Search results for: spatial audio processing

Authors: K. Zhumadilov, P. Kazymbet, A. Ivannikov, M. Bakhtin, A. Akylbekov, K. Kadyrzhanov, A. Morzabayev, M. Hoshi

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The aim of the study is to evaluate the possible excess of dose received by uranium processing plant workers. The possible excess of dose of workers was evaluated with comparison with population pool (Stepnogorsk) and control pool (Astana city). The measured teeth samples were extracted according to medical indications. In total, twenty-seven tooth enamel samples were analyzed from the residents of Stepnogorsk city (180 km from Astana city, Kazakhstan). About 6 tooth samples were collected from the workers of uranium processing plant. The results of tooth enamel dose estimation show us small influence of working conditions to workers, the maximum excess dose is less than 100 mGy. This is pilot study of EPR dose estimation and for a final conclusion additional sample is required.

Keywords: EPR dose, workers, uranium mines, tooth samples

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Authors: Chitresh Kumar, Santanu Gupta

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The research work intends to understand the process of initiation, planning and development of capital-intensive urban area level infrastructure development in East Asian Cities (specific to Indian Cities). With the onset of emphasis on sustainable urban transport, self-financed urban local bodies, it has become of utmost important to identify infrastructure and projects on a priority basis, which provide optimal utility to the urban area. Through identification of Spatial, Demographic and Socio-Economic and Political Instability Parameters and their trends for the past 60 years at the urban area and state level, the paper attempts to identify the most suitable time period when initiation of the project would become economically and demographically viable for the city.

Keywords: urban planning, regional planning, mass transit, infrastructure development, spatial planning

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Authors: Alemaw Kefale, Aramde Fetene, Hayal Desta

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Monitoring the amount of green space in urban areas is important for ensuring sustainable development and proper management. The study analyzed changes in urban green space coverage over the past 20 years in two rapidly urbanizing cities in Ethiopia, Debre Berhan and Debre Markos, using GIS and remote sensing. The researchers used Landsat 5 and 8 data with a spatial resolution of 30 m to determine different land use and land cover classes, including urban green spaces, barren and croplands, built-up areas, and water bodies. The classification accuracy ranged between 90% and 91.4%, with a Kappa Statistic of 0.85 to 0.88. The results showed that both cities experienced significant decreases in vegetation cover in their urban cores between 2000 and 2020, with radical changes observed from green spaces and croplands to built-up areas. In Debre Berhan, barren and croplands decreased by 32.96%, while built-up and green spaces increased by 357.9% and 37.4%, respectively, in 2020. In Debre Markos, built-up areas increased by 224.2%, while green spaces and barren and croplands decreased by 41% and 5.71%, respectively. The spatial structure of cities and planning policies were noticed as the major factors for big green cover change. Thus it has an implication for other rapidly urbanized cities in Africa and Asia. Overall, rapid urbanization threatens green spaces and agricultural areas, highlighting the need for ecological-based spatial planning in rapidly urbanizing cities.

Keywords: green space coverage, GIS and remote sensing, Landsat, LULC, Ethiopia

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Authors: A. Abdullah, S. Abushalmat, A. Bakshwain, A. Basuhail, A. Aslam

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GIS (Geographic Information System) applications require geo-referenced data, this data could be available as databases or in the form of digital or hard-copy agro-meteorological maps. These parameter maps are color-coded with different regions corresponding to different parameter values, converting these maps into a database is not very difficult. However, text and different planimetric elements overlaid on these maps makes an accurate image to database conversion a challenging problem. The reason being, it is almost impossible to exactly replace what was underneath the text or icons; thus, pointing to the need for inpainting. In this paper, we propose a probabilistic inpainting approach that uses the probability of spatial locality of colors in the map for replacing overlaid elements with underlying color. We tested the limits of our proposed technique using non-textual simulated data and compared text removing results with a popular image editing tool using public domain data with promising results.

Keywords: noise, image, GIS, digital map, inpainting

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Authors: Pei-Chih Wu, Hsin-Chih Lai, Yung-Lung Lee, Yun-Yao Chi, Ching-Yi Horng, Hsien-Chang Wang

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The impact of climate change to health has always been well documented. Amongst them, water-borne infectious diseases, chronic adverse effects or cancer risks due to chemical contamination in flooding or drought events are especially important in river basin. This study therefore utilizes GIS and different models to integrate demographic, land use, disaster prevention, social-economic factors, and human health assessment in the Erren River basin. Therefore, through the collecting of climatic, demographic, health surveillance, water quality and other water monitoring data, potential risks associated with the Erren River Basin are established and to understand human exposure and vulnerability in response to climate extremes. This study assesses the temporal and spatial patterns of melioidosis (2000-2015) and various cancer incidents in Tainan and Kaohsiung cities. The next step is to analyze the spatial association between diseases incidences, climatic factors, land uses, and other demographic factors by using ArcMap and GeoDa. The study results show that amongst all melioidosis cases in Taiwan, 24% cases (115) residence occurred in the Erren River basin. The relationship between the cases and in Tainan and Kaohsiung cities are associated with population density, aging indicator, and residence in Erren River basin. Risks from flooding due to heavy rainfall and fish farms in spatial lag regression are also related. Through liver cancer, the preliminary analysis in temporal and spatial pattern shows an increases pattern in annual incidence without clusters in Erren River basin. Further analysis of potential cancers connected to heavy metal contamination from water pollution in Erren River is established. The final step is to develop an assessment tool for human exposure from water contamination and vulnerability in response to climate extremes for the second year.

Keywords: climate change, health impact, health adaptation, Erren River Basin

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Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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Authors: Arash Rahmani, Ahmad Ghanbari, Abbas Baghernezhad, Babak Safaei

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In the design of parallel manipulators, usually mean value of a dexterity measure over the workspace volume is considered as the objective function to be used in optimization algorithms. The mentioned indexes in a hybrid parallel manipulator (HPM) are quite complicated to solve thanks to infinite solutions for every point within the workspace of the redundant manipulators. In this paper, spatial isotropic design axioms are extended as a well-known method for optimum design of manipulators. An upper limit for the isotropy measure of HPM is calculated and instead of computing and minimizing isotropy measure, minimizing the obtained limit is considered. To this end, two different objective functions are suggested which are obtained from objective functions of comprising modules. Finally, by using genetic algorithm (GA), the best geometric parameters for a specific hybrid parallel robot which is composed of two modified Gough-Stewart platforms (MGSP) are achieved.

Keywords: hybrid manipulator, spatial isotropy, genetic algorithm, optimum design

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Authors: Lin Dong, Fei Shi

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Based on the railway network and the principles of space syntax, the study attempts to reconstruct the spatial relationship of the passenger network connections from space and time perspective. According to the travel time data of main stations in the Yangtze River Delta urban agglomeration obtained by the Internet, the topological drawing of railway network under different time sections is constructed. With the comprehensive index composed of connection and integration, the accessibility and network operation efficiency of the railway network in different time periods is calculated, while the fairness of the network is analyzed by the fairness indicators constructed with the integration and location entropy from the perspective of horizontal and vertical fairness respectively. From the analysis of the efficiency and fairness of the railway passenger transport network, the study finds: (1) There is a strong regularity in regional system accessibility change; (2) The problems of efficiency and fairness are different in different time periods; (3) The improvement of efficiency will lead to the decline of horizontal fairness to a certain extent, while from the perspective of vertical fairness, the supply-demand situation has changed smoothly with time; (4) The network connection efficiency of Shanghai, Jiangsu and Zhejiang regions is higher than that of the western regions such as Anqing and Chizhou; (5) The marginalization of Nantong, Yancheng, Yangzhou, Taizhou is obvious. The study explores the application of spatial syntactic theory in regional traffic analysis, in order to provide a reference for the development of urban agglomeration transportation network.

Keywords: spatial syntax, the Yangtze River Delta, railway passenger time, efficiency and fairness

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Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet

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In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.

Keywords: dropwise condensation, textured surface, image processing, watershed

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Authors: S. K. Khosrowshahi, E. Güler

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This study investigates the reinforcement function of geosynthetics on the shear strength and strain profile of sand. Conducting a series of simple shear tests, the shearing behavior of the samples under static and cyclic loads was evaluated. Three different types of geosynthetics including geotextile and geonets were used as the reinforcement materials. An image processing analysis based on the optical flow method was performed to measure the lateral displacements and estimate the shear strains. It is shown that besides improving the shear strength, the geosynthetic reinforcement leads a remarkable reduction on the shear strains. The improved layer reduces the required thickness of the soil layer to resist against shear stresses. Consequently, the geosynthetic reinforcement can be considered as a proper approach for the sustainable designs, especially in the projects with huge amount of geotechnical applications like subgrade of the pavements, roadways, and railways.

Keywords: image processing, soil reinforcement, geosynthetics, simple shear test, shear strain profile

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Authors: Nirmal Sugathan, Santosh Maruthy

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Background: A considerable number of studies have evidenced that phonological encoding (PE) and working memory (WM) skills operate differently in adults who stutter (AWS). In order to tap these skills, several paradigms have been employed such as phonological priming, phoneme monitoring, and nonword repetition tasks. This study, however, utilizes a word jumble paradigm to assess both PE and WM using different modalities and this may give a better understanding of phonological processing deficits in AWS. Aim: The present study investigated PE and WM abilities in conjunction with lexical access in AWS using jumbled words. The study also aimed at investigating the effect of increase in cognitive load on phonological processing in AWS by comparing the speech reaction time (SRT) and accuracy scores across various syllable lengths. Method: Participants were 11 AWS (Age range=19-26) and 11 adults who do not stutter (AWNS) (Age range=19-26) matched for age, gender and handedness. Stimuli: Ninety 3-, 4-, and 5-syllable jumbled words (JWs) (n=30 per syllable length category) constructed from Kannada words served as stimuli for jumbled word paradigm. In order to generate jumbled words (JWs), the syllables in the real words were randomly transpositioned. Procedures: To assess PE, the JWs were presently visually using DMDX software and for WM task, JWs were presented through auditory mode through headphones. The participants were asked to silently manipulate the jumbled words to form a Kannada real word and verbally respond once. The responses for both tasks were audio recorded using record function in DMDX software and the recorded responses were analyzed using PRAAT software to calculate the SRT. Results: SRT: Mann-Whitney test results demonstrated that AWS performed significantly slower on both tasks (p < 0.001) as indicated by increased SRT. Also, AWS presented with increased SRT on both the tasks in all syllable length conditions (p < 0.001). Effect of syllable length: Wilcoxon signed rank test was carried out revealed that, on task assessing PE, the SRT of 4syllable JWs were significantly higher in both AWS (Z= -2.93, p=.003) and AWNS (Z= -2.41, p=.003) when compared to 3-syllable words. However, the findings for 4- and 5-syllable words were not significant. Task Accuracy: The accuracy scores were calculated for three syllable length conditions for both PE and PM tasks and were compared across the groups using Mann-Whitney test. The results indicated that the accuracy scores of AWS were significantly below that of AWNS in all the three syllable conditions for both the tasks (p < 0.001). Conclusion: The above findings suggest that PE and WM skills are compromised in AWS as indicated by increased SRT. Also, AWS were progressively less accurate in descrambling JWs of increasing syllable length and this may be interpreted as, rather than existing as a uniform deficiency, PE and WM deficits emerge when the cognitive load is increased. AWNS exhibited increased SRT and increased accuracy for JWs of longer syllable length whereas AWS was not benefited from increasing the reaction time, thus AWS had to compromise for both SRT and accuracy while solving JWs of longer syllable length.

Keywords: adults who stutter, phonological ability, working memory, encoding, jumbled words

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Authors: Khen Cohen, Daniel Yankelevich, David Mendlovic, Dan Raviv

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We present a 3D stereo system for high-resolution sensing in both the spatial and the temporal domains by combining a frame-based camera and an event-based camera. We establish a method to merge both devices into one unite system and introduce a calibration process, followed by a correspondence technique and interpolation algorithm for 3D reconstruction. We further provide quantitative analysis about our system in terms of depth resolution and additional parameter analysis. We show experimentally how our system performs temporal super-resolution up to effectively 1ms and can detect fast-moving objects and human micro-movements that can be used for micro-expression analysis. We also demonstrate how our method can extract colored events for an event-based camera without any degradation in the spatial resolution, compared to a colored filter array.

Keywords: DVS-CIS stereo vision, micro-movements, temporal super-resolution, 3D reconstruction

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Authors: Mahdi Almaky

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The thermostabilization of High Density Polyethylene (HDPE) is realized through the action of primary antioxidant such as phenolic antioxidants and secondary antioxidants as aryl phosphates. The efficiency of two secondary antioxidants, commercially named Irgafos 168 and Weston 399, was investigated using different physical, mechanical, spectroscopic, and calorimetric methods. The effect of both antioxidants on the processing stability and long term stability of HDPE produced in Ras Lanuf oil and gas processing Company were measured and compared. The combination of Irgafos 168 with Irganox 1010, as used in smaller concentration, results in a synergetic effect against thermo-oxidation and protect better than the combination of Weston 399 with Irganox 1010 against the colour change at processing temperature and during long term oxidation process.

Keywords: thermostabilization, high density polyethylene, primary antioxidant, phenolic antioxidant, Irgafos 168, Irganox 1010, Weston 399

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Authors: Narjes Abbasabadi

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As the world continues to urbanize and suburbanize, where suburbanization associated with mass sprawl has been the dominant form of this expansion, sustainable development challenges will be more concerned. Sprawling, characterized by low density and automobile dependency, presents significant environmental issues regarding energy consumption and Co2 emissions. This paper examines the vertical expansion of suburbs integrated into mass transit nodes as a planning strategy for boosting density, intensification of land use, conversion of single family homes to multifamily dwellings or mixed use buildings and development of viable alternative transportation choices. It analyzes the spatial patterns of tall building transit-oriented development (TB-TOD) of suburban regions in Sydney (Australia), Toronto (Canada), and Washington D.C. (United States). The main objectives of this research seek to understand the effect of the new morphology of suburban tall, the physical dimensions of individual buildings and their arrangement at a larger scale with energy efficiency. This study aims to answer these questions: 1) why and how can the potential phenomenon of vertical expansion or high-rise development be integrated into suburb settings? 2) How can this phenomenon contribute to an overall denser development of suburbs? 3) Which spatial pattern or typologies/ sub-typologies of the TB-TOD model do have the greatest energy efficiency? It addresses these questions by focusing on 1) energy, heat energy demand (excluding cooling and lighting) related to design issues at two levels: macro, urban scale and micro, individual buildings—physical dimension, height, morphology, spatial pattern of tall buildings and their relationship with each other and transport infrastructure; 2) Examining TB-TOD to provide more evidence of how the model works regarding ridership. The findings of the research show that the TB-TOD model can be identified as the most appropriate spatial patterns of tall buildings in suburban settings. And among the TB-TOD typologies/ sub-typologies, compact tall building blocks can be the most energy efficient one. This model is associated with much lower energy demands in buildings at the neighborhood level as well as lower transport needs in an urban scale while detached suburban high rise or low rise suburban housing will have the lowest energy efficiency. The research methodology is based on quantitative study through applying the available literature and static data as well as mapping and visual documentations of urban regions such as Google Earth, Microsoft Bing Bird View and Streetview. It will examine each suburb within each city through the satellite imagery and explore the typologies/ sub-typologies which are morphologically distinct. The study quantifies heat energy efficiency of different spatial patterns through simulation via GIS software.

Keywords: energy efficiency, spatial pattern, suburb, tall building transit-oriented development (TB-TOD)

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Authors: Phawin Sangsuvan, Chutimet Srinilta

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This Paper presents the applications of Particle Swarm Optimization (PSO) Method for Thai optical character recognition (OCR). OCR consists of the pre-processing, character recognition and post-processing. Before enter into recognition process. The Character must be “Prepped” by pre-processing process. The PSO is an optimization method that belongs to the swarm intelligence family based on the imitation of social behavior patterns of animals. Route of each particle is determined by an individual data among neighborhood particles. The interaction of the particles with neighbors is the advantage of Particle Swarm to determine the best solution. So PSO is interested by a lot of researchers in many difficult problems including character recognition. As the previous this research used a Projection Histogram to extract printed digits features and defined the simple Fitness Function for PSO. The results reveal that PSO gives 67.73% for testing dataset. So in the future there can be explored enhancement the better performance of PSO with improve the Fitness Function.

Keywords: character recognition, histogram projection, particle swarm optimization, pattern recognition techniques

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Authors: Qi Kan, Xiaoyu Ying

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With a rapid urbanization in China, the high-density new urban-center districts have already changed the microclimate in the city. Because of the using characters of building the commercial pedestrian streets which have emerged massively making a large number of pedestrians appear in there, pedestrian comfort in the commercial streets of the new urban-center districts requires more attention. The different street spatial layout will change the wind environment in the street and then influence the pedestrian comfort. Computational fluid dynamics (CFD) models are used to study the correlation between the street aspect ratio and wind environment, under the simulation with relevant weather conditions. The results show that the wind speed in the city streets is inversely proportional to the street aspect ratio. The conclusion will provide an evaluation basis for urban planners and architects at the beginning stage of the design to effectively avoid the potential poor physical environment.

Keywords: street spatial layout, wind environment, street aspect ratio, pedestrian comfort

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Authors: B. Hekner, J. Myalski, P. Wrzesniowski

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This study presents aluminum matrix composites reinforced by glassy carbon (GC) and titanium (Ti). In the first step, the heterophase (GC+Ti), spatial form (similar to skeleton) of reinforcement was obtained via own method. The polyurethane foam (with spatial, open-cells structure) covered by suspension of Ti particles in phenolic resin was pyrolyzed. In the second step, the prepared heterogeneous foams were infiltrated by aluminium alloy. The manufactured composites are designated to industrial application, especially as a material used in tribological field. From this point of view, the glassy carbon was applied to stabilise a coefficient of friction on the required value 0.6 and reduce wear. Furthermore, the wear can be limited due to titanium phase application, which reveals high mechanical properties. Moreover, fabrication of thin titanium layer on the carbon skeleton leads to reduce contact between aluminium alloy and carbon and thus aluminium carbide phase creation. However, the main modification involves the manufacturing of reinforcement in the form of 3D, skeleton foam. This kind on reinforcement reveals a few important advantages compared to classical form of reinforcement-particles: possibility to control homogeneity of reinforcement phase in composite material; low-advanced technique of composite manufacturing- infiltration; possibility to application the reinforcement only in required places of material; strict control of phase composition; High quality of bonding between components of material. This research is founded by NCN in the UMO-2016/23/N/ST8/00994.

Keywords: metal matrix composites, MMC, glassy carbon, heterophase composites, tribological application

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Authors: Rachel Hetherington, Chad Deering, Ann Maclean, Snehamoy Chatterjee

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The U.S. Geological Survey conducted a soil survey and subsequent mineralogical and geochemical analyses of over 4800 samples taken across the contiguous United States between the years 2007 and 2013. At each location, samples were taken from the top 5 cm, the A-horizon, and the C-horizon. Many studies have looked at the correlation between the mineralogical and geochemical content of soils and influencing factors such as parent lithology, climate, soil type, and age, but it seems little has been done in relation to quantifying and assessing the correlation between elements in the soil on a national scale. GIS was used for the mapping and multivariate interpolation of over 40 major and trace elements for surficial soils (0-5 cm depth). Qualitative analysis of the spatial distribution across the U.S. shows distinct patterns amongst elements both within the same periodic groups and within different periodic groups, and therefore with different behavioural characteristics. Results show the emergence of 4 main patterns of high concentration areas: vertically along the west coast, a C-shape formed through the states around Utah and northern Arizona, a V-shape through the Midwest and connecting to the Appalachians, and along the Appalachians. The Band Collection Statistics tool in GIS was used to quantitatively analyse the geochemical raster datasets and calculate a correlation matrix. Patterns emerged, which were not identified in qualitative analysis, many of which are also amongst elements with very different characteristics. Preliminary results show 41 element pairings with a strong positive correlation ( ≥ 0.75). Both qualitative and quantitative analyses on this scale could increase knowledge on the relationships between element distribution and behaviour in surficial soils of the U.S.

Keywords: correlation matrix, geochemical analyses, spatial distribution of elements, surficial soils

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Authors: Jiajun Lu, Yun Ma

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As a member of the tertiary industry, tourism is an important driving factor for urban economic development. As a well-known tourist city in China, according to statistics, the added value of tourism and related industries in 2022 will reach 106.326 billion yuan, a year-on-year increase of 1.2%, accounting for 3.7% of the city's GDP. However, the overall tourism development level of Chongqing is seriously unbalanced, and the tourism strength of the main urban area is much higher than that of the southeast Chongqing, northeast Chongqing and the surrounding city tourism area, and the overall tourism strength of the other three regions is relatively balanced. Based on the estimation of tourism development level and the geographic detector method, this paper finds that the important factors affecting the tourism development level of non-main urban areas in Chongqing are A-level tourist attractions. Through GIS geospatial analysis technology and SPSS data correlation research method, the spatial distribution characteristics and influencing factors of A-level tourist attractions in Chongqing were quantitatively analyzed by using data such as geospatial data cloud, relevant documents of Chongqing Municipal Commission of Culture and Tourism Development, planning cloud, and relevant statistical yearbooks. The results show that: (1) The spatial distribution of tourist attractions in non-main urban areas of Chongqing is agglomeration and uneven. (2) The spatial distribution of A-level tourist attractions in non-main urban areas of Chongqing is affected by ecological factors, and the degree of influence is in the order of water factors> topographic factors > green space factors.

Keywords: tourist attractions, geographic detectors, quantitative research, ecological factors, GIS technology, SPSS analysis

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Authors: Mehaiguene Madjid, Touhari Fadhila, Meddi Mohamed

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The Cheliff basin offers a good hydrological example for the possibility of studying the problem which elucidated in the future, because of the unclearity in several aspects and hydraulic installation. Thus, our study of the Cheliff basin is divided into two principal parts: The spatial evaluation of the precipitation: also, the understanding of the modes of the reconstitution of the resource in water supposes a good knowledge of the structuring of the precipitation fields in the studied space. In the goal of a good knowledge of revitalizes them in water and their management integrated one judged necessary to establish a precipitation card of the Cheliff basin for a good understanding of the evolution of the resource in water in the basin and that goes will serve as basis for all study of hydraulic planning in the Cheliff basin. Then, the establishment of the precipitation card of the Cheliff basin answered a direct need of setting to the disposition of the researchers for the region and a document of reference that will be completed therefore and actualized. The hydrological study, based on the statistical hydrometric data processing will lead us to specify the hydrological terms of the assessment hydrological and to clarify the fundamental aspects of the annual flow, seasonal, extreme and thus of their variability and resources surface water.

Keywords: hydrological assessment, surface water resources, Cheliff, Algeria

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Authors: Nagi Mekhiel

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Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Ala’a F. Jaber, Bara’ah A. Bsharat, Noor T. Ismael

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Background: Sensory processing is a fundamental skill needed for the successful performance of daily living activities. These skills are impaired as parts of the neurodevelopmental process issues among children with autism spectrum disorder (ASD). This systematic review aimed to summarize the evidence on the differences in sensory processing and motor characteristic between children with ASD and children with TD. Method: This systematic review followed the guidelines of the preferred reporting items for systematic reviews and meta-analysis. The search terms included sensory, motor, condition, and child-related terms or phrases. The electronic search utilized Academic Search Ultimate, CINAHL Plus with Full Text, ERIC, MEDLINE, MEDLINE Complete, Psychology, and Behavioral Sciences Collection, and SocINDEX with full-text databases. The hand search included looking for potential studies in the references of related studies. The inclusion criteria included studies published in English between years 2009-2020 that included children aged 3-18 years with a confirmed ASD diagnosis, according to the DSM-V criteria, included a control group of typical children, included outcome measures related to the sensory processing and/or motor functions, and studies available in full-text. The review of included studies followed the Oxford Centre for Evidence-Based Medicine guidelines, and the Guidelines for Critical Review Form of Quantitative Studies, and the guidelines for conducting systematic reviews by the American Occupational Therapy Association. Results: Eighty-eight full-text studies related to the differences between children with ASD and children with TD in terms of sensory processing and motor characteristics were reviewed, of which eighteen articles were included in the quantitative synthesis. The results reveal that children with ASD had more extreme sensory processing patterns than children with TD, like hyper-responsiveness and hypo-responsiveness to sensory stimuli. Also, children with ASD had limited gross and fine motor abilities and lower strength, endurance, balance, eye-hand coordination, movement velocity, cadence, dexterity with a higher rate of gait abnormalities than children with TD. Conclusion: This systematic review provided preliminary evidence suggesting that motor functioning should be addressed in the evaluation and intervention for children with ASD, and sensory processing should be supported among children with TD. More future research should investigate whether how the performance and engagement in daily life activities are affected by sensory processing and motor skills.

Keywords: sensory processing, occupational therapy, children, motor skills

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Authors: Ibrahim Gomaa, Hoda M. O. Mokhtar

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Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Keywords: continuous query processing, dynamic database, moving object, skyline queries

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Authors: Hossam M. Moftah, Aboul Ella Hassanien

Abstract:

In the recent years the importance of automatic traffic control has increased due to the traffic jams problem especially in big cities for signal control and efficient traffic management. Traffic counting as a kind of traffic control is important to know the road traffic density in real time. This paper presents a fast and robust traffic counting system using different image processing techniques. The proposed system is composed of the following four fundamental building phases: image acquisition, pre-processing, object detection, and finally counting the connected objects. The object detection phase is comprised of the following five steps: subtracting the background, converting the image to binary, closing gaps and connecting nearby blobs, image smoothing to remove noises and very small objects, and detecting the connected objects. Experimental results show the great success of the proposed approach.

Keywords: traffic counting, traffic management, image processing, object detection, computer vision

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Authors: Zhichao Song, Swanand Vaidya

Abstract:

Nowadays, most portable (e.g., smartphones) and wearable (e.g., smartwatches and earphones) consumer hardware are designed to be dustproof following IP5 or IP6 ratings to ensure the product is able to handle potentially dusty outdoor environments. On the other hand, the design guideline is relatively vague for indoor devices (e.g., smart displays and speakers). While it is generally believed that the indoor environment is much less dusty, in certain circumstances, dust ingression is still able to cause functional failures, such as microphone frequency response shift and camera black spot, or cosmetic dissatisfaction, mainly the dust build up in visible pockets and gaps which is hard to clean. In this paper, we developed a simulation methodology to analyze dust settlement and ingression into known ports of a device. A closed system is initialized with dust particles whose sizes follow Weibull distribution based on data collected in a user study, and dust particle movement was approximated as a settlement in stationary fluid, which is governed by Stokes’ law. Following this method, we simulated dust ingression into MEMS microphone through the acoustic port and protective mesh. Various design and environmental parameters are evaluated including mesh pore size, acoustic port depth-to-diameter ratio, mass density of dust material and inclined angle of microphone port. Although the dependencies of dust resistance on these parameters are all monotonic, smaller mesh pore size, larger acoustic depth-to-opening ratio and more inclined microphone placement (towards horizontal direction) are preferred for dust resistance; these preferences may represent certain trade-offs in audio performance and compromise in industrial design. The simulation results suggest the quantitative ranges of these parameters, with more pronounced effects in the improvement of dust resistance. Based on the simulation results, we proposed several design guidelines that intend to achieve an overall balanced design from audio performance, dust resistance, and flexibility in industrial design.

Keywords: dust settlement, numerical simulation, microphone design, Weibull distribution, Stoke's equation

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Authors: Yassir Abdelrazig, Ren Moses

Abstract:

Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

Keywords: gemoetric design, optimization, planning, roadway planning, roadway design

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Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao

Abstract:

Today's mining industry is advancing gradually toward digital and visual direction. The three dimensional visualization geological modeling of mine is the digital characterization of mineral deposit, and is one of the key technology of digital mine. The three-dimensional geological modeling is a technology that combines the geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in three-dimensional environment with computer technology, and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provided scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

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Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

Abstract:

The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

Abstract:

Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

Procedia PDF Downloads 115