Search results for: spatial parallel structure

Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

Procedia PDF Downloads 373

Authors: Guilan Huang

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In 2013 and 2014, the U.S. Food and Drug Administration (FDA) collected data from selected fast food restaurants and full service restaurants for tracking changes in the occurrence of foodborne illness risk factors. This paper discussed how we customized spatial random sampling method by considering financial position and availability of FDA resources, and how we enriched restaurants data with location. Location information of restaurants provides opportunity for quantitatively determining random sampling within non-government units (e.g.: 240 kilometers around each data-collector). Spatial analysis also could optimize data-collectors’ work plans and resource allocation. Spatial analytic and processing platform helped us handling the spatial random sampling challenges. Our method fits in FDA’s ability to pinpoint features of foodservice establishments, and reduced both time and expense on data collection.

Keywords: geospatial technology, restaurant, retail food risk factor study, spatially random sampling

Procedia PDF Downloads 321

Authors: Mohamed Mahmoud Hasan, Hoda M. O. Mokhtar

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With the gigantic increment in portable applications use and the spread of positioning and location-aware technologies that we are seeing today, new procedures and methodologies for location-based strategies are required. Location recommendation is one of the highly demanded location-aware applications uniquely with the wide accessibility of social network applications that are location-aware including Facebook check-ins, Foursquare, and others. In this paper, we aim to present a new methodology for location recommendation. The proposed approach coordinates customary spatial traits alongside other essential components including shortest distance, and user interests. We also present another idea namely, "activity trajectory" that represents trajectory that fulfills the set of activities that the user is intrigued to do. The approach dispatched acquaints the related distance value to select trajectory(ies) with minimum cost value (distance) and spatial-area to prune unneeded directions. The proposed calculation utilizes the idea of movement direction to prescribe most comparable N-trajectory(ies) that matches the client's required action design with least voyaging separation. To upgrade the execution of the proposed approach, parallel handling is applied through the employment of a MapReduce based approach. Experiments taking into account genuine information sets were built up and tested for assessing the proposed approach. The exhibited tests indicate how the proposed approach beets different strategies giving better precision and run time.

Keywords: location based recommendation, map-reduce, recommendation system, trajectory search

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Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, a one-dimensional (1d) Parallel Elasto- Plastic Model (PEPM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement, is presented. The parallel modeling concept is applied to discretize the continuously decreasing tangent stiffness function, thus allowing to simulate the dynamic behavior of seismic isolation bearings by putting linear elastic and nonlinear elastic-perfectly plastic elements in parallel. The mathematical model has been validated by comparing the experimental force-displacement hysteresis loops, obtained testing a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted numerically. Good agreement between the simulated and experimental results shows that the proposed model can be an effective numerical tool to predict the forcedisplacement relationship of seismic isolators within relatively large displacements. Compared to the widely used Bouc-Wen model, the proposed one allows to avoid the numerical solution of a first order ordinary nonlinear differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort, and requires the evaluation of only three model parameters from experimental tests, namely the initial tangent stiffness, the asymptotic tangent stiffness, and a parameter defining the transition from the initial to the asymptotic tangent stiffness.

Keywords: base isolation, earthquake engineering, parallel elasto-plastic model, seismic isolators, softening hysteresis loops

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Authors: Sarah Nasser, Anne Moreau, Alain Hedoux, Romain Jeantet, Guillaume Delaplace

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Background: Spray dryed powders containing some caseins are commonly produced in dairy industry. It is widely admitted that the structure of casein evolves during powder storage, inducing a loss of solubility. However few studies evaluate accurately the destabilization mechanisms at molecular and mesoscopic level, in particular for Native Phospho Casein powder (NPC). Consequently, at the state of the art, it is very difficult to assess which secondary structure change or crosslinks initiate insolubility during storage. To address this issue, controlled ageing conditions have been applied to a NPC powder (which was obtained by spray drying a concentrate containing a higher content of casein (90%), whey protein (8%) and lactose (few %)). Evolution of structure and loss of solubility, with the effects of temperature and time of storage were systematically reported. Methods: FTIR spectroscopy, Raman and Circular Dichroism were used to monitor changes of secondary structure in dry powder and in solution after rehydration. Besides, proteomic tools and electrophoresis have been performed after varying storage conditions for evaluating aggregation and post translational modifications, like lactosylation or phosphorylation. Finally, Tof Sims and MEB were used to follow in parallel evolution of structure in surface and skin formation due to storage. Results + conclusion: These results highlight the important role of storage temperature in the stability of NPC. It is shown that this is not lactosylation at the heart of formation of aggregates, as advanced in others publications This is almost the rise of multitude post translational modifications (chemical cross link), added to disulphide bridges (physical cross link) wich contribute to the destabilisation of structure and aggregation of casein. A relative quantification of each kind of cross link, source of aggregates, is proposed. In addition, it has been proved that migration of lipids and formation of skin in surface during the ageing also explains the evolution of structure casein and thus the alterations of functional properties of NPC powder.

Keywords: casein, cross link, powder, storage

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Authors: Chengming Li, Yong Yin, Peipei Guo, Xiaoli Liu

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Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.

Keywords: POI, road network, selection method, spatial information expression, distribution pattern

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Authors: Aziza Ben Halima, Julien Bert, Dimitris Visvikis

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In this paper, we propose designing and evaluating a parallel co-manipulated robot dedicated to low-dose-rate prostate brachytherapy. We developed 6 degrees of freedom compact and lightweight robot easy to install in the operating room thanks to its parallel design. This robotic system provides a co-manipulation allowing the surgeon to keep control of the needle’s insertion and consequently to improve the acceptability of the plan for the clinic. The best dimension’s configuration was solved by calculating the geometric model and using an optimization approach. The aim was to ensure the whole coverage of the prostate volume and consider the allowed free space around the patient that includes the ultrasound probe. The final robot dimensions fit in a cube of 300 300 300 mm³. A prototype was 3D printed, and the robot workspace was measured experimentally. The results show that the proposed robotic system satisfies the medical application requirements and permits the needle to reach any point within the prostate.

Keywords: medical robotics, co-manipulation, prostate brachytherapy, optimization

Procedia PDF Downloads 175

Authors: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

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In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.

Keywords: binary vector quantization (BVQ), DCT coefficients, face recognition, local binary patterns (LBP)

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Authors: S. K. Appiah, E. N. Aidoo, D. Asamoah Owusu, M. W. Nuonabuor

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Urbanization remains one of the unique predominant factors which is linked to the destruction of urban environment and its associated cases of soil contamination by heavy metals through the natural and anthropogenic activities. These activities are important sources of toxic heavy metals such as arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), and lead (Pb), nickel (Ni) and zinc (Zn). Often, these heavy metals lead to increased levels in some areas due to the impact of atmospheric deposition caused by their proximity to industrial plants or the indiscriminately burning of substances. Information gathered on potentially hazardous levels of these heavy metals in soils leads to establish serious health and urban agriculture implications. However, characterization of spatial variations of soil contamination by heavy metals in Ghana is limited. Kumasi is a Metropolitan city in Ghana, West Africa and is challenged with the recent spate of deteriorating soil quality due to rapid economic development and other human activities such as “Galamsey”, illegal mining operations within the metropolis. The paper seeks to use both univariate and multivariate geostatistical techniques to assess the spatial distribution of heavy metals in soils and the potential risk associated with ingestion of sources of soil contamination in the Metropolis. Geostatistical tools have the ability to detect changes in correlation structure and how a good knowledge of the study area can help to explain the different scales of variation detected. To achieve this task, point referenced data on heavy metals measured from topsoil samples in a previous study, were collected at various locations. Linear models of regionalisation and coregionalisation were fitted to all experimental semivariograms to describe the spatial dependence between the topsoil heavy metals at different spatial scales, which led to ordinary kriging and cokriging at unsampled locations and production of risk maps of soil contamination by these heavy metals. Results obtained from both the univariate and multivariate semivariogram models showed strong spatial dependence with range of autocorrelations ranging from 100 to 300 meters. The risk maps produced show strong spatial heterogeneity for almost all the soil heavy metals with extremely risk of contamination found close to areas with commercial and industrial activities. Hence, ongoing pollution interventions should be geared towards these highly risk areas for efficient management of soil contamination to avert further pollution in the metropolis.

Keywords: coregionalization, heavy metals, multivariate geostatistical analysis, soil contamination, spatial distribution

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Authors: Francky Fouedjio

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Multivariate geostatistical data have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations within the same cluster are more similar while clusters are different from each other, in some sense. Spatially contiguous clusters can significantly improve the interpretation that turns the resulting clusters into meaningful geographical subregions. In this paper, we develop an agglomerative hierarchical clustering approach that takes into account the spatial dependency between observations. It relies on a dissimilarity matrix built from a non-parametric kernel estimator of the spatial dependence structure of data. It integrates existing methods to find the optimal cluster number and to evaluate the contribution of variables to the clustering. The capability of the proposed approach to provide spatially compact, connected and meaningful clusters is assessed using bivariate synthetic dataset and multivariate geochemical dataset. The proposed clustering method gives satisfactory results compared to other similar geostatistical clustering methods.

Keywords: clustering, geostatistics, multivariate data, non-parametric

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Authors: Taisiia Gorshkova

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Since the 1980s, spatial correlation models have been used more often to model regional indicators. An increasingly popular method for studying regional indicators is modeling taking into account spatial relationships between objects that are part of the same economic zone. In 2000s the new class of model – spatial vector autoregressions was developed. The main difference between standard and spatial vector autoregressions is that in the spatial VAR (SpVAR), the values of indicators at time t may depend on the values of explanatory variables at the same time t in neighboring regions and on the values of explanatory variables at time t-k in neighboring regions. Thus, VAR is a special case of SpVAR in the absence of spatial lags, and the spatial panel data model is a special case of spatial VAR in the absence of time lags. Two specifications of SpVAR were applied to Russian regional data for 2000-2017. The values of GRP and regional CPI are used as endogenous variables. The lags of GRP, CPI and the unemployment rate were used as explanatory variables. For comparison purposes, the standard VAR without spatial correlation was used as “naïve” model. In the first specification of SpVAR the unemployment rate and the values of depending variables, GRP and CPI, in neighboring regions at the same moment of time t were included in equations for GRP and CPI respectively. To account for the values of indicators in neighboring regions, the adjacency weight matrix is used, in which regions with a common sea or land border are assigned a value of 1, and the rest - 0. In the second specification the values of depending variables in neighboring regions at the moment of time t were replaced by these values in the previous time moment t-1. According to the results obtained, when inflation and GRP of neighbors are added into the model both inflation and GRP are significantly affected by their previous values, and inflation is also positively affected by an increase in unemployment in the previous period and negatively affected by an increase in GRP in the previous period, which corresponds to economic theory. GRP is not affected by either the inflation lag or the unemployment lag. When the model takes into account lagged values of GRP and inflation in neighboring regions, the results of inflation modeling are practically unchanged: all indicators except the unemployment lag are significant at a 5% significance level. For GRP, in turn, GRP lags in neighboring regions also become significant at a 5% significance level. For both spatial and “naïve” VARs the RMSE were calculated. The minimum RMSE are obtained via SpVAR with lagged explanatory variables. Thus, according to the results of the study, it can be concluded that SpVARs can accurately model both the actual values of macro indicators (particularly CPI and GRP) and the general situation in the regions

Keywords: forecasting, regional data, spatial econometrics, vector autoregression

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Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit

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This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.

Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation

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Authors: Bilal Saoud

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In this paper, we propose a new method to find the community structure in networks. Our method is based on bee colony and the maximization of modularity to find the community structure. We use a bee colony algorithm to find the first community structure that has a good value of modularity. To improve the community structure, that was found, we merge communities until we get a community structure that has a high value of modularity. We provide a general framework for implementing our approach. We tested our method on computer-generated and real-world networks with a comparison to very known community detection methods. The obtained results show the effectiveness of our proposition.

Keywords: bee colony, networks, modularity, normalized mutual information

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Authors: Jong-Hwa Kim, Mu-Wook Pyeon, Yang-dam Eo, Ill-Woong Jang

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Construction of geo-spatial information recently tends to develop as multi-dimensional geo-spatial information. People constructing spatial information is also expanding its area to the general public from some experts. As well as, studies are in progress using a variety of devices, with the aim of near real-time update. In this paper, getting the stereo images using GoPro device used widely also to the general public as well as experts. And correcting the distortion of the images, then by using SIFT, DLT, is acquired the point clouds. It presented a possibility that on the basis of this experiment, using a video device that is readily available in real life, to create a real-time digital map.

Keywords: GoPro, SIFT, DLT, point clouds

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Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

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The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

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Authors: T. Weber, D. MacKenzie

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The script in this paper describes the use of advanced simulation environment using electronic systems (microcontroller, operational amplifiers, and FPGA). The simulation was used for non-linear dynamic systems behaviour with required observer structure working with parallel real-time simulation based on state-space representation. The proposed deposited model was used for electrodynamic effects including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time and such systems. For further purpose, the spatial temperature distribution may also be used. With upon system, the uncertainties and disturbances may be determined. This provides the estimation of the more precise system states for the required system and additionally the estimation of the ionising disturbances that arise due to radiation effects in space systems. The results have also shown that a system can be developed specifically with the real-time calculation (estimation) of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. TID (Total Ionising Dose) of 1 Gy and Single Effect Transient (SET) free operation up to 50 MeVcm²/mg may assure certain functions. Single-Event Latch-up (SEL) results on the placement of several transistors in the shared substrate of an integrated circuit; ionising radiation can activate an additional parasitic thyristor. This short circuit between semiconductor-elements can destroy the device without protection and measurements. Single-Event Burnout (SEB) on the other hand, increases current between drain and source of a MOSFET and destroys the component in a short time. A Single-Event Gate Rupture (SEGR) can destroy a dielectric of semiconductor also. In order to be able to react to these processes, it must be calculated within a shorter time that ionizing radiation and dose is present. For this purpose, sensors may be used for the realistic evaluation of the diffusion and ionizing effects of the test system. For this purpose, the Peltier element is used for the evaluation of the dynamic temperature increases (dT/dt), from which a measure of the ionization processes and thus radiation will be detected. In addition, the piezo element may be used to record highly dynamic vibrations and oscillations to absorb impacts of charged particle flux. All available sensors shall be used to calibrate the spatial distributions also. By measured value of size and known location of the sensors, the entire distribution in space can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms.

Keywords: cattle, biochar, manure, microbial activity

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Authors: Javed Mallick

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In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

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Authors: Abdul Hakim Khan

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The aim of the present paper is to study the Banach Space and Combinatorial Algebraic Structure of R. It is further aimed to study algebraic structure of set of all q-extension of classical formula and function for 0 < q < 1.

Keywords: integral functions, q-extensions, q numbers of metric space, algebraic structure of r and banach space

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Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi

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The spectral random field method is one of the widely used methods to obtain more reliable and accurate results in geotechnical problems involving material variability. Karhunen-Loeve (K-L) expansion method was applied to perform random field discretization of cross-correlated creep parameters. Karhunen-Loeve expansion method is based on eigenfunctions and eigenvalues of covariance function adopting Kernel integral solution. In this paper, the accuracy of Karhunen-Loeve expansion was investigated to predict long-term settlement of soft soils adopting elastic visco-plastic creep model. For this purpose, a parametric study was carried to evaluate the effect of K-L expansion terms and spatial correlation length on the reliability of results. The results indicate that small values of spatial correlation length require more K-L expansion terms. Moreover, by increasing spatial correlation length, the coefficient of variation (COV) of creep settlement increases, confirming more conservative and safer prediction.

Keywords: Karhunen-Loeve expansion, long-term settlement, reliability analysis, spatial correlation length

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Authors: Rahaf Suleiman Altallaa

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City planning involves making plans, organizing and dealing with the cities urban areas. It attempts to organize socio-spatial relationships at exceptional ranges of governance Urban planning offers the social, monetary and environmental effects of defining spatial obstacles and the influence on the spatial distribution of resources. The dreams and methods of reaching such dissemination vary extensively traditionally and geographically and are often challenged through traditional strategies that expose the political nature of application interventions and the bounds of technical know-how claims. Space, network, argument, and postcolonial debates address how present-day socio-spatial organization is formed, what needs to or should not trade, and the way it underscores whether or not a good plan will contribute to a given situation. Inside the absence of an agreed-upon technical justification for the planning exercise, the planning idea has a tendency to focus on normative processes, positioning making plans as an area for participatory democracy.

Keywords: environmental governance, environmental planning, environmental management, sustainable competitiveness, sustainability

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Authors: Toral Khalpada, Kanhai Joshi

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Generally, constructions of structures built in India are indeterminate structures. The purpose of this study is to investigate the application of a structure that is proved to be non-economical. The testing practice involves the application of different types of loads on both, determinate and indeterminate structure by computing it on a software system named Staad and also inspecting them practically on the construction site, analyzing the most efficient structure and diagnosing the utilization of the structure which is not so beneficial as compared to other. Redundant structures (indeterminate structure) are found to be more reasonable. All types of loads were applied on the beams of both determinate and indeterminate structures parallelly on the software and the same was done on the site practically which proved that maximum stresses in statically indeterminate structures are generally lower than those in comparable determinate structures. These structures are found to have higher stiffness resulting in lesser deformations so indeterminate structures are economical and are better than determinate structures to use for construction. On the other hand, statically determinate structures have the benefit of not producing stresses because of temperature changes. Therefore, our study tells that indeterminate structure is more beneficial but determinate structure also has used as it can be used in many areas; it can be used for the construction of two hinged arch bridges where two supports are sufficient and where there is no need for expensive indeterminate structure. Further investigation is needed to contrive more implementation of the determinate structure.

Keywords: construction, determinate structure, indeterminate structure, stress

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Authors: Somkait Udomhunsakul

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In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into sub-blocks and each block was identified the clearer regions by using the Spatial Frequency Measurement (SFM). Finally, the recovered fused image was reconstructed by performing the Inverse Wavelet Transform. From the experimental results, it was found that the proposed method outperformed the traditional SFM based methods in terms of objective and subjective assessments.

Keywords: multi-focus image fusion, wavelet packet, spatial frequency measurement

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Authors: D. Pazder

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The main assumption of the study is to examine the coherence between two aspects of spatial planning important in Poland. The first one is the need to realize a participatory planning paradigm, and the second is a global trend of the pro-ecological orientation of city development. The aim of the research is the verification of the possibility of finding the right balance between economic and socio-spatial dimensions of urban redefinition, especially within public green areas. The significance of the examination lies in the fact that there are a huge anthropopressure and overinvestment in downtown areas of big Polish cities. The methodology used in the research of a case study was the three-layered comparative analyses of spatial planning documents, participatory planning undertakings, soft and hard actions concerning a given area in the period of 2008-2020. The main findings are that there is a lack of satisfactory cooperation between the municipality and local communities, a connection between soft actions and investment in green public space, inhabitants are of high ecological consciousness but not so concerned about spatial planning legislation. The conclusion is that it is needed to provide real participation in spatial planning processes so as to take advantage of local communities’ activity and to combine more top-down and bottom-up actions so as to integrate people and educate them on how to act in favor of a common good in democratic citizenship.

Keywords: placemaking, participatory planning, anesthetization, public greenery

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Authors: Hong Lu, Xin Chen, Zhengcheng Fan

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Prior research has claimed a close association between handwriting and mathematics attainment with the help of spatial cognition. However, the exact mechanism behind this relationship remains un-investigated. Focusing on visual-motor integration (VMI), one critical spatial skill, this meta-analysis aims to estimate the size of the handwriting- visual-motor integration relationship and examine the moderating effect of handwriting dimensions on the link. With a random effect model, a medium relation (r=.26, 95%CI [.22, .30]) between handwriting and VMI was summarized in 38 studies with 55 unique samples and 141 effect sizes. Findings suggested handwriting dimensions significantly moderated the handwriting- VMI relationship, with handwriting legibility showing a substantial correlation with VMI, but neither handwriting speed nor pressure. Identifying the essential relationship between handwriting legibility and VMI, this study adds to the literature about the key cognitive processing needs underlying handwriting, and spatial cognition thus highlights the cognitive mechanism regarding handwriting, spatial cognition, and mathematics performances.

Keywords: handwriting, visual-motor integration, legibility, meta-analysis

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Authors: Shengdan Yang

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The outbreak of the COVID-19 pandemic in early 2020 has made public health issues to be re-examined. The value of green space configuration is an important measure of community health quality. By combining quantitative and qualitative methods, the structure and function of community green space can be better evaluated. This study selects Wuhan Kunhou Community as the site and proposes to analyze the daily health service function of the community's green infrastructure. Through GIS-based spatial analysis, case study, and field investigation, this study evaluates the accessibility of green infrastructure and discusses the ideal green space form based on health indicators. The findings show that Kunhou Community lacks access to green infrastructure and public space for daily activities. The research findings provide a bridge between public health indicators and community space planning and propose design suggestions for green infrastructure planning.

Keywords: accessibility, community health, GIS, green infrastructure

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Authors: Parisa Göker

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With the birth of Islam, the definitions of paradise in Quran have spread across three continents since 7^th century, showing itself in the palace gardens as a reflection of Islamic Culture. The design characteristics of Islamic gardens come forth with the influence of religious beliefs, as well as taking its form as per the cultural, climatic and soil characteristics of its geography, and showing its difference. It is possible to see these differences from the garden examples that survived to present time from the civilizations in the lands of Islamic proliferation. The main material of this research is the Islamic gardens in Iran and Spain. Field study was carried out in Alhambra Palace in Spain, Granada and Shah Goli garden in Iran, Tabriz. In this study, the birth of Islamic gardens, spatial perception of paradise, design principles, spatial structure, along with the structural/plantation materials used are examined. Also the characteristics and differentiation of the gardens examined in different cultures and geographies have been revealed. In the conclusion section, Iran and Spain Islamic garden samples were evaluated and their properties were determined.

Keywords: Islamic civilization, Islamic architecture, cultural landscape, Islamic garden

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Tyler Gill, Sophia Daniels

Abstract:

The paper examines how accessing the spatial-temporal constrains of data will help inform policymakers and law enforcement officials. The authors utilize Chicago crime data from 2006-2016 to demonstrate how the Emerging Hot Spot Tool is an ideal hot spot clustering approach to analyze crime data. Traditional approaches include density maps or creating a spatial weights matrix to include the spatial-temporal constrains. This new approach utilizes a space-time implementation of the Getis-Ord Gi* statistic to visualize the data more quickly to make better decisions. The research will help complement socio-cultural research to find key patterns to help frame future policies and evaluate the implementation of prior strategies. Through this analysis, homicide trends and patterns are found more effectively and recommendations for use by non-traditional users of GIS are offered for real life implementation.

Keywords: crime mapping, emerging hot spot analysis, Getis-Ord Gi*, spatial-temporal analysis

Procedia PDF Downloads 217

Authors: Matan Cohen, Maxim Shoshany

Abstract:

Climatic, topographic and geological diversity, together with frequent disturbance and recovery cycles, produce highly complex spatial patterns of trees, shrubs, dwarf shrubs and bare ground patches. Assessment of spatial and temporal variations of these life-forms patterns under climate change is of high ecological priority. Here we report on one of the first attempts to discriminate between images of three Mediterranean life-forms patterns at three densities. The development of an extensive database of orthophoto images representing these 9 pattern categories was instrumental for training and testing pre-trained and newly-trained DL models utilizing DenseNet architecture. Both models demonstrated the advantages of using Deep Learning approaches over existing spectral and spatial (pattern or texture) algorithmic methods in differentiation 9 life-form spatial mixtures categories.

Keywords: texture classification, deep learning, desert fringe ecosystems, climate change

Procedia PDF Downloads 57

Authors: A. Llopis Alvarez, D. Muller-Eie

Abstract:

Participatory GIS (geographic information systems) are designed for community mapping exercises in order to produce spatial representations of local knowledge. Ideally, participatory GIS caters to public participation through the use of spatial data in order to increase community-led policy-and decision-making. Having defined a spatial object, such as a neighborhood, subjective mapping involves attaining a description of the spatial, physical, social and psychological characteristics of that spatial object. This paper highlights an emerging appreciation of the subjective component, particularly in spatial analyses. The beliefs, feelings, and behaviors associated with an urban area reflect its sense of place for an individual or a group. It is important therefore to understand what types of beliefs, emotions, and behavioral patterns are relevant to particular resident, groups and urban scales. In this sense, resident’s emotional attachment to their urban areas motivates civic engagement and facilitates awareness of its strengths and its problems. Similarly, subjective perceptions act in complex ways to influence the formation and maintenance of social identity and quality of life. This paper reports on findings from a case study of immigrant population in Norwegian cities, their residential conditions and their relationship to quality of urban life. Cognitive mapping methodologies are used in this study to understand local perceptions of urban qualities. Thus, measures to alleviate disadvantages and improve quality of urban life are more likely to be effective when they are informed by an understanding of a place as constructed by those who live in it, meaning their subjective perceptions about it.

Keywords: mapping methodologies, participatory GIS, perceptual maps, public participation, spatial analysis, subjective perceptions

Procedia PDF Downloads 116