Search results for: spatial transformer network

Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Ł. Kaczmarek, T. Wejrzanowski, M. Maksimczuk

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The study presents the use of the numerical calculations based on high-resolution computed microtomography in analysis of fluid flow through Miocene sandstones. Therefore, the permeability studies of rocks were performed. Miocene samples were taken from well S-3, located in the eastern part of the Carpathian Foredeep. For aforementioned analysis, two series of X-ray irradiation were performed. The first set of samples was selected to obtain the spatial distribution of grains and pores. At this stage of the study length of voxel side amounted 27 microns. The next set of X-ray irradation enabled recognition of microstructural components as well as petrophysical features. The length of voxel side in this stage was up to 2 µm. Based on this study, the samples were broken down into two distinct groups. The first one represents conventional reservoir deposits, in opposite to second one - unconventional type. Appropriate identification of petrophysical parameters such as porosity and permeability of the formation is a key element for optimization of the reservoir development.

Keywords: grains, permeability, pores, pressure distribution

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Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno

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Banda Sea collision zone (BSCZ) of is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location in the eastern part of Indonesia. This zone has a very high seismic activity. In this research, we will be calculated rate (λ) and Mean Square Eror (MSE). By this result, we will identification of Poisson distribution of earthquakes in the BSCZ with the point process approach. Chi-square test approach and test Anscombe made in the process of identifying a Poisson distribution in the partition area. The data used are earthquakes with Magnitude ≥ 6 SR and its period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: molluca banda sea collision zone, earthquakes, mean square error, poisson distribution, chi-square test, anscombe test

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Authors: Muhardiyan Erawan, Zaenal Mutaqin

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Balingara River is one of the rivers with the type Gravel-Bed in Indonesia. Gravel-Bed Rivers easily deformed in a relatively short time due to several variables, that are climate (rainfall), river discharge, topography, rock types, and land cover. To determine stream channel changes in Balingara River used Landsat 7 and 8 and analyzed planimetric or two dimensions. Parameters to determine changes in the stream channel are sinuosity ratio, Brice Index, the extent of erosion and deposition. Changes in stream channel associated with changes in land cover then analyze with a descriptive analysis of spatial and temporal. The location of a stream channel has a low gradient in the upstream, and middle watershed with the type of rock in the form of gravel is more easily changed than other locations. Changes in the area of erosion and deposition influence the land cover changes.

Keywords: Brice Index, erosion, deposition, gravel-bed, land cover change, sinuosity ratio, stream channel change

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Authors: Chao-Ton Su, Li-Fei Chen

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The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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Authors: Chengyuan Zhu, Zhu Wang

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With the strategy of Rural Rejuvenation proposed in China, the rural has become the focus of all works today. In addition to the support of industry and policy, the rural planning and construction which is the space dependence of Rural Rejuvenation are also very crucial. Based on an analysis of the case of Yangdun Village in Deqing County, this paper summarizes village existing resources and construction status quo. It tries to illuminate the micro-activated organic renewal strategies and methods, based on ecological landscape, history context, industry development and living life requirements. It takes advantage of industrial linkage and then asks for the coordination of both spatial and industrial planning, the revival and remodeling of the rural image can be achieved through shaping the of architectural and landscape nodes as well as the activation of street space.

Keywords: rural construction, rural human settlements, micro-activation, organic renewal

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Authors: Bagus Indrawan Hardi

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Cellular Automata are widely used in land use modeling, it has been proven powerful to simulate land use change for small scale in many large cities in the world. In this paper, we try to implement CA for land use modeling in unique city in Indonesia, Karawang. Instead the complex numerical implementation, CA are simple, and it is accurate and also highly dependable on the on the rules (rule based). The most important to do in CA is how we form and calculate the neighborhood effect. The neighborhood effect represents the environment and relationship situation between the occupied cell and others. We adopted 196 cells of circular neighborhood with 8 cells of radius. For the results, CA works well in this study, we exhibit several analyzed and proceed of zoomed part in Karawang region. The rule set can handle the complexity in land use modeling. However, we cannot strictly believe of the result, many non-technical parameters, such as politics, natural disaster activities, etc. may change the results dramatically.

Keywords: cellular automata (CA), land use change, spatial dynamics, urban sprawl

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Authors: Aurore Cauquis, Philippe Heinrich, Mario Ricchiuto, Audrey Gailler

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In this talk, we look for an accurate time scheme to model the propagation of waves. Several numerical schemes have been developed to solve the extended weakly nonlinear weakly dispersive Boussinesq Equations. The temporal schemes used are two Lax-Wendroff schemes, second or third order accurate, two Runge-Kutta schemes of second and third order and a simplified third order accurate Lax-Wendroff scheme. Spatial derivatives are evaluated with fourth order accuracy. The numerical model is applied to two monodimensional benchmarks on a flat bottom. It is also applied to the simulation of the Algerian tsunami generated by a Mw=6 seism on the 18th March 2021. The tsunami propagation was highly dispersive and propagated across the Mediterranean Sea. We study here the effects of the order of temporal discretization on the accuracy of the results and on the time of computation.

Keywords: numerical analysis, tsunami propagation, water wave, boussinesq equations

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Authors: Aditya Verma

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E-voting using blockchain provides us with a distributed system where data is present on each node present in the network and is reliable and secure too due to its immutability property. This work compares various blockchain consensus algorithms used for e-voting applications in the past, based on performance and node scalability, and chooses the optimal one and improves on one such previous implementation by proposing solutions for the loopholes of the optimally working blockchain consensus algorithm, in our chosen application, e-voting.

Keywords: blockchain, parallel bft, consensus algorithms, performance

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Nadezda Sergunicheva, Victoria Vasilenko

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The emotional sphere is one of the most important aspects of the child's development and significant factor in his psychological well-being. Present research aims to identify the relationships between emotional characteristics of preschoolers and parameters of family interaction: emotional interaction, parental styles, family adaptation, and cohesion. The study involved 40 people from Saint-Petersburg: 20 children (10 boys and 10 girls) from 5 to 6 years, Mage = 5 years 4 months and 20 mothers. Methods used were: Test 'Emotional identification' by E.Izotova, Empathy test by T. Gavrilova, Children's fears test by A. Zakharov, M. Panfilova, 'Parent-child emotional interaction questionnaire' by E. Zakharova, 'Analysis of family relationships questionnaire by E. Eidemiller and V. Yustitskis, Family Adaptation and Cohesion Scales (FACES III) by D. X. Olson, J. Portner, I. Lavi. Сorrelation analysis revealed that the higher index of underdevelopment of parental feelings, the lower the child’s ability to identify emotions (p < 0,05), but at the same time, the higher ability to understand emotional states (p < 0,01), as in the case of hypoprotection (p < 0,05). Two last correlations can be explained by compensatory mechanism. This is also confirmed by negative correlations between maternal educational uncertainty and child’s ability to understand emotional states and between indulgence and child’s ability to perceive emotional states (p < 0,05). The more pronounced the phobia of a child's loss, the higher egocentric nature of child’s empathy (p < 0,05). The child’s fears have the greatest number of relationships with the characteristics of family interaction. The more pronounced mother’s positive feelings in interaction, emotional support, acceptance of himself as a parent, desire for physical contact with child and the more adaptive the family system, the less the total number of child’s fears (p < 0,05). The more the mother's ability to perceive the child's state, positive feelings in interaction, emotional support (p < 0,01), unconditional acceptance of the child, acceptance of himself as a parent and the desire for physical contact (p < 0,05), the less the amount child’s spatial fears. Socially-mediated fears are associated with less pronounced mother's positive feelings in interaction, less emotional support and deficiency of demands, obligations (p < 0,05). Fears of animals and fairy-tale characters positively correlated with the excessive demands, obligations and excessive sanctions (p < 0,05). The more emotional support (p < 0,01), mother's ability to perceive the child's state, positive feelings in interaction, unconditional acceptance of the child, acceptance of himself as a parent (p < 0,05), the less the amount child’s fears of nightmares. This kind of fears is positively correlated with excessive demands, prohibitions (p < 0,05). The more adaptive the family system (p < 0,01), the higher family cohesion, mother's acceptance of himself as a parent and preference to childish traits (p < 0,05), the less fear of death. Thus, the children's fears have the closest relationships with the characteristics of family interaction. The severity of fears, especially spatial, is connected, first of all, with the emotional side of the mother-parent interaction. Fears of animals and fairy-tale characters are associated with some characteristics of the parental styles, connected with the rigor of mothers. Correlations of the emotional identification are contradictory and require further clarification. Research is supported by RFBR №18-013-00990.

Keywords: emotional characteristics, family interaction, fears, parental styles, preschoolers

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Authors: W. Riahi, M. L. Mansour

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Using tools of data processing such as geographic information system (GIS) for the contribution of the space management becomes more and more frequent. It allows collecting and analyzing diverse natural information relative to the same territory. Space technologies play crucial role in agricultural phenomenon analysis. For this, satellite images treatment were used to classify vegetation density and particularly agricultural areas in Setif province by making recourse to the Normalized Difference Vegetation Index (NDVI). This step was completed by mapping agricultural activities of the province by using ArcGIS.10 software in order to display an overall view and to realize spatial analysis of various themes combined between them which are chosen according to their strategic importance in different thematic maps. The synthesis map elaborately showed that geographic information system can contribute significantly to agricultural management by describing potentialities and development opportunities of production systems and agricultural sectors.

Keywords: GIS, satellite image, agriculture, NDVI, thematic map

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Authors: Simone Galati, Adriano Troia

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Ultrasound (US) is widely used in medical field for a variety diagnostic techniques but, in recent years, it has also been creating great interest for therapeutic aims. Regarding drug delivery, the use of US as an activation source provides better spatial delivery confinement and limits the undesired side effects. However, at present there is no complete characterization at a fundamental level of the different signals produced by sono-activated nanocarriers. Therefore, the aim of this study is to obtain a metrological characterization of the cavitation phenomena induced by US through three parallel investigation approaches. US was focused into a channel of a customized phantom in which a solution with oxygen-loaded nanodroplets (OLNDs) was led to flow and the cavitation activity was monitored. Both quantitative and qualitative real-time analysis were performed giving information about the dynamics of bubble formation, oscillation and final implosion with respect to the working acoustic pressure and the type of nanodroplets, compared with pure water. From this analysis a possible interpretation of the observed results is proposed.

Keywords: cavitation, drug delivery, nanodroplets, ultra-sound

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Authors: Krzysztof Malczewski

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Magnetic Resonance Imaging (MRI) reconstruction algorithm using compressed sensing is presented in this paper. It is exhibited that the offered approach improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were conventionally assumed necessary. Magnetic Resonance Imaging (MRI) is a fundamental medical imaging method struggles with an inherently slow data acquisition process. The use of CS to MRI has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the objective is to combine super-resolution image enhancement algorithm with CS framework benefits to achieve high resolution MR output image. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. The presented algorithm considers the cardiac and respiratory movements.

Keywords: super-resolution, MRI, compressed sensing, sparse-sense, image enhancement

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Authors: Andreas Aagaard Nohr

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International Relations is an academic discipline which is rarely in direct contact with its field. However, there has in recent years been a growing interest in the different agents within and beyond the state and their associated practices; yet some of the research tools with which to study them are not widely used. This paper introduces video-observation as a method for the study of IR and argues that it offers a unique way of studying the complexity of the everyday context of actors. The paper is divided into two main parts: First, the philosophical and methodological underpinnings of the kind of data that video-observation produces are discussed; primarily through a discussion of the phenomenology of Husserl, Heidegger, and Merleau-Ponty. Second, taking simulation of a WTO negotiation round as an example, the paper discusses how the data created can be analysed: in particular with regard to the structure of events, the temporal and spatial organization of activities, rhythm and periodicity, and the concrete role of artefacts and documents. The paper concludes with a discussion of the ontological, epistemological, and practical challenges and limitations that ought to be considered if video-observation is chosen as a method within the field of IR.

Keywords: video-observation, phenomenology, international relations

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Authors: Cecilia Sosa, Fernanda Figueroa, Leonardo Calzada

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Biosphere reserves (BR) are considered as the main strategy for biodiversity and ecosystems conservation. Mexican BR are mainly inhabited by rural communities who strongly depend on forests and their resources. Even though the dual objective of conservation and development has been sought in BR, land cover change is a common process in these areas, while most rural communities are highly marginalized, partly as a result of restrictions imposed by conservation to the access and use of resources. Achieving ecosystems conservation and social development face serious challenges. Factors such as financial support for development projects (public/private), environmental conditions, infrastructure and regional economic conditions might influence both land use change and wellbeing. Examining the temporal trends of conservation and development in BR is central for the evaluation of outcomes for these conservation strategies. In this study, we analyzed changes in primary vegetation cover (as a proxy for conservation) and the index of marginalization (as a proxy for development) in Mexican BR (2000-2015); we also explore the influence of various factors affecting these trends, such as conservation-development projects financial support (public or private), geographical distribution in ecoregions (as a proxy for shared environmental conditions) and in economic zones (as a proxy for regional economic conditions). We developed a spatial analysis at the municipal scale (2,458 municipalities nationwide) in ArcGIS, to obtain road densities, geographical distribution in ecoregions and economic zones, the financial support received, and the percent of municipality area under protection by protected areas and, particularly, by BR. Those municipalities with less than 25% of area under protection were regarded as part of the protected area. We obtained marginalization indexes for all municipalities and, using MODIS in Google Earth Engine, the number of pixels covered by primary vegetation. We used a linear mixed model in RStudio for the analysis. We found a positive correlation between the marginalization index and the percent of primary vegetation cover per year (r=0.49-0.5); i.e., municipalities with higher marginalization also show higher percent of primary vegetation cover. Also, those municipalities with higher area under protection have more development projects (r=0.46) and some environmental conditions were relevant for percent of vegetation cover. Time, economic zones and marginalization index were all important. Time was particularly, in 2005, when both marginalization and deforestation decreased. Road densities and financial support for conservation-development projects were irrelevant as factors in the general correlation. Marginalization is still being affected by the conservation strategies applied in BR, even though that this management category considers both conservation and development of local communities as its objectives. Our results suggest that roads densities and support for conservation-development projects have not been a factor of poverty alleviation. As better conservation is being attained in the most impoverished areas, we face the dilemma of how to improve wellbeing in rural communities under conservation, since current strategies have not been able to leave behind the conservation-development contraposition.

Keywords: deforestation, local development, marginalization, protected areas

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Authors: Devika Tanna

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'Biometrics' means 'life measurement' but the term is usually associated with the use of unique physiological characteristics to identify an individual. It is important to secure the privacy of digital face image that is stored in central database. To impart privacy to such biometric face images, first, the digital face image is split into two host face images such that, each of it gives no idea of existence of the original face image and, then each cover image is stored in two different databases geographically apart. When both the cover images are simultaneously available then only we can access that original image. This can be achieved by using the XM2VTS and IMM face database, an adaptive algorithm for spatial greyscale. The algorithm helps to select the appropriate host images which are most likely to be compatible with the secret image stored in the central database based on its geometry and appearance. The encryption is done using GEVCS which results in a reconstructed image identical to the original private image.

Keywords: adaptive algorithm, database, host images, privacy, visual cryptography

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Authors: Mustaffa Kamal Bashar Mohd Fauzi, Puteri Shireen Jahn Kassim, Nurul Syala Abdul Latip

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It is increasingly realized that sustainability includes both a response to the climatic and cultural context of a place. To assess the cultural context, a morphological analysis of urban patterns from heritage legacies is necessary. While the climatic form is derived from an analysis of meteorological data, cultural patterns and forms must be abstracted from a typological and morphological study. This current study aims to analyzes morphological and formal elements of water-based architectural and urban design of past Islamic vernacular complexes in the hot arid regions and how a vast utilization of water was shaped and sited to act as cooling devices for an entire complex. Apart from its pleasant coolness, water can be used in an aesthetically way such as emphasizing visual axes, vividly enhancing the visual of the surrounding environment and symbolically portraying the act of purity in the design. By comparing 2 case studies based on the analysis of interactions of water features into the form, planning and morphology of 2 Islamic heritage complexes, Fatehpur Sikri (India) and Lahore Fort (Pakistan) with a focus on Shish Mahal of Lahore Fort in terms of their mass, architecture and urban planning, it is agreeable that water plays an integral role in their climatic amelioration via different methods of water conveyance system. Both sites are known for their substantial historical values and prominent for their sustainable vernacular buildings for example; the courtyard of Shish Mahal in Lahore fort are designed to provide continuous coolness by constructing various miniatures water channels that run underneath the paved courtyard. One of the most remarkable features of this system that all water is made dregs-free before it was inducted into these underneath channels. In Fatehpur Sikri, the method of conveyance seems differed from Lahore Fort as the need to supply water to the ridge where Fatehpur Sikri situated is become the major challenges. Thus, the achievement of supplying water to the palatial complexes is solved by placing inhabitable water buildings within the two supply system for raising water. The process of raising the water can be either mechanical or laborious inside the enclosed well and water rising houses. The studies analyzes and abstract the water supply forms, patterns and flows in 3-dimensional shapes through the actions of evaporative cooling and wind-induced ventilation under arid climates. Through the abstraction analytical and descriptive relational morphology of the spatial configurations, the studies can suggest the idealized spatial system that can be used in urban design and complexes which later became a methodological and abstraction tool of sustainability to suit the modern contemporary world.

Keywords: heritage site, Islamic vernacular architecture, water features, morphology, urban design

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Authors: Huda Algharib, Amal Algharib, Hanan Algharib, Ali Mohammad Alqudah

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Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.

Keywords: image registration, mutual information, image gradients, image transformations

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Authors: Majid Karimabadi, Ahmad Farzaneh Kore, Behnam Azadegan

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The evolution of magnetized quark gluon plasma (QGP) in the framework of magneto- hydrodynamics is the focus of our study. We are investigating the temporal and spatial evolution of QGP using a second order viscous hydrodynamic framework. The fluid is considered to be magnetized and subjected to the influence of a magnetic field that is generated during the early stages of relativistic heavy ion collisions. We assume boost invariance along the beam line, which is represented by the z coordinate, and fluid expansion in the x direction. Additionally, we assume that the magnetic field is perpendicular to the reaction plane, which corresponds to the y direction. The fluid is considered to have infinite electrical conductivity. To analyze this system, we solve the coupled Maxwell and conservation equations. By doing so, we are able to determine the time and space dependence of the energy density, velocity, and magnetic field in the transverse plane of the viscous magnetized hot plasma. Furthermore, we obtain the spectrum of hadrons and compare it with experimental data.

Keywords: QGP, magnetohydrodynamics, hadrons, conversation

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Authors: Robert L. Burdett, Bayan Bevrani

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Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways, these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

Keywords: capacity analysis, capacity expansion, railways, track sub division, track duplication

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Authors: Jiajia Peng, Jianqing Qiu, Jianjun Ren, Yu Zhao

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Background: Insufficient sleep has been focused on as a public health epidemic. However, a comprehensive analysis of disease trajectory associated with unhealthy sleep habits is still unclear currently. Objective: This study sought to comprehensively clarify the disease's trajectory in relation to the overall poor sleep pattern and unhealthy sleep behaviors separately. Methods: 410,682 participants with available information on sleep behaviors were collected from the UK Biobank at the baseline visit (2006-2010). These participants were classified as having high- and low risk of each sleep behavior and were followed from 2006 to 2020 to identify the increased risks of diseases. We used Cox regression to estimate the associations of high-risk sleep behaviors with the elevated risks of diseases, and further established diseases trajectory using significant diseases. The low-risk unhealthy sleep behaviors were defined as the reference. Thereafter, we also examined the trajectory of diseases linked with the overall poor sleep pattern by combining all of these unhealthy sleep behaviors. To visualize the disease's trajectory, network analysis was used for presenting these trajectories. Results: During a median follow-up of 12.2 years, we noted 12 medical conditions in relation to unhealthy sleep behaviors and the overall poor sleep pattern among 410,682 participants with a median age of 58.0 years. The majority of participants had unhealthy sleep behaviors; in particular, 75.62% with frequent sleeplessness, and 72.12% had abnormal sleep durations. Besides, a total of 16,032 individuals with an overall poor sleep pattern were identified. In general, three major disease clusters were associated with overall poor sleep status and unhealthy sleep behaviors according to the disease trajectory and network analysis, mainly in the digestive, musculoskeletal and connective tissue, and cardiometabolic systems. Of note, two circularity disease pairs (I25→I20 and I48→I50) showed the highest risks following these unhealthy sleep habits. Additionally, significant differences in disease trajectories were observed in relation to sex and sleep medication among individuals with poor sleep status. Conclusions: We identified the major disease clusters and high-risk diseases following participants with overall poor sleep health and unhealthy sleep behaviors, respectively. It may suggest the need to investigate the potential interventions targeting these key pathways.

Keywords: sleep, poor sleep, unhealthy sleep behaviors, disease trajectory, UK Biobank

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Authors: Osama Hidayat, Yoshitaka Kajiat

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Kabul is a city that is highly representative of Afghanistan’s rapid urbanization process. As the city rapidly expands, there are enormous challenges to the sustainable use of land resources. This paper evaluates land use change and urban spatial expansion, from 1950 to 2016, in Kabul the capital of Afghanistan, using satellite images, field observation, and socio-economic data. The discussion covers the reduction in rural-to-urban land conversion, the delineation of urban growth boundaries, arable land reclamation and the establishment of farmland protection areas, urban upgrading, and the investigation and prosecution of illegal construction. This paper considers the aspects of urbanization and land management systems in Afghanistan. Efficient frames are outlined in Kabul for the following elements: governmental self-restraint and policy modification. The paper concludes that Kabul’s sustainable land use practices can provide a reference for other cities in Afghanistan.

Keywords: urban land expansion, urbanization, land use policy, sustainable development

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Authors: Danuvasin Charoen

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The study investigates the business process and business model of GRABTAXI. The paper also discusses how the company implemented strategies to gain competitive advantages. The data is derived from the analysis of secondary data and the in-depth interviews among staffs, taxi drivers, and key customers. The findings indicated that the company’s competitive advantages come from being the first mover, emphasising on the ease of use and tangible benefits of application, and using network effect strategy.

Keywords: taxi, mobile application, innovative business model, Thailand

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Authors: Rashid Mahmood

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The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.

Keywords: IDS, cloud, naas, detection

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Authors: Richard O’Riordan, Saritha Unnikrishnan

Abstract:

Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

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Authors: Rupesh S. Gundewar, Kanchan C. Khare

Abstract:

Runoff contribution from urban areas is generally from manmade structures and few natural contributors. The manmade structures are buildings; roads and other paved areas whereas natural contributors are groundwater and overland flows etc. Runoff alleviation is done by manmade as well as natural storages. Manmade storages are storage tanks or other storage structures such as soakways or soak pits which are more common in western and European countries. Natural storages are catchment slope, infiltration, catchment length, channel rerouting, drainage density, depression storage etc. A literature survey on the manmade and natural storages/inflow has presented percentage contribution of each individually. Sanders et.al. in their research have reported that a vegetation canopy reduces runoff by 7% to 12%. Nassif et el in their research have reported that catchment slope has an impact of 16% on bare standard soil and 24% on grassed soil on rainfall runoff. Infiltration being a pervious/impervious ratio dependent parameter is catchment specific. But a literature survey has presented a range of 15% to 30% loss of rainfall runoff in various catchment study areas. Catchment length and channel rerouting too play a considerable role in reduction of rainfall runoff. Ground infiltration inflow adds to the runoff where the groundwater table is very shallow and soil saturates even in a lower intensity storm. An approximate percent contribution through this inflow and surface inflow contributes to about 2% of total runoff volume. Considering the various contributing factors in runoff it has been observed during a literature survey that integrated modelling approach needs to be considered. The traditional storm water network models are able to predict to a fair/acceptable degree of accuracy provided no interaction with receiving water (river, sea, canal etc), ground infiltration, treatment works etc. are assumed. When such interactions are significant then it becomes difficult to reproduce the actual flood extent using the traditional discrete modelling approach. As a result the correct flooding situation is very rarely addressed accurately. Since the development of spatially distributed hydrologic model the predictions have become more accurate at the cost of requiring more accurate spatial information.The integrated approach provides a greater understanding of performance of the entire catchment. It enables to identify the source of flow in the system, understand how it is conveyed and also its impact on the receiving body. It also confirms important pain points, hydraulic controls and the source of flooding which could not be easily understood with discrete modelling approach. This also enables the decision makers to identify solutions which can be spread throughout the catchment rather than being concentrated at single point where the problem exists. Thus it can be concluded from the literature survey that the representation of urban details can be a key differentiator to the successful understanding of flooding issue. The intent of this study is to accurately predict the runoff from impermeable areas from urban area in India. A representative area has been selected for which data was available and predictions have been made which are corroborated with the actual measured data.

Keywords: runoff, urbanization, impermeable response, flooding

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Manikandan Sathianarayanan, Pernaidu Pasala

Abstract:

This paper presents the results of our studies concerning the implementation and exploitation of a Geographical Information System (GIS) dedicated to the support and assistance of decisions requested by drought management. In this study on diverting of surplus water through canals, pond sand check dams in the study area was carried out. The remote sensing data and GIS data was used to identify the drought prone villages in sivaganga taluk and to generate present land use, drainage pattern as well as slope and contour. This analysis was carried out for diverting surplus water through proposed canal and pond. The results of the study indicate that if the surplus water from the ponds and streams are diverted to the drought villages in Sivaganga taluk, it will definitely improve the agricultural production due to availability of water in the ponds. The improvements in agricultural production will help to improve the economical condition of the farmers in the region.

Keywords: interlinking, spatial analysis, remote sensing, GIS

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Authors: John Dorrell, Matthew Ambrosia, Abilash

Abstract:

This paper employs econometric analysis to quantify the potential profit wind farms can receive by allocating excess wind energy to power bitcoin mining machines. Cryptocurrency mining consumes a substantial amount of electricity worldwide, and wind energy produces a significant amount of energy that is lost because of the intermittent nature of the resource. Supply does not always match consumer demand. By combining the weaknesses of these two technologies, we can improve efficiency and a sustainable path to mine cryptocurrencies. This paper uses historical wind energy from the ERCOT network in Texas and cryptocurrency data from 2000-2021, to create 4-year return on investment projections. Our research model incorporates the price of bitcoin, the price of the miner, the hash rate of the miner relative to the network hash rate, the block reward, the bitcoin transaction fees awarded to the miners, the mining pool fees, the cost of the electricity and the percentage of time the miner will be running to demonstrate that wind farms generate enough excess energy to mine bitcoin profitably. Excess wind energy can be used as a financial battery, which can utilize wasted electricity by changing it into economic energy. The findings of our research determine that wind energy producers can earn profit while not taking away much if any, electricity from the grid. According to our results, Bitcoin mining could give as much as 1347% and 805% return on investment with the starting dates of November 1, 2021, and November 1, 2022, respectively, using wind farm curtailment. This paper is helpful to policymakers and investors in determining efficient and sustainable ways to power our economic future. This paper proposes a practical solution for the problem of crypto mining energy consumption and creates a more sustainable energy future for Bitcoin.

Keywords: bitcoin, mining, economics, energy

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