

Abstract:

The society of 21st century constantly faces with complex otherness that emerges in various forms and justifications. Otherness caused by class, race or ethnicity inevitably reflects to urban areas, and in this way, cities are diversified into totally self-centered and closed-off urban enclaves. One of the most important dynamics that creates otherness in contemporary society is migration. Immigration on an international scale is one of the most important events that have reshaped the world, and the number of immigrants in the world is increasing day by day. Forced migration and refugee statements constitute the major part of countries' immigration policies and practices. Domestic problems such as racism, violence, war, censorship and silencing, attitudes contrary to human rights, different cultural or religious identities cause populations to migrate. Immigration is one of the most important reasons for the formation of urban enclaves within cities. Turkey, which was used to face a higher rate of outward migration, has begun to host immigrant groups from foreign countries. 1980s is the breaking point about the issue as a result of internal disturbances in the Middle East. After Iranian, Iraqi and Afghan immigrants, Turkey faces the largest external migration in its story with Syrian population. Turkey has been hosting approximate three million Syrian people after Syrian Civil War which started in 2011. 92% of Syrian refugees are currently living in different urban areas in Turkey instead of camps. Syrian refugees are experiencing a spontaneous spatiality due to the lack of specific settlement and housing policies of the country. This spontaneity is one of the most important factors in the creation of urban enclaves. From this point of view, the aim of this study is to clarify processes that lead the creation of urban enclaves and to explain socio-spatial effects of these urban enclaves to the other parts of the cities. Ankara, which is one of the most registered Syrian hosting Province in Turkey, is selected as a case study area. About 55% of the total Syrian population lives in the Altındağ district in Ankara. They settled specifically in two neighborhoods in Altındağ district, named as Önder and Ulubey. These neighborhoods are old slum areas, and they were evacuated due to urban renewal on the same dates with the migration of the Syrians. Before demolition of these old slums, Syrians are settled into them as tenants. In the first part of the study, a brief explanation of the concept of urban enclave, its occurrence parameters and possible socio-spatial threats, examples from previous immigrant urban enclaves caused internal migration will be given. Emergence of slums, planning history and social processes in the case study area will be described in the second part of the study. The third part will be focused on the Syrian refugees and their socio-spatial relationship in the case study area and in-depth interviews with refugees and spatial analysis will be realized. Suggestions for the future of the case study area and recommendations to prevent immigrant groups from social and spatial exclusion will be discussed in the conclusion part of the study.

Keywords: migration, immigration, Syrian refugees, urban enclaves, Ankara

Procedia PDF Downloads 192

Authors: Kazi Md. Shifun Newaz, S. Miaji, Shahnewaz Hazanat-E-Rabbi

Abstract:

In this study, the kernel density estimation tool has been used to identify most crash prone locations in a national highway of Bangladesh. Like other developing countries, in Bangladesh road traffic crashes (RTC) have now become a great social alarm and the situation is deteriorating day by day. Today’s black spot identification process is not based on modern technical tools and most of the cases provide wrong output. In this situation, characteristic analysis and black spot identification by spatial analysis would be an effective and low cost approach in ensuring road safety. The methodology of this study incorporates a framework on the basis of spatial-temporal study to identify most RTC occurrence locations. In this study, a very important and economic corridor like Dhaka to Sylhet highway has been chosen to apply the method. This research proposes that KDE method for identification of Hazardous Road Location (HRL) could be used for all other National highways in Bangladesh and also for other developing countries. Some recommendations have been suggested for policy maker to reduce RTC in Dhaka-Sylhet especially in black spots.

Keywords: hazardous road location (HRL), crash, GIS, kernel density

Procedia PDF Downloads 298

Authors: Jan-Peter Mund, Christian Kind

Abstract:

In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

Procedia PDF Downloads 74