Search results for: spatial rainfall prediction

Authors: Liang Sun, Yi He

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The origination and development of Chinese traditional villages have a strong link with clan society. Thousands of traditional villages are constituted by one big family who have the same surname. Villages’ basic social relationships are built on the basis of family kinship. Clan power controls family courtyards’ spatial structure and influences their evolvement process. Compared with other countries, research from perspective of clanism is a particular and universally applicable manner to recognize Chinese traditional villages’ space features. This paper takes traditional villages in astern Zhejiang province as examples, especially a single-clan village named Zoumatang. Through combining rural sociology with architecture, it clarifies the coupling relationship between clan structure and village space, reveals spatial composition and evolvement logic of family courtyards. Clan society pays much attention to the patrilineal kinship and genealogy. In astern Zhejiang province, clan is usually divided to ‘clan-branches-families’ three levels. Its structural relationship looks like pyramid, which results in ‘center-margin’ structure when projecting to villages’ space. Due to the cultural tradition of ancestor worship, family courtyards’ space exist similar ‘center-margin’ structure. Ancestor hall and family temple are respectively the space core of village and courtyard. Other parts of courtyard also shows order of superiority and inferiority. Elder and men must be the first. However, along with the disintegration of clan society, family courtyard gradually appears fragmentation trend. Its spatial structure becomes more and more flexible and its scale becomes smaller and smaller. Living conditions rather than ancestor worship turn out to be primary consideration. As a result, there are different courtyard historical prototype in different historic period. To some extent, Chinese present traditional villages’ conservation ignore the impact of clan society. This paper discovers the social significance of courtyard’s spatial texture and rebuilds the connection between society and space. It is expected to promote Chinese traditional villages’ conservation paying more attention to authenticity which defined in the historical process and integrity which built on the basis of social meaning.

Keywords: China, clanism, courtyard, evolvement process, spatial structure, traditional village

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Authors: Serife Gulden Yilmaz, Suleyman Karaman

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Sheep breeding is important in terms of meeting both the demand of red meat consumption and the availability of industrial raw materials and the employment of the rural sector in Turkey. It is also very important to ensure the selection and continuity of the breeds that are raised in order to increase quality and productive products related to sheep breeding. The protection of local breeds and crossbreds also enables the development of the sector in the region and the reduction of imports. In this study, the data were obtained from the records of the Turkish Statistical Institute and Antalya Sheep & Goat Breeders' Association. Spatial distribution of sheep breeds in Antalya is reviewed statistically in terms of concentration at the local level for 2015 period spatially. For this reason; mapping, box plot, linear regression are used in this study. Concentration is introduced by means of studbook data on sheep breeding as locals and total sheep farm by mapping. It is observed that Pırlak breed (17.5%) and Merinos crossbreed (16.3%) have the highest concentration in the region. These breeds are respectively followed by Akkaraman breed (11%), Pirlak crossbreed (8%), Merinos breed (7.9%) Akkaraman crossbreed (7.9%) and Ivesi breed (7.2%).

Keywords: sheep breeds, local, spatial distribution, agglomeration, Antalya

Procedia PDF Downloads 270

Authors: Ashok Tejankar, Rohan K. Pathrikar

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Maharashtra is covered by heterogeneous flows of Deccan basaltic terrains of upper cretaceous to lower Eocene age. It consist mainly different types of basalt flow, having heterogeneous Geohydrological characters. The study area Aurangabad dist. lies in the central part of Maharashtra. The study area is typically covered by Deccan traps formation mainly basalt type of igneous volcanic rock. The area is located in the survey of India toposheet No. 47M and laying between 19° to 20° north latitudes and 74° to 76° east longitudes. Groundwater is the primary source for fresh water in the study area. There has been a growing demand for fresh water in domestic & agriculture sectors. Due to over exploitation and rainfall failure has been created an irrecoverable stress on groundwater in study area. In an effort to maintain the water table condition in balance, artificial recharge is being implemented. The selection of site for artificial recharge is a very important task in recharge basalt. The present study aims at sitting artificial recharge structure at village Pachod in basaltic terrain of the Godavari-Purna river basin in Aurangabad district of Maharashtra, India. where the average annual rainfall is 650mm. In this investigation, integrated remote sensing and GIS techniques were used and various parameters like lithology, structure, etc. aspect of drainage basins, landforms and other parameters were extracted from visual interpretation of IRS P6 Satellite data and Survey of India (SIO) topographical sheets, aided by field checks by carrying well inventory survey. The depth of weathered material, water table conditions, and rainfall data were been considered. All the thematic information layers were digitized and analyzed in Arc-GIS environment and the composite maps produced show suitable site, depth of bed rock flows for successful artificial recharge in village Pachod to increase groundwater potential of low laying area.

Keywords: hard rock, artificial recharge, remote sensing, GIS

Procedia PDF Downloads 280

Authors: Zegrar Ahmed, Ghabi Mohamed

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The degradation of arid and semi-arid ecosystems in Algeria has become a palpable fact that only hinders progress and rural development. In these exceptionally fragile environments, the decline of vegetation is done according to an alarming increase and wind erosion dominates. The ecosystem is subjected to a long hot dry season and low annual average rainfall. The urgency of the fight against desertification is imposed by the very nature of the process that tends to self-accelerate, resulting when human intervention is not forthcoming the irreversibility situations, preventing any possibility of restoration state of these zones. These phenomena have led to different degradation processes, such as the destruction of vegetation, soil erosion, and deterioration of the physical environment. In this study, the work is mainly based on the criteria for classification and identification of physical parameters for spatial analysis and multi-sources to determine the vulnerability of major steppe formations and their impact on desertification. we used Landsat data with two different dates March 2010 and November 2014 in order to determine the changes in land cover, sand moving and land degradation for the diagnosis of the desertification Phenomenon. The application, through specific processes, including the supervised classification was used to characterize the main steppe formations. An analysis of the vulnerability of plant communities was conducted to assign weights and identify areas most susceptible to desertification. Vegetation indices are used to characterize the steppe formations to determine changes in land use.

Keywords: remote sensing, SIG, ecosystem, degradation, desertification

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Authors: Ntungamili Kenosi, Moatlhodi W. Letshwenyo

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Negative environmental impacts due to construction of large projects such as dams have become an important aspect of land degradation. This paper will review the previous literature on the previous researches or study in the same area of study in the other parts of the world. After dam has been constructed, the actual environmental impacts are investigated and compared to the predicted results of the carried out Environmental Impact Assessment. GIS and Remote Sensing, play an important role in generating automated spatial data sets and in establishing spatial relationships. Results from other sources shows that the normalized vegetation index (NDVI) analysis was used to detect the spatial and temporal change of vegetation biomass in the study area. The result indicated that the natural vegetation biomass is declining. This is mainly due to the expansion of agricultural land and escalating human made structures in the area. Urgent environmental conservation is necessary when adjoining projects site. Less study on the evaluation of EIA on dam has been conducted in Botswana hence there is a need for the same study to be conducted and then it will be easy to be compared to other studies around the world.

Keywords: Botswana, dam, environmental impact assessment, GIS, normalized vegetation index (NDVI), remote sensing

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Authors: Aidan J. Bowes, Reaz Hasan

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The automotive industry is continually aiming to develop the aerodynamics of car body design. This may be for a variety of beneficial reasons such as to increase speed or fuel efficiency by reducing drag. However recently there has been a greater amount of focus on wind noise produced while driving. Designers in this industry seek a combination of both simplicity of approach and overall effectiveness. This combined with the growing availability of commercial CFD (Computational Fluid Dynamics) packages is likely to lead to an increase in the use of RANS (Reynolds Averaged Navier-Stokes) based CFD methods. This is due to these methods often being simpler than other CFD methods, having a lower demand on time and computing power. In this investigation the effectiveness of turbulent flow and acoustic noise prediction using RANS based methods has been assessed for different wing mirror geometries. Three different RANS based models were used, standard k-ε, realizable k-ε and k-ω SST. The merits and limitations of these methods are then discussed, by comparing with both experimental and numerical results found in literature. In general, flow prediction is fairly comparable to more complex LES (Large Eddy Simulation) based methods; in particular for the k-ω SST model. However acoustic noise prediction still leaves opportunities for more improvement using RANS based methods.

Keywords: acoustics, aerodynamics, RANS models, turbulent flow

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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Authors: Ling Qi, Matloob Khushi, Josiah Poon

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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

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Authors: Daniel Macedo Neto, Sandro Froehner, Juan Sanez

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Suspended sediments (SS) are an environmental constituent able to represent the effects of land use changes on watersheds. One important consideration of land use change is its implication on trace element loading. Water bodies have the capacity to retain trace elements. Spatial variation in trace elements concentrations can be associated with land occupation and sources of pollution. In this work, the spatial variation of trace elements in suspended sediments from an urban river was assessed. Time-integrated fluvial suspended sediment samples were installed in three different sites of Barigui River. The suspend solids were collected every 30 days, from May 2015 to August 2015 (total samples 12). Site P1 covers 44 km2 drainage area and has low land occupation, whilst P2 cover an area of 87 km2 and it is totally urban as P3, which area is higher than 130 km2. Trace elements (As, Cd, Cr, P, Pb and Zn) were analysed by ICP-ES. All elements analyzed showed a similar pattern, i.e., the concentration raise with the urbanization, exception for As (P1=7.75; P2=5.75; P3=5.60mg/kg). There was increase in concentration for Cd (P1=0.75; P2=0.78; P3=1.45mg/kg), Cr (P1=59.50; P2=101.75; P3=102.00 mg/kg), Zn (P1=142.25; P2=152.50; P3=223.00mg/kg), P (P1=937.50; P2=1,545.00; P3=2,355.00 mg/kg) and for Pb (P1=31.25; P2=32.75; P3=39.17±2.56 mg/kg). The variation in concentrations were as follow -27.74% (As), +93.33% (Cd), +71.43% (Cr), +151.20% (P), +25.33% (Pb) e +56.77% (Zn). Cd, Cr, P, Pb and Zn presented a clear trend of increasing the concentration from upstream to downstream. Such variation is more notorious for P, Cd and Cr, possibly due the urbanization.

Keywords: trace elements, erosion, urbanization, suspended sediments

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Authors: Amira Abdelrasoul, Huu Doan, Ali Lohi

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An efficient and well-planned ultrafiltration process is becoming a necessity for monetary returns in the industrial settings. The aim of the present study was to develop a mathematical model for an accurate prediction of ultrafiltration membrane fouling of latex effluent applied to homogeneous and heterogeneous membranes with uniform and non-uniform pore sizes, respectively. The models were also developed for an accurate prediction of power consumption that can handle the large-scale purposes. The model incorporated the fouling attachments as well as chemical and physical factors in membrane fouling for accurate prediction and scale-up application. Both Polycarbonate and Polysulfone flat membranes, with pore sizes of 0.05 µm and a molecular weight cut-off of 60,000, respectively, were used under a constant feed flow rate and a cross-flow mode in ultrafiltration of the simulated paint effluent. Furthermore, hydrophilic ultrafilic and hydrophobic PVDF membranes with MWCO of 100,000 were used to test the reliability of the models. Monodisperse particles of 50 nm and 100 nm in diameter, and a latex effluent with a wide range of particle size distributions were utilized to validate the models. The aggregation and the sphericity of the particles indicated a significant effect on membrane fouling.

Keywords: membrane fouling, mathematical modeling, power consumption, attachments, ultrafiltration

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Authors: Dedah Ahmed Babou, Nicolas Bez

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The Min-Max autocorrelation factor (MAF) approach makes it possible to express in a space formed by spatially independent factors, spatiotemporal observations. These factors are ordered in decreasing order of spatial autocorrelation. The starting observations are thus expressed in the space formed by these factors according to temporal coordinates. Each vector of temporal coefficients expresses the temporal evolution of the weight of the corresponding factor. Applying this approach has enabled us to achieve the following results: (i) Define a spatially orthogonal space in which the projections of the raw data are determined; (ii) Define a limit threshold for the factors with the strongest structures in order to analyze the weight, and the temporal evolution of these different structures (iii) Study the correlation between the temporal evolution of the persistent spatial structures and that of the observed average abundance (iv) Propose prototypes of campaigns reflecting a high vs. low abundance (v) Propose a classification of campaigns that highlights seasonal and/or temporal similarities. These results were obtained by analyzing the octopus yield during the scientific campaigns of the oceanographic vessel Al Awam during the period 1989-2017 in the Mauritanian exclusive economic zone.

Keywords: spatiotemporal , autocorrelation, kriging, variogram, Octopus vulgaris

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

Procedia PDF Downloads 350

Authors: Hala Obeid

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Among the cities that have been touched by hard events and have been experiencing this polemic of existence, one can quote Beirut. A city that defies and confronts itself for its own existence. Beirut materialized all the social complexity; it has also preserved the memory of a society that has been able to build and reflect a certain unique identity. In spite of its glory, Lebanon’s civil war has marked a turning point in Beirut’s history. It has caused many deaths and opposed religious communities. Once this civil war has ended, the reconstruction of the city center, however, saw the spatial exclusion of manual labor, small local commerce, and middle-class residences. The urban functions that characterized the pre-war center were removed, and the city’s spontaneous evolutions were replaced by a historical urban planning, which neglected the city’s memory and identity. The social and spatial fragmentation that has erupted since the war has led to a breakdown of spatial and social boundaries within the city. The aim of this study is to evaluate the impact of fragmentation and boundaries on the city of Beirut in spatial, social, religious and ethnic terms. The method used in this research is what we call the mixed method which is a combination between the quantitative method and the qualitative one. These two approaches, in this case, do not oppose but complement each other in order to study the city of Beirut physically and socially. The main purpose of the qualitative approach is to describe and analyze the social phenomenon of the fragmentation of the city; this method can be summarized by the field observation and study. While the quantitative approach is based on filling out questionnaires that leads to statistics analyzes. Together, these two approaches will mark the course of the research. As a result, Beirut is not only a divided city but is fragmented spatially into many fragments and socially into many groups. This fragmentation is creating immaterial boundaries between fragments and therefore between groups. These urban and social boundaries are specifically religious and ethnic limits. As a conclusion, one of the most important and discussed boundary in Beirut is a spatial and religious boundary called ‘the green line’ or the demarcation line, a true caesura within the city. It marks the opposition of two urban groups and the aggravated fragmentation between them. This line divided Beirut into two compartments: East Beirut (for Christians) and West Beirut (for Muslims). This green line has become an urban void that holds the past in suspension. Finally, to think of Beirut as an urban unit becomes an insoluble problem.

Keywords: Beirut, boundaries, fragmentation, identity

Procedia PDF Downloads 151

Authors: A. Papadopoulou

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When people are asked to provide an oral description of a space they usually provide a Tour description, which is a dynamic type of spatial narrative centered on the narrator’s body, rather than a Map description, which is a static type of spatial narrative focused on the organization of the space as seen from above. Also, subjects with training in the architecture discipline tend to adopt a Tour perspective of space when the narrative refers to a space they have actually experienced but tend to adopt a Map perspective when the narrative refers to a space they have merely imagined. This pilot study aims to investigate whether the Tour description, which is the most common mode in the oral descriptions of experienced space, is a cognitive perspective taken in the process of designing a space. The study investigates whether a spatial description provided by a subject with architecture training in the type of a Tour description would be accurately translated into a spatial layout by other subjects with architecture training. The subjects were given the Tour description in written form and were asked to make a plan drawing of the described space. The results demonstrate that when we conceive and design space we do not adopt the same rules and cognitive patterns that we adopt when we reconstruct space from our memory. As shown by the results of this pilot study, the rules that underlie the Tour description were not detected in the translation from narratives to drawings. In a different phase, the study also investigates how would subjects with architecture training describe space when forced to take a Tour perspective in their oral description of a space. The results of this second phase demonstrate that if intentionally taken, the Tour perspective leads to descriptions of space that are more detailed and focused on experiential aspects.

Keywords: architecture, design process, embodied cognition, map description, oral narratives, tour description

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Authors: Marzieh Karimihaghighi, Carlos Castillo

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This work studies how Machine Learning (ML) may be used to increase the effectiveness of a criminal recidivism risk assessment tool, RisCanvi. The two key dimensions of this analysis are predictive accuracy and algorithmic fairness. ML-based prediction models obtained in this study are more accurate at predicting criminal recidivism than the manually-created formula used in RisCanvi, achieving an AUC of 0.76 and 0.73 in predicting violent and general recidivism respectively. However, the improvements are small, and it is noticed that algorithmic discrimination can easily be introduced between groups such as national vs foreigner, or young vs old. It is described how effectiveness and algorithmic fairness objectives can be balanced, applying a method in which a single error disparity in terms of generalized false positive rate is minimized, while calibration is maintained across groups. Obtained results show that this bias mitigation procedure can substantially reduce generalized false positive rate disparities across multiple groups. Based on these results, it is proposed that ML-based criminal recidivism risk prediction should not be introduced without applying algorithmic bias mitigation procedures.

Keywords: algorithmic fairness, criminal risk assessment, equalized odds, recidivism

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Authors: Mohamed Elhakeem, A. N. Thanos Papanicolaou, Christopher Wilson, Yi-Jia Chang

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In this study, a physically-based, modelling framework was developed to predict saturated hydraulic conductivity (KSAT) dynamics in the Clear Creek Watershed (CCW), Iowa. The modelling framework integrated selected pedotransfer functions and watershed models with geospatial tools. A number of pedotransfer functions and agricultural watershed models were examined to select the appropriate models that represent the study site conditions. Models selection was based on statistical measures of the models’ errors compared to the KSAT field measurements conducted in the CCW under different soil, climate and land use conditions. The study has shown that the predictions of the combined pedotransfer function of Rosetta and the Water Erosion Prediction Project (WEPP) provided the best agreement to the measured KSAT values in the CCW compared to the other tested models. Therefore, Rosetta and WEPP were integrated with the Geographic Information System (GIS) tools for visualization of the data in forms of geospatial maps and prediction of KSAT variability in CCW due to the seasonal changes in climate and land use activities.

Keywords: saturated hydraulic conductivity, pedotransfer functions, watershed models, geospatial tools

Procedia PDF Downloads 239

Authors: Tomas Berhanu Bekele

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

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Authors: Andrey Lebedev, Ilya Dmitrenok, JooYoung Lee, Leonard Johard

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Top-k shortest path routing problem is an extension of finding the shortest path in a given network. Shortest path is one of the most essential measures as it reveals the relations between two nodes in a network. However, in many real world networks, whose diameters are small, top-k shortest path is more interesting as it contains more information about the network topology. Many variations to compute top-k shortest paths have been studied. In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Then, we also propose a top-k distance based graph matching algorithm.

Keywords: graph matching, link prediction, shortest path, similarity

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Authors: Arup K. Sarma, Jayshree Hazarika

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The North-eastern part of India, which receives heavier rainfall than other parts of the subcontinent, is of great concern now-a-days with regard to climate change. High intensity rainfall for short duration and longer dry spell, occurring due to impact of climate change, affects river morphology too. In the present study, an attempt is made to delineate the North-Eastern region of India into some homogeneous clusters based on the Fuzzy Clustering concept and to compare the resulting clusters obtained by using conventional methods and non conventional methods of clustering. The concept of clustering is adapted in view of the fact that, impact of climate change can be studied in a homogeneous region without much variation, which can be helpful in studies related to water resources planning and management. 10 IMD (Indian Meteorological Department) stations, situated in various regions of the North-east, have been selected for making the clusters. The results of the Fuzzy C-Means (FCM) analysis show different clustering patterns for different conditions. From the analysis and comparison it can be concluded that non conventional method of using GCM data is somehow giving better results than the others. However, further analysis can be done by taking daily data instead of monthly means to reduce the effect of standardization.

Keywords: climate change, conventional and nonconventional methods of clustering, FCM analysis, homogeneous regions

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Authors: Sidong Zhao, Xingping Wang

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Recently, the government of China has provided strong support the developments of overseas industrial parks. The global distribution of China overseas industrial parks has gradually moved from the 'sparks of fire' to the 'prairie fires.' The support and distribution have promoted developing overseas industrial parks to a strategy of constructing a China's new open economic system and a typical representative of the 'Chinese wisdom' and the 'China's plans' that China has contributed to the globalization of the new era under the initiative of the Belt and Road. As the industrial parks are the basis of 'work/employment', a basic function of a city (Athens Constitution), planning for developments of industrial parks has become a long-term focus of urban planning. Based on the research of the planning and the analysis of the present developments of some typical China overseas industrial parks, we found some interesting rules: First, large numbers of the China overseas industrial parks are located in less developed countries. These industrial parks have become significant drives of the developments of the host cities and even the regions in those countries, especially in investment, employment and paid tax fee for the local, etc. so, the planning and development of overseas industrial parks have received extensive attention. Second, there are some problems in the small part of the overseas Park, such as the planning of the park not following the planning of the host city and lack of implementation of the park planning, etc. These problems have led to the difficulties of the implementation of the planning and the sustainable developments of the parks. Third, a unique pattern of space development has been formed. in the dimension of the patterns of regional spatial distribution, there are five characteristics - along with the coast, along the river, along with the main traffic lines and hubs, along with the central urban area and along the connections of regions economic. In the dimension of the spatial relationships between the industrial park and the city, there is a growing and evolving trend as 'separation – integration - union'. In the dimension of spatial mode of the industrial parks, there are different patterns of development, such as a specialized industrial park, complex industrial park, characteristic town and new urban area of industry, etc. From the perspective of the trends of the developments and spatial modes, in the future, the planning of China overseas industrial parks should emphasize the idea of 'building a city based on the industrial park'. In other words, it's making the developments of China overseas industrial parks move from 'driven by policy' to 'driven by the functions of the city', accelerating forming the system of China overseas industrial parks and integrating the industrial parks and the cities.

Keywords: overseas industrial park, spatial mode, planning, China

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Authors: Marinela Istrate, Ionel Muntele, Alexandru Bănică

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The authors propose the identification, analysis and prognosis of the quantitative and qualitative evolution of the elderly population in the functional urban areas. The present paper takes into account the analysis of some representative indicators (the weight of the elderly population, ageing index, dynamic index of economic ageing of productive population etc.) and the elaboration of an integrated indicator that would help differentiate the population ageing forms in the 48 functional urban areas that were defined based on demographic and social-economic criteria for all large and medium cities in Romania.

Keywords: ageing, demographic transition, functional urban areas, spatial resilience

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Authors: Krzysztof T. Piotrowski

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The main goal of the research was to investigate differences in attention in two kinds of musical performance - recall and improvisation. Musical recall is a sample of convergent production that requires intensively focused attention. Inversely, musical improvisation is a divergent task and probably requires a different way of attentional control. The study was designed in dual task paradigm. Participants were to remember a simple melody and then recall or improvise, simultaneously performing the spatial attentional test on computer screen. The result shows that improvising participants find spatial goals in more disperse way. The conclusion is that musical improvisation requires extensification of attention to occur.

Keywords: attention, creativity, divergent task, musical improvisation

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Authors: Faizul Azly Abd Dzubir, Muhammad F. Othman

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Conventional structural health monitoring approach for mechanical equipment uses inspection data from Non-Destructive Testing (NDT) during plant shut down window and fitness for service evaluation to estimate the integrity of the equipment that is prone to crack damage. Yet, this forecast is fraught with uncertainty because it is often based on assumptions of future operational parameters, and the prediction is not continuous or online. Advanced Diagnostic and Prognostic Technology (ADaPT) uses Acoustic Emission (AE) technology and a stochastic prognostic model to provide real-time monitoring and prediction of mechanical defects or cracks. The forecast can help the plant authority handle their cracked equipment before it ruptures, causing an unscheduled shutdown of the facility. The ADaPT employs process historical data trending, finite element analysis, fitness for service, and probabilistic statistical analysis to develop a prediction model for crack initiation and growth due to mechanical damage. The prediction model is combined with live equipment operating data for real-time prediction of the remaining life span owing to fracture. ADaPT was devised at a hot combined feed exchanger (HCFE) that had suffered creep crack damage. The ADaPT tool predicts the initiation of a crack at the top weldment area by April 2019. During the shutdown window in April 2019, a crack was discovered and repaired. Furthermore, ADaPT successfully advised the plant owner to run at full capacity and improve output by up to 7% by April 2019. ADaPT was also used on a coke drum that had extensive fatigue cracking. The initial cracks are declared safe with ADaPT, with remaining crack lifetimes extended another five (5) months, just in time for another planned facility downtime to execute repair. The prediction model, when combined with plant information data, allows plant operators to continuously monitor crack propagation caused by mechanical damage for improved maintenance planning and to avoid costly shutdowns to repair immediately.

Keywords: mechanical damage, cracks, continuous monitoring tool, remaining life, acoustic emission, prognostic model

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Authors: Prashant Verma

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Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

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Authors: Pitchayanin Sukholthaman

Abstract:

Gradually accumulated, the enormous amount of waste has caused tremendous adverse impacts to the world. Bangkok, Thailand, is chosen as an urban city of a developing country having coped with serious MSW problems due to the vast amount of waste generated, ineffective and improper waste management problems. Waste generation is the most important factor for successful planning of MSW management system. Thus, the prediction of MSW is a very important role to understand MSW distribution and characteristic; to be used for strategic planning issues. This study aims to find influencing variables that affect the amount of Bangkok MSW generation quantity.

Keywords: MSW generation, MSW quantity prediction, MSW management, multiple regression, Bangkok

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Authors: Kudzanayi Chiteka, Wellington Makondo

Abstract:

The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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Authors: Rahim Sarvar, Bahram Azadbakht, Samira Safaee

Abstract:

The leading goal of all planning is to attain sustainable development, regional balance, suitable distribution of activities, and maximum use of environmental capabilities in the process of development of regions. Intensive concentration of population and activities in one or some limited geographical locality is of main characteristics of most developing countries, especially Iran. Not considering the long-term programs and relying on temporary and superficial plans by people in charge of decision-making to attain their own objectives causes obstacles, resulting in unbalance development. The basic reason for these problems is to establish the development planning while economic aspects are merely considered and any attentions are not paid to social and regional feedbacks, what have been ending up to social and economic inequality, unbalanced distribution of development among the regions as well. In addition to study of special planning and structure of the county of Malekan, this research tries to achieve some other aims, i.e. recognition and introduction of approaches in order to utilize resources optimally, to distribute the population, activities, and facilities in optimum fashion, and to investigate and identify the spatial development potentials of the County. Based on documentary, descriptive, analytical, and field studies, this research employs maps to analyze the data, investigates the variables, and applies SPSS, Auto CAD, and Arc View software. The results show that the natural factors have a significant influence on spatial layout of settlements; distribution of facilities and functions are not equal among the rural districts of the county; and there is a spatial equivalence in the region area between population and number of settlements.

Keywords: development, entropy index, Malekan City, planning, regional equilibrium

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Authors: Olalekan Lawrence Ojo

Abstract:

Designing microwave terrestrial propagation networks requires a thorough evaluation of the severity of multipath fading, especially at frequencies below 10 GHz. In nations like Nigeria, without a large enough databases to support the existing empirical models, the mistakes in the prediction technique intended for the evaluation may be severe. The need for higher bandwidth for various satellite applications makes the investigation of the effects of radio refractivity, fading due to multipath, and Geoclimatic factors on satellite propagation links more important. One of the key elements to take into account for the best functioning of microwave frequencies is the clear air effects. This work has taken into account the geographical distribution of radio refractivity and fades depth over a number of stations in Nigeria. Data from five locations in Nigeria—Akure, Enugu, Jos, Minna, and Sokoto—based on five-year (2017–2021) measurement methods of atmospheric pressure, relative, and humidity temperature—at two levels (ground surface and 100 m heights)—are studied to deduced their effects on signals propagated through a µwave communication links. The assessments included considerations for µwave communication systems as well as the impacts of the dry and wet components of radio refractivity, the effects of the fade depth at various frequencies, and a 20 km link distance. The results demonstrate that the percentage occurrence of the dry terms dominated the radio refractivity constituent at the surface level, contributing a minimum of about 78% and a maximum of about 92%, while at heights of 100 meters, the percentage occurrence of the dry terms dominated the radio refractivity constituent, contributing a minimum of about 79% and a maximum of about 92%. The spatial distribution reveals that, regardless of height, the country's tropical rainforest (TRF) and freshwater swampy mangrove (FWSM) regions reported the greatest values of radio refractivity. The statistical estimate shows that fading values can differ by as much as 1.5 dB, especially near the TRF and FWSM coastlines, even during clear air conditions. The current findings will be helpful for budgeting Earth-space microwave links, particularly for the rollout of Nigeria's 5G and 6G projected microcellular networks.

Keywords: fade depth, geoclimatic factor, refractivity, refractivity gradient

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Authors: Guantao Bai

Abstract:

Public space is an indispensable and important component of the urban built environment. How to more accurately evaluate the usage characteristics of public space can help improve its spatial quality. Compared to traditional survey methods, computer vision technology based on deep learning has advantages such as dynamic observation and low cost. This study takes the public space of Shaping Park as an example and, based on deep learning computer vision technology, processes and analyzes the image data of the public space to obtain the spatial usage characteristics and spatiotemporal characteristics of the public space. Research has found that the spontaneous activity time in public spaces is relatively random with a relatively short average activity time, while social activities have a relatively stable activity time with a longer average activity time. Computer vision technology based on deep learning can effectively describe the spatial usage characteristics of the research area, making up for the shortcomings of traditional research methods and providing relevant support for creating a good public space.

Keywords: computer vision, deep learning, public spaces, using features

Procedia PDF Downloads 52