Search results for: spatial imagery

Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino

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In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.

Keywords: hierarchical temporal memory, HTM, learning algorithms, machine learning, spatial pooler

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Authors: Musthaya Patchanee

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The study of Sanitary landfill in Bang Nok-khwaek municipality consists of two procedures. First, to survey and create the spatial database by using physical factor, environmental factor, economical factor and social factor to follow the method of Geographic information system: GIS, second, to analyze the proper spatial for allocating the sanitary landfill in Bang Nok-khwaek municipality by using Overlay techniques to calculate the weighting linear total in Arc GIS program. The study found that there are 2.49 sq.km. proper spatial for the sanitary landfill in Bang Nok-khwaek municipals city which is 66.76% of the whole area. The highest proper spatial is 0.02 sq.km. which is 0.54%, The high proper spatial is 0.3 sq.km. which is 8.04%, the moderate spatial is 1.62 sq.km. which is 43.43% and the low proper spatial is 0.55 sq.km. which is 14.75%. These results will be used as the guideline to select the sanitary landfill area in accordance with sanitation standard for Subdistrict Administrative Organization and Subbdistrict Municipality in Samut Songkhram provice.

Keywords: Geographic Information System (GIS), sanitary landfill, Bang Nok-Khwaek municipality, Subdistrict Administrative Organization

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Authors: Xiaofang Wei

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Harmful Algal Blooms are a recurrent disturbing occurrence in Lake Erie that has caused significant negative impacts on water quality and aquatic ecosystem around Great Lakes areas in the United States. Targeting the recent HAB events in western Lake Erie, this paper utilizes satellite imagery and hydrological modeling to monitor HAB cyanobacteria blooms and analyze the impacts of agricultural activities from Maumee watershed, the biggest watershed of Lake Erie and agriculture dominant.SWAT (Soil & Water Assessment Tool) Model for Maumee watershed was established with DEM, land use data, crop data layer, soil data, and weather data, and calibrated with Maumee River gauge stations data for streamflow and nutrients. Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) was applied to remove atmospheric attenuation and cyanobacteria Indices were calculated from Landsat OLI imagery to study the intensity of HAB events in the years 2015, 2017, and 2019. The agricultural practice and nutrients management within the Maumee watershed was studied and correlated with HAB cyanobacteria indices to study the relationship between HAB intensity and nutrient loadings. This study demonstrates that hydrological models and satellite imagery are effective tools in HAB monitoring and modeling in rivers and lakes.

Keywords: harmful algal bloom, landsat OLI imagery, SWAT, HAB cyanobacteria

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Authors: Rutuja Rajendra Ghadage

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Villages surrounding the city undergo the process of peri urbanization, which transforms their original village character. These villages undergo fast and unplanned physical growth and development. Due to the expansion of urban activities, peri-urban villages are experiencing extensive changes. Focusing on the peri-urban villages of Baramati city in Maharashtra, India, this paper assesses the nature and extent of spatial development and identifies the factors contributing to the rapid development of eleven sample Peri-urban villages. After reviewing similar studies, four indicators are selected to assess the spatial development of peri-urban villages; 1) population, 2) road network, 3) land use landcover change, and 4) built-up distribution. The spatial development of peri-urban villages of Baramati is uneven as few villages are still expanding or growing while few villages have started intensifying. The main factor for this development is the presence of industries and educational institutions. They have affected spatial development directly as well as indirectly. In the future, most of the peri-urban villages of Baramati will be in the intensification phase, so if this happens in an unplanned manner, it will create stress on services and facilities.

Keywords: factors and indicators of spatial development, peri urban villages, peri urbanization, spatial development

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Authors: Dibyendu Roy, V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

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Imaging of underwater objects is primarily conducted by acoustic imagery due to the severe attenuation of electro-magnetic waves in water. Acoustic imagery underwater has varied range of significant applications such as side-scan sonar, mine hunting sonar. It also finds utility in other domains such as imaging of body tissues via ultrasonography and non-destructive testing of objects. In this paper, we explore the feasibility of using active acoustic imagery in air and simulate phased array beamforming techniques available in literature for various array designs to achieve a suitable acoustic sensor array design for a portable mobile robot which can be applied to detect the presence/absence of anomalous objects in a room. The multi-path reflection effects especially in enclosed rooms and environmental noise factors are currently not simulated and will be dealt with during the experimental phase. The related hardware is designed with the same feasibility criterion that the developed system needs to be deployed on a portable mobile robot. There is a trade of between image resolution and range with the array size, number of elements and the imaging frequency and has to be iteratively simulated to achieve the desired acoustic sensor array design. The designed acoustic imaging array system is to be mounted on a portable mobile robot and targeted for use in surveillance missions for intruder alerts and imaging objects during dark and smoky scenarios where conventional optic based systems do not function well.

Keywords: acoustic sensor array, acoustic imagery, anomaly detection, phased array beamforming

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Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

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Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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Authors: Rubaiyea Uddin

Abstract:

The hippocampus, located in the limbic system, is most commonly known for its role in memory and spatial navigation (as cited in Brain Reward and Pathways). It maintains an especially important role in specifically episodic and declarative memory. The hippocampus has also recently been linked to dopamine, the reward pathway’s primary neurotransmitter. Since research has found that dopamine also contributes to memory consolidation and hippocampal plasticity, this neurotransmitter is potentially responsible for contributing to the hippocampus’s role in memory formation. In this experiment we tested to see the effect of tactile cues on spatial navigation for eight different mice. We used a radial arm that had one designated 'reward' arm containing sucrose. The presence or absence of bedding was our tactile cue. We attempted to see if the memory of that cue would enhance the mice’s memory of having received the reward in that arm. The results from our study showed there was no significant response from the use of tactile cues on spatial navigation on our 129 mice. Tactile cues therefore do not influence spatial navigation.

Keywords: mice, radial arm maze, memory, spatial navigation, tactile cues, hippocampus, reward, sensory skills, Alzheimer’s, neurodegnerative disease

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Authors: Ana Paula Camelo, Keila Sanches

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The Geographically Weighted Regression (GWR) was proposed in geography literature to allow relationship in a regression model to vary over space. In Brazil, the agricultural exploitation of the Cerrado Biome is the main cause of deforestation. In this study, we propose a methodology using geostatistical methods to characterize the spatial dependence of deforestation in the Cerrado based on agricultural production indicators. Therefore, it was used the set of exploratory spatial data analysis tools (ESDA) and confirmatory analysis using GWR. It was made the calibration a non-spatial model, evaluation the nature of the regression curve, election of the variables by stepwise process and multicollinearity analysis. After the evaluation of the non-spatial model was processed the spatial-regression model, statistic evaluation of the intercept and verification of its effect on calibration. In an analysis of Spearman’s correlation the results between deforestation and livestock was +0.783 and with soybeans +0.405. The model presented R²=0.936 and showed a strong spatial dependence of agricultural activity of soybeans associated to maize and cotton crops. The GWR is a very effective tool presenting results closer to the reality of deforestation in the Cerrado when compared with other analysis.

Keywords: deforestation, geographically weighted regression, land use, spatial analysis

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Authors: Rabia Munsaf Khan, Eshrat Fatima

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The analysis of the spatial extent and temporal change of vegetation cover using remotely sensed data is of critical importance to agricultural sciences. Pakistan, being an agricultural country depends on this resource as it makes 70% of the GDP. The case study is of Lal Suhanra National Park, which is not only the biggest forest reserve of Pakistan but also of Asia. The study is performed using different temporal images of Landsat. Also, the results of Landsat are cross-checked by using Sentinel-2 imagery as it has both higher spectral and spatial resolution. Vegetation can easily be detected using NDVI which is a common and widely used index. It is an important vegetation index, widely applied in research on global environmental and climatic change. The images are then classified to observe the change occurred over 15 years. Vegetation cover maps of 2000 and 2016 are used to generate the map of vegetation change detection for the respective years and to find out the changing pattern of vegetation cover. Also, the NDVI values aided in the detection of percentage decrease in vegetation cover. The study reveals that vegetation cover of the area has decreased significantly during the year 2000 and 2016.

Keywords: Landsat, normalized difference vegetation index (NDVI), sentinel 2, Greenland monitoring

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Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Dai Zhimei, Hua Chen

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The exploration of urban spatial evolution is an important part of urban development research. Therefore, the evolutionary modern Yangzhou urban spatial texture was taken as the research object, and Spatial Syntax was used as the main research tool, this paper explored Yangzhou spatial evolution law and its driving factors from the urban street network scale, district scale and street scale. The study has concluded that at the urban scale, Yangzhou urban spatial evolution is the result of a variety of causes, including physical and geographical condition, policy and planning factors, and traffic conditions, and the evolution of space also has an impact on social, economic, environmental and cultural factors. At the district and street scales, changes in space will have a profound influence on the history of the city and the activities of people. At the end of the article, the matters needing attention during the evolution of urban space were summarized.

Keywords: block, space syntax and methodology, street, urban space, Yangzhou

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Authors: Fangzheng Li, Xiong Li

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Significant differences in urban greening have occurred in Chinese cities, which accompanied with China's rapid urbanization. However, few studies focused on the spatial differentiation of urban greening in China with large amounts of data. The spatial differentiation pattern, spatial correlation characteristics and the distribution shape of urban green space ratio, urban green coverage rate and public green area per capita were calculated and analyzed, using Global and Local Moran's I using data from 289 cities in 2014. We employed Spatial Lag Model and Spatial Error Model to assess the impacts of urbanization process on urban greening of China. Then we used Geographically Weighted Regression to estimate the spatial variations of the impacts. The results showed: 1. a significant spatial dependence and heterogeneity existed in urban greening values, and the differentiation patterns were featured by the administrative grade and the spatial agglomeration simultaneously; 2. it revealed that urbanization has a negative correlation with urban greening in Chinese cities. Among the indices, the the proportion of secondary industry, urbanization rate, population and the scale of urban land use has significant negative correlation with the urban greening of China. Automobile density and per capita Gross Domestic Product has no significant impact. The results of GWR modeling showed that the relationship between urbanization and urban greening was not constant in space. Further, the local parameter estimates suggested significant spatial variation in the impacts of various urbanization factors on urban greening.

Keywords: China’s urbanization, geographically weighted regression, spatial differentiation pattern, urban greening

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Authors: O. Abusaeeda, J. P. O. Evans, D. Downes

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We demonstrate the synthesis of intermediary views within a sequence of X-ray images that exhibit depth from motion or kinetic depth effect in a visual display. Each synthetic image replaces the requirement for a linear X-ray detector array during the image acquisition process. Scale invariant feature transform, SIFT, in combination with epipolar morphing is employed to produce synthetic imagery. Comparison between synthetic and ground truth images is reported to quantify the performance of the approach. Our work is a key aspect in the development of a 3D imaging modality for the screening of luggage at airport checkpoints. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, KDE, view synthesis

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Authors: Jianjia Wang, Tong Yu, Haoran Zhu, Kun Liu, Jinwei Hao

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The underlying pattern in the modern city is agglomeration. To some degree, the distribution of urban spatial density can be used to describe the status of this assemblage. There are three intrinsic characteristics to measure urban spatial density, namely, Floor Area Ratio (FAR), Building Coverage Ratio (BCR), and Average Storeys (AS). But the underlying mechanism that contributes to these quantities is still vague in the statistical urban study. In this paper, we explore the corresponding extrinsic factors related to spatial density. These factors can further provide the potential influence on the intrinsic quantities. Here, we take Shanghai Inner Ring Area and Manhattan in New York as examples to analyse the potential impacts on urban spatial density with six selected extrinsic elements. Ebery single factor presents the correlation to the spatial distribution, but the overall global impact of all is still implicit. To handle this issue, we attempt to develop the Boltzmann statistical model to explicitly explain the mechanism behind that. We derive a corresponding novel quantity, called capacity, to measure the global effects of all other extrinsic factors to the three intrinsic characteristics. The distribution of capacity presents a similar pattern to real measurements. This reveals the nonlinear influence on the multi-factor relations to the urban spatial density in agglomeration.

Keywords: urban spatial density, Boltzmann statistics, multi-factor correlation, spatial distribution

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Authors: Lucas Derks, Christine Beenhakker, Michiel Brandt, Gert Arts, Ruud van Langeveld

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Background: The method Depression in Awareness Space (DAS) is a psychotherapeutic intervention technique based on the principles of spatial cognition and imagination therapy with spatial components. The basic assumptions are: mental space is the primary organizing principle in the mind, and all psychological issues can be treated by first locating and by next relocating the conceptualizations involved. The most clinical experience was gathered over the last 20 years in the area of social issues (with the social panorama model). The latter work led to the conclusion that a mental object (image) gains emotional impact when it is placed more central, closer and higher in the visual field – and vice versa. Changing the locations of mental objects in space thus alters the (socio-) emotional meaning of the relationships. The experience of depression seems always associated with darkness. Psychologists tend to see the link between depression and darkness as a metaphor. However, clinical practice hints to the existence of more literal forms of darkness. Aims: The aim of the method Depression in Awareness Space is to reduce the distress of clients with depression in the clinical counseling practice, as a reliable alternative method of psychological therapy for the treatment of depression. The method Depression in Awareness Space aims at making dark areas smaller, lighter and more transparent in order to identify the problem or the cause of the depression which lies behind the darkness. It was hypothesized that the darkness is a subjective side-effect of the neurological process of repression. After reducing the dark clouds the real problem behind the depression becomes more visible, allowing the client to work on it and in that way reduce their feelings of depression. This makes repression of the issue obsolete. Results: Clients could easily get into their 'sadness' when asked to do so and finding the location of the dark zones proved pretty easy as well. In a recent pilot study with five participants with mild depressive symptoms (measured on two different scales and tested against an untreated control group with similar symptoms), the first results were also very promising. If the mental spatial approach to depression can be proven to be really effective, this would be very good news. The Society of Mental Space Psychology is now looking for sponsoring of an up scaled experiment. Conclusions: For spatial cognition and the research into spatial psychological phenomena, the discovery of dark areas can be a step forward. Beside out of pure scientific interest, it is great to know that this discovery has a clinical implication: when darkness can be connected to depression. Also, darkness seems to be more than metaphorical expression. Progress can be monitored over measurement tools that quantify the level of depressive symptoms and by reviewing the areas of darkness.

Keywords: depression, spatial cognition, spatial imagery, social panorama

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Authors: Hira Jabbar

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Education is vital for inclusive growth of an economy and a critical contributor for investment in human capital. Like other developing countries, Pakistan is facing enormous challenges regarding the provision of public facilities, improper infrastructure planning, accelerating rate of population and poor accessibility. The influence of the rapid advancement and innovations in GIS and RS techniques have proved to be a useful tool for better planning and decision making to encounter these challenges. Therefore present study incorporates GIS and RS techniques to investigate the spatial distribution of school facilities, identifies settlements with served and unserved population, finds potential areas for new schools based on population and develops an accessibility index to evaluate the higher accessibility for schools. For this purpose high-resolution worldview imagery was used to develop road network, settlements and school facilities and to generate school accessibility for each level. Landsat 8 imagery was utilized to extract built-up area by applying pre and post-processing models and Landscan 2015 was used to analyze population statistics. Service area analysis was performed using network analyst extension in ArcGIS 10.3v and results were evaluated for served and underserved areas and population. An accessibility tool was used to evaluate a set of potential destinations to determine which is the most accessible with the given population distribution. Findings of the study may contribute to facilitating the town planners and education authorities for understanding the existing patterns of school facilities. It is concluded that GIS and remote sensing can be effectively used in urban transport and facility planning.

Keywords: accessibility, geographic information system, landscan, worldview

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Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Rubaiyea Uddin, Rebecca Taylor, Emily Levesque

Abstract:

The hippocampus, located in the limbic system, is most commonly known for its role in memory and spatial navigation (as cited in Brain Reward and Pathways). It maintains an especially important role in specifically episodic and declarative memory. The hippocampus has also recently been linked to dopamine, the reward pathway’s primary neurotransmitter. Since research has found that dopamine also contributes to memory consolidation and hippocampal plasticity, this neurotransmitter is potentially responsible for contributing to the hippocampus’s role in memory formation. In this experiment we tested to see the effect of tactile cues on spatial navigation for eight different mice. We used a radial arm that had one designated “reward” arm containing sucrose. The presence or absence of bedding was our tactile cue. We attempted to see if the memory of that cue would enhance the mice’s memory of having received the reward in that arm. The results from our study showed there was no significant response from the use of tactile cues on spatial navigation on our 129 mice. Tactile cues therefore do not influence spatial navigation.

Keywords: mice, radial arm maze, memory, spatial navigation, tactile cues, hippocampus, reward, sensory skills, Alzheimer's, neuro-degenerative diseases

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Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

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Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

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Authors: Zaqiatul Mardiah, Afdol Tharik Wastono, Abdul Muta'ali

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In general, the Arabic preposition ‘ala encodes the sense of UP-DOWN schema. However, the use of the preposition ‘ala can has many extended schemas that still have relation to its primary sense. In this paper, we show how the framework of cognitive linguistics (CL) based on image schemas can be applied to analyze the spatial semantic of the use of preposition ‘ala in the horizontal and vertical axes. The preposition ‘ala is usually used in the locative sense in which one physical entity is UP-DOWN relation to another physical entity. In spite of that, the cognitive analysis of ‘ala justifies the use of this preposition in many situations to seemingly encode non-up down-related spatial relations, and non-physical relation. This uncovers some of the unsolved issues concerning prepositions in general and the Arabic prepositions in particular the use of ‘ala as a sample. Using the Arabic corpus data, we reveal that in many cases and situations, the use of ‘ala is extended to depict relations other than the ones where the Trajector (TR) is actually in up-down relation to the Landmark (LM). The instances analyzed in this paper show that ‘ala encodes not only the spatial relations in which the TR and the LM are horizontally or vertically related to each other, but also non-spatial relations.

Keywords: image schema, preposition, spatial semantic, up-down relation

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Authors: Sarita Kumari, Ranjit Kumar Upadhyay

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This paper deals with plankton-fish dynamics where the fish population is growing logistically and nonlinearly harvested. The interaction between phytoplankton and zooplankton population is considered to be Crowley-Martin type functional response. It has been assumed that phytoplankton grows logistically and is affected by a space-dependent growth rate. Conditions for the existence of a positive equilibrium point and their stability analysis (both local and global) have been discussed for the non-spatial system. We have discussed maximum sustainable yields as well as optimal harvesting policy for maximizing the economic gain. The stability and existence of Hopf –bifurcation analysis have been discussed for the spatial system. Different conditions for turning pattern formation have been established through diffusion-driven instability analysis. Numerical simulations have been carried out for both non-spatial and spatial models. Phase plane analysis, the largest Lyapunov exponent, and bifurcation theory are used to numerically analyzed the non-spatial system. Our study shows that spatial heterogeneity, the mortality rate of phytoplankton, and constant harvesting of the fish population each play an important role in the dynamical behavior of the marine system.

Keywords: optimal harvesting, pattern formation, spatial heterogeneity, Crowley-Martin functional response

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Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

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Authors: Daijun Chen

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Affordable housing is subsidized by the government to meet the housing demand of low and middle-income urban residents in the process of urbanization and to alleviate the housing inequality caused by market-based housing reforms. It is a recognized fact that the living conditions of the insured have been improved while constructing the subsidized housing. However, the choice of affordable housing is mostly in the suburbs, where the surrounding urban functions and infrastructure are incomplete, resulting in the spatial mismatch of "jobs-housing" in affordable housing. The main reason for this problem is that the residents of affordable housing are more sensitive to the spatial location of their residence, but their selectivity and controllability to the housing location are relatively weak, which leads to higher commuting costs. Their real cost of living has not been effectively reduced. In this regard, 92 subsidized housing communities in Nanjing, China, are selected as the research sample in this paper. The residents of the affordable housing and their commuting Spatio-temporal behavior characteristics are identified based on the LBS (location-based service) data. Based on the spatial mismatch theory, spatial mismatch indicators such as commuting distance and commuting time are established to measure the spatial mismatch degree of subsidized housing in different districts of Nanjing. Furthermore, the geographically weighted regression model is used to analyze the influencing factors of the spatial mismatch of affordable housing in terms of the provision of employment opportunities, traffic accessibility and supporting service facilities by using spatial, functional and other multi-source Spatio-temporal big data. The results show that the spatial mismatch of affordable housing in Nanjing generally presents a "concentric circle" pattern of decreasing from the central urban area to the periphery. The factors affecting the spatial mismatch of affordable housing in different spatial zones are different. The main reasons are the number of enterprises within 1 km of the affordable housing district and the shortest distance to the subway station. And the low spatial mismatch is due to the diversity of services and facilities. Based on this, a spatial optimization strategy for different levels of spatial mismatch in subsidized housing is proposed. And feasible suggestions for the later site selection of subsidized housing are also provided. It hopes to avoid or mitigate the impact of "spatial mismatch," promote the "spatial adaptation" of "jobs-housing," and truly improve the overall welfare level of affordable housing residents.

Keywords: affordable housing, spatial mismatch, commuting characteristics, spatial adaptation, welfare benefits

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Authors: Lucie Pospíšilová, Robert Osman, Hana Porkertová

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The scholarly literature demonstrates disability and masculinity in conflict with each other. While disability is associated with dependence, weakness, or helplessness, masculinity is associated with independence, strength, and power. Thus, disabled masculinity might be a dilemma experienced on a personal level. The relationship between masculinity and disability is also interesting from a geographical point of view because the conception of space is gendered. In our society, the skills like spatial orientation, working with the maps, and navigation technologies as same as with scale are associated with masculinity. And because these skills are related to the visual imagination, it is the blindness that is associated with the limitation or even the absence of them. Thus, the conflict of masculinity and disability in the spatial experience is very well apparent in the case of visually impaired men. To study this conflict can tell us a lot not only about the experience of visually impaired men but also about the conception of space in geography and in our society. The paper uses Henri Lefebvre's theory of space based on a triad of spatial practice, representations of space, and representational space. It answers the question: How masculinity and disability intersect in the spatial experience of visually impaired men? The data come from research conducted in Brno and Prague (Czechia) in 2020 and 2021 and include 7 interviews and 6 go-alongs with visually impaired men.

Keywords: disability, masculinity, abstract space, spatial experience, visually impaired men

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Authors: Vaikunthan Rajaratnam

Abstract:

Intro: Motor imagery (MI) and mental practice (MP) can be an alternative to acquire mastery of surgical skills. One component of using this technique is the use of a mental script. The aim of this study was to design and develop a mental script for basic micro suturing training for skill acquisition using a low-fidelity rubber glove model and to describe the detailed methodology for this process. Methods: This study was based on a design and development research framework. The mental script was developed with 5 expert surgeons performing a cognitive walkthrough of the repair of a vertical opening in a rubber glove model using 8/0 nylon. This was followed by a hierarchal task analysis. A draft script was created, and face and content validity assessed with a checking-back process. The final script was validated with the recruitment of 28 participants, assessed using the Mental Imagery Questionnaire (MIQ). Results: The creation of the mental script is detailed in the full text. After assessment by the expert panel, the mental script had good face and content validity. The average overall MIQ score was 5.2 ± 1.1, demonstrating the validity of generating mental imagery from the mental script developed in this study for micro suturing in the rubber glove model. Conclusion: The methodological approach described in this study is based on an instructional design framework to teach surgical skills. This MP model is inexpensive and easily accessible, addressing the challenge of reduced opportunities to practice surgical skills. However, while motor skills are important, other non-technical expertise required by the surgeon is not addressed with this model. Thus, this model should act a surgical training augment, but not replace it.

Keywords: mental script, motor imagery, cognitive walkthrough, verbal protocol analysis, hierarchical task analysis

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Authors: Guangtong Xu, Yi He

Abstract:

Like most historic and cultural cities in China, the historic urban area of Jingmen city is facing a typical spatial problem of fragmentation and fuzzification. This study focuses on exploring a method for evaluating the existing values of historic urban area based on spatial prototype, a concept introduced into urban morphology from 'Archetype' in architectural typology. As the spatial elements and built-up relationship of historic city, spatial prototype has habitual structural characteristics and formal modulus. It is the inherent logic and order rules behind the scattered historic environment, providing a clue to understand the spatial characteristics and a basis for guiding the construction and conservation in historic urban areas. Three criteria, the resolution of historical elements, the completeness of historical structure and the renewal potential of associated land, were selected to construct the integrated assessment system. These three dimensions are linked to the spatial prototype and its constituent elements, as well as the transformation relationship in ancient and present day. The results showed that historic urban areas have changed from a holistic city to different existing types dominated by their historic structure elements. It is necessary to improve the pertinence of planning strategies and develop diversified management measures in the conservation scope of historic urban area. Moreover, a constructive-conservation strategy should be put forward to enhance the integrity of historic urban area based on the trace of spatial prototype and evaluation results.

Keywords: constructive conservation, existing value, historic urban area, spatial prototype

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Authors: Zohra Mekranfar, Ahmed Saidi, Abdellah Mebrek

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This work aims to develop multi-criteria decision making (MCDM) and spatial data warehouse (SDW) methods, which will be integrated into a GIS according to a ‘GIS dominant’ approach. The GIS operating tools will be operational to operate the SDW. The MCDM methods can provide many solutions to a set of problems with various and multiple criteria. When the problem is so complex, integrating spatial dimension, it makes sense to combine the MCDM process with other approaches like data mining, ascending analyses, we present in this paper an experiment showing a geo-decisional methodology of SWD construction, On-line analytical processing (OLAP) technology which combines both basic multidimensional analysis and the concepts of data mining provides powerful tools to highlight inductions and information not obvious by traditional tools. However, these OLAP tools become more complex in the presence of the spatial dimension. The integration of OLAP with a GIS is the future geographic and spatial information solution. GIS offers advanced functions for the acquisition, storage, analysis, and display of geographic information. However, their effectiveness for complex spatial analysis is questionable due to their determinism and their decisional rigor. A prerequisite for the implementation of any analysis or exploration of spatial data requires the construction and structuring of a spatial data warehouse (SDW). This SDW must be easily usable by the GIS and by the tools offered by an OLAP system.

Keywords: data warehouse, GIS, MCDM, SOLAP

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Authors: Caiwei Zhu, Remke Klapwijk

Abstract:

Spatial thinking, a way of thinking based on the understanding and reasoning of spatial concepts and representations, is embedded in science, technology, engineering, arts, and mathematics (STEAM) learning. Aside from many studies that successfully used targeted training to improve students’ spatial thinking skills, few have closely examined how spatial thinking can be trained in classroom settings. Design and technology education, which receives increasing attention towards its integration into formal curriculums, inherently encompasses a wide range of spatial activities, such as constructing mental representations of design ideas, mentally transforming objects and materials to form designs, visually communicating design plans through annotated drawings, and creating 2D and 3D design artifacts. Among different design topics, biomimicry offers a unique avenue for students to recognize and analyze the shapes and structures in nature. By mapping the forms of plants and animals onto functions, students gain inspiration to solve human design challenges. This study is one of the first to highlight opportunities for training spatial thinking in a biomimicry design project for primary school students. Embracing methodological principles of educational design-based research, this case study is conducted along with iterations in the design of the intervention and collaboration with teachers. Data are harvested from small groups of 10- to 12-year-olds at an international school in the Netherlands. Classroom videos, semi-structured interviews with students, design drawings and artifacts, formative assessment, and the pre- and post-intervention spatial test triangulate evidence for students' spatial thinking. In addition to contributing to a theory of integrating spatial thinking in the primary curriculum, mechanisms underlying such improvement in spatial thinking are explored and discussed.

Keywords: biomimicry, design and technology education, primary education, spatial thinking

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