Search results for: remote sensing mapping

Authors: Barbora Haltofová

Abstract:

In recent years, citizens have become an important source of geographic information and, therefore, geo-crowdsourcing, often known as volunteered geographic information, has provided an interesting alternative to traditional mapping practices which are becoming expensive, resource-intensive and unable to capture the dynamic nature of urban environments. In order to address a gap in research literature, this paper deals with a survey conducted to assess the current state of geo-crowdsourcing, a recent phenomenon popular with people who collect geographic information using their smartphones. This article points out that there is an increasing body of knowledge of geo-crowdsourcing mobile applications in the Visegrad countries marked by the ubiquitous Internet connection and the current massive proliferation of smartphones. This article shows how geo-crowdsourcing can be used as a complement, or in some cases a replacement, to traditionally generated sources of spatial data and information in public management. It discusses the new spaces of citizen participation constructed by these geo-crowdsourcing practices.

Keywords: citizen participation, e-Government, geo-crowdsourcing, participatory mapping, mobile applications

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Authors: J. Bahrawi, M. Elhag

Abstract:

Estimation of evapotranspiration is always a major component in water resources management. Traditional techniques of calculating daily evapotranspiration based on field measurements are valid only for local scales. Earth observation satellite sensors are thus used to overcome difficulties in obtaining daily evapotranspiration measurements on regional scale. The Surface Energy Balance System (SEBS) model was adopted to estimate daily evapotranspiration and relative evaporation along with other land surface energy fluxes. The model requires agro-climatic data that improve the model outputs. Advance Along Track Scanning Radiometer (AATSR) and Medium Spectral Resolution Imaging Spectrometer (MERIS) imageries were used to estimate the daily evapotranspiration and relative evaporation over the entire Nile Delta region in Egypt supported by meteorological data collected from six different weather stations located within the study area. Daily evapotranspiration maps derived from SEBS model show a strong agreement with actual ground-truth data taken from 92 points uniformly distributed all over the study area. Moreover, daily evapotranspiration and relative evaporation are strongly correlated. The reliable estimation of daily evapotranspiration supports the decision makers to review the current land use practices in terms of water management, while enabling them to propose proper land use changes.

Keywords: daily evapotranspiration, relative evaporation, SEBS, AATSR, MERIS, Nile Delta

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Authors: Anirudh Bhaikhel

Abstract:

The exclusive objective of this paper is to develop a device which can pass on the interpreted result of the sensed information to the interfaced communicable devices to avoid or minimise accidents. This device may also be used in case of emergencies like kidnapping, robberies, medical emergencies etc. The present era has seen a rapid metamorphosis in the automobile industry with increasing use of technology and speed. The increase in purchasing power of customers and price war of automobile companies has made an easy access to the automobile users. The use of automobiles has increased tremendously in last 4-5 years thus causing traffic congestions and thus making vehicles more prone to accidents. This device can be an effective measure to counteract cases of abduction. Risks of accidents can be decreased tremendously through the notifications received by these alerts. It will help to detect the upcoming emergencies. This paper includes the simulation of the communication and sensing device required in automobiles using VHDL.

Keywords: automobiles, communication, component, cyclic redundancy check (CRC), modulo-2 arithmetic, parity bits, receiver, sensors, transmitter, turns, VHDL (VHSIC hardware descriptive language)

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Authors: Sandhya Rao

Abstract:

Kevin Lynch’s Theory on Imeageability, let on explore a city in terms of five elements, Nodes, Paths, Edges, landmarks and Districts. What happens when we try to record the same data in an Indian context? What happens when we apply the same theory of Imageability to a complex shifting urban pattern of the Indian cities and how can we as Urban Designers demonstrate our role in the image building ordeal of these cities? The organizational patterns formed through mental images, of an Indian city is often diverse and intangible. It is also multi layered and temporary in terms of the spirit of the place. The pattern of images formed is loaded with associative meaning and intrinsically linked with the history and socio-cultural dominance of the place. The embedded memory of a place in one’s mind often plays an even more important role while formulating these images. Thus while deriving an image of a city one is often confused or finds the result chaotic. The images formed due to its complexity are further difficult to represent using a single medium. Under such a scenario it’s difficult to derive an output of an image constructed as well as make design interventions to enhance the legibility of a place. However, there can be a combination of tools and methods that allows one to record the key elements of a place through time, space and one’s user interface with the place. There has to be a clear understanding of the participant groups of a place and their time and period of engagement with the place as well. How we can translate the result obtained into a design intervention at the end, is the main of the research. Could a multi-faceted cognitive mapping be an answer to this or could it be a very transient mapping method which can change over time, place and person. How does the context influence the process of image building in one’s mind? These are the key questions that this research will aim to answer.

Keywords: imageability, organizational patterns, legibility, cognitive mapping

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Authors: Elyas Palantei, Dewiani, Farid Armin, Ardiansyah

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High precision of printed microwave sensor utilized for sensing and monitoring the potential breast cancer existed in women breast tissue was optimally computed. The single element of UWB printed sensor that successfully modeled through several numerical optimizations was multiple fabricated and incorporated with woman bra to form the spherical sensors array. One sample of UWB microwave sensor obtained through the numerical computation and optimization was chosen to be fabricated. In overall, the spherical sensors array consists of twelve stair patch structures, and each element was individually measured to characterize its electrical properties, especially the return loss parameter. The comparison of S11 profiles of all UWB sensor elements is discussed. The constructed UWB sensor is well verified using HFSS programming, CST programming, and experimental measurement. Numerically, both HFSS and CST confirmed the potential operation bandwidth of UWB sensor is more or less 4.5 GHz. However, the measured bandwidth provided is about 1.2 GHz due to the technical difficulties existed during the manufacturing step. The configuration of UWB microwave sensing and monitoring system implemented consists of 12 element UWB printed sensors, vector network analyzer (VNA) to perform as the transceiver and signal processing part, the PC Desktop/Laptop acting as the image processing and displaying unit. In practice, all the reflected power collected from whole surface of artificial breast model are grouped into several numbers of pixel color classes positioned on the corresponding row and column (pixel number). The total number of power pixels applied in 2D-imaging process was specified to 100 pixels (or the power distribution pixels dimension 10x10). This was determined by considering the total area of breast phantom of average Asian women breast size and synchronizing with the single UWB sensor physical dimension. The interesting microwave imaging results were plotted and together with some technical problems arisen on developing the breast sensing and monitoring system are examined in the paper.

Keywords: UWB sensor, UWB microwave imaging, spherical array, breast cancer monitoring, 2D-medical imaging

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Authors: Luixa Reizabal, Inaki Garcia, Eneko Sansinenea, Ainize Sarrionandia, Karmele Lopez De Ipina, Elsa Fernandez

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Although the effects of incarceration in prisons close to prisoners’ and their families’ residences have been studied, little is known about the effects of remote incarceration. The present study shows the impact of secondary prisonization on mental health of elderly parents of Basque prisoners who are incarcerated in prisons located far away from prisoners’ and their families’ residences. Secondary prisonization refers to the effects that imprisonment of a family member has on relatives. In the study, psychological effects are analyzed by means of comparative methodology. Specifically, levels of psychopathology (depression, anxiety, and stress) and positive mental health (psychological, social, and emotional well-being) are studied in a sample of parents over 65 years old of prisoners incarcerated in prisons located a long distance away (concretely, some of them in a distance of less than 400 km, while others farther than 400 km) from the Basque Country. The dataset consists of data collected through a questionnaire and from a spontaneous speech recording. The statistical and automatic analyses show that levels of psychopathology and positive mental health of elderly parents of prisoners incarcerated in remote jails are affected by the incarceration of their sons or daughters. Concretely, these parents show higher levels of depression, anxiety, and stress and lower levels of emotional (but not psychological or social) wellbeing than parents with no imprisoned daughters or sons. These findings suggest that parents with imprisoned sons or daughters suffer the impact of secondary prisonization on their mental health. When comparing parents with sons or daughters incarcerated within 400 kilometers from home and parents whose sons or daughters are incarcerated farther than 400 kilometers from home, the latter present higher levels of psychopathology, but also higher levels of positive mental health (although the difference between the two groups is not statistically significant). These findings might be explained by resilience. In fact, in traumatic situations, people can develop a force to cope with the situation, and even present a posttraumatic growth. Bearing in mind all these findings, it could be concluded that secondary prisonization implies for elderly parents with sons or daughters incarcerated in remote jails suffering and, in consequence, that changes in the penitentiary policy applied to Basque prisoners are required in order to finish this suffering.

Keywords: automatic spontaneous speech analysis, elderly parents, machine learning, positive mental health, psychopathology, remote incarceration, secondary prisonization

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Authors: Efleda Preclaro Tolentino

Abstract:

Research indicates that an educator’s belief system is reflected in the way they structure the learning environment. Their values and belief system have the potential to positively impact school readiness through an understanding of children’s development and the creation of a stable, motivating environment. Based on the premise that the social environment influences the development of social skills, knowledge construct, and shared values of young children, this study examined verbal and nonverbal exchanges between early childhood teachers and their preschool students within the context of remote learning. Using the qualitative method of data collection, the study determined the nature of interactions between preschoolers and their teachers within a remote learning environment at a preschool in Southeast Asia that utilized the Mother Tongue-based Multilingual Education (MTBMLE) Approach. From the lens of sociocultural theory, the study investigated preschoolers’ use of literacies to convey meaning and to interact within a remote learning environment. Using a Strengths Perspective, the study revealed the creativity and resourcefulness of preschoolers in expressing themselves through trans-literacies that were made possible by the use of online mode of learning within cultural and subcultural norms. The study likewise examined how social skills acquired by young children were transmitted (verbally or nonverbally) in their interactions with peers during Zoom meetings. By examining the dynamics of social exchanges between teachers and children, the findings of the study underscore the importance of providing support for preschool students as they apply acquired values and shared practices within a remote learning environment. The potential of distance learning in the early years will be explored, specifically in supporting young children’s language and literacy development. At the same time, the study examines the role of teachers as cultivators of trans-literacies. The teachers’ skillful use of technology in facilitating young children’s learning, as well as in supporting interactions with families, will be examined. The findings of this study will explore the potential of distance learning in early childhood education to establish continuity in learning, supporting young children’s social and emotional transitions, and nurturing trans-literacies that transcend prevailing definitions of learning contexts. The implications of teachers and parents working collaboratively to support student learning will be examined. The importance of preparing teachers to be resourceful, adaptable, and innovative to ensure that learning takes place across a variety of modes and settings will be discussed.

Keywords: transliteracy, preschoolers, remote learning, strengths perspective

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Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense

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The Wairau Plains are located in the north-east of the South Island of New Zealand in the region of Marlborough. The region is cut by many active crustal faults such as the Wairau, Awatere, and Clarence faults, which give rise to frequent seismic events. This paper presents the preliminary results of the overall project in which liquefaction-induced ground damage maps are developed in the Wairau Plains based on the Ministry of Business, Innovation and Employment NZ guidance. A suite of maps has been developed in relation to the level of details that was available to inform the liquefaction hazard mapping. Maps at the coarsest level of detail make use of regional geologic information, applying semi-quantitative criteria based on geological age, design peak ground accelerations and depth to the water table. The next level of detail incorporates higher resolution surface geomorphologic characteristics to better delineate potentially liquefiable and non-liquefiable deposits across the region. The most detailed assessment utilised CPT sounding data to develop ground damage response curves for areas across the region and provide a finer level of categorisation of liquefaction vulnerability. Linking these with design level earthquakes defined through NZGS guidelines will enable detailed classification to be carried out at CPT investigation locations, from very low through to high liquefaction vulnerability. To update classifications to these detailed levels, CPT investigations in geomorphic regions are grouped together to provide an indication of the representative performance of the soils in these areas making use of the geomorphic mapping outlined above.

Keywords: hazard, liquefaction, mapping, seismicity

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Authors: Narissara Nuthammachot, Dimitris Stratoulias

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Fire is one of the main causes of environmental and ecosystem change. Therefore, it is a challenging task for fire risk assessment fire potential mapping. The study area is Hua Sai district, Nakorn Sri Thammarat province, which covers in a part of peat swamp forest areas. 55 fire points in peat swamp areas were reported from 2012 to 2016. Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) methods were selected for this study. The risk fire area map was arranged on these factors; elevation, slope, aspect, precipitation, distance from the river, distance from town, and land use. The results showed that the predicted fire risk areas are found to be in appreciable reliability with past fire events. The fire risk map can be used for the planning and management of fire areas in the future.

Keywords: analytic hierarchy process, fire risk assessment, geographic information system, peat swamp forest

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Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

Abstract:

The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS

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Authors: Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran

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Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately and still require systematic clarification. The present study aimed to investigate the spatial-temporal clustering relationships between these factors and dengue outbreaks in the northern region of Sri Lanka. Remote sensing (RS) data gathered from a plurality of satellites were used to develop an index comprising rainfall, humidity and temperature data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling temporal analysis, spatial statistical analysis and space-time clustering analysis. Our present results showed that increases in the number of the combination of ecological factor and socio-economic and demographic factors with above the average or the presence contribute to significantly high rates of space-time dengue clusters.

Keywords: ALOS/AVNIR-2, dengue, space-time clustering analysis, Sri Lanka

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Authors: Khan R. Rahaman, Quazi K. Hassan

Abstract:

Global changes in climate, environment, economies, populations, governments, institutions, and cultures converge in localities. Changes at a local scale, in turn, contribute to global changes as well as being affected by them. Our hypothesis is built on a consideration that temperature does vary at local level (i.e., termed as local warming) in comparison to the predicted models at the regional and/or global scale. To date, the bulk of the research relating local places to global climate change has been top-down, from the global toward the local, concentrating on methods of impact analysis that use as a starting point climate change scenarios derived from global models, even though these have little regional or local specificity. Thus, our focus is to understand such trends over the southern Alberta, which will enable decision makers, scientists, researcher community, and local people to adapt their policies based on local level temperature variations and to act accordingly. Specific objectives in this study are: (i) to understand the local warming (temperature in particular) trend in context of temperature normal during the period 1961-2010 at point locations using meteorological data; (ii) to validate the data by using specific yearly data, and (iii) to delineate the spatial extent of the local warming trends and understanding influential factors to adopt situation by local governments. Existing data has brought the evidence of such changes and future research emphasis will be given to validate this hypothesis based on remotely sensed data (i.e. MODIS product by NASA).

Keywords: local warming, climate change, urban area, Alberta, Canada

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Authors: Lucille Alonso, Florent Renard

Abstract:

The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

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Authors: Zegrar Ahmed, Ghabi Mohamed

Abstract:

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

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

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Authors: Donglian Sun, Yu Li, Paul Houser, Xiwu Zhan

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California experienced severe drought conditions in the past years. In this study, the drought conditions in California are analyzed using soil moisture anomalies derived from integrated optical and microwave satellite observations along with auxiliary land surface data. Based on the U.S. Drought Monitor (USDM) classifications, three typical drought conditions were selected for the analysis: extreme drought conditions in 2007 and 2013, severe drought conditions in 2004 and 2009, and normal conditions in 2005 and 2006. Drought is defined as negative soil moisture anomaly. To estimate soil moisture at high spatial resolutions, three approaches are explored in this study: the universal triangle model that estimates soil moisture from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST); the basic model that estimates soil moisture under different conditions with auxiliary data like precipitation, soil texture, topography, and surface types; and the refined model that uses accumulated precipitation and its lagging effects. It is found that the basic model shows better agreements with the USDM classifications than the universal triangle model, while the refined model using precipitation accumulated from the previous summer to current time demonstrated the closest agreements with the USDM patterns.

Keywords: soil moisture, high resolution, regional drought, analysis and monitoring

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Authors: Luís M. João, Patrício Langa

Abstract:

The article reviews the literature on quality assurance (QA) in African higher education studies (HES) conducted through a bibliometric mapping of published papers between 1999 and 2019. Specifically, the article highlights the nuances of knowledge production in four scientific databases: Scopus, Web of Science (WoS), African Journal Online (AJOL), and Google Scholar. The analysis included 531 papers, of which 127 are from Scopus, 30 are from Web of Science, 85 are from African Journal Online, and 259 are from Google Scholar. In essence, 284 authors wrote these papers from 231 institutions and 69 different countries (i.e., Africa=54 and outside Africa=15). Results indicate the existing knowledge. This analysis allows the readers to understand the growth and development of the field during the two-decade period, identify key contributors, and observe potential trends or gaps in the research. The paper employs bibliometric mapping as its primary analytical lens. By utilizing this method, the study quantitatively assesses the publications related to QA in African HES, helping to identify patterns, collaboration networks, and disparities in research output. The bibliometric approach allows for a systematic and objective analysis of large datasets, offering a comprehensive view of the knowledge production in the field. Furthermore, the study highlights the lack of shared resources available to enhance quality in higher education institutions (HEIs) in Africa. This finding underscores the importance of promoting collaborative research efforts, knowledge exchange, and capacity building within the region to improve the overall quality of higher education. The paper argues that despite the growing quantity of QA research in African higher education, there are challenges related to citation impact and access to high-impact publication avenues for African researchers. It emphasises the need to promote collaborative research and resource-sharing to enhance the quality of HEIs in Africa. The analytical lenses of bibliometric mapping and the examination of publication players' scenarios contribute to a comprehensive understanding of the field and its implications for African higher education.

Keywords: Africa, bibliometric research, higher education studies, quality assurance, scientific database, systematic review

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Authors: Zaki Ahmad Khan, Jamshed Siddiqui, Abdus Samad

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The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear type of architectures as well as cube based architectures. Two standard dynamic scheduling schemes namely Minimum Distance Scheduling (MDS) and Two Round Scheduling (TRS) schemes are implemented on the LCQ network. Parallel tasks are mapped and the imbalance of load is evaluated on different set of processors in LCQ network. The simulations results are evaluated and effort is made by means of through analysis of the results to obtain the best solution for the given network in term of load imbalance left and execution time. The other performance matrices like speedup and efficiency are also evaluated with the given dynamic algorithms.

Keywords: dynamic algorithm, load imbalance, mapping, task scheduling

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Authors: Peyman Honarmandi, Mazen Alhirsh

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Banner towing is a major form of advertisement. It consists of a banner showing a logo or a selection of words or letters being towed by an aircraft. Traditionally bush planes have been used to tow banners given their high thrust capabilities; however, with the development of remote-controlled (RC) aircraft, they could be a good replacement as RC planes mitigate the risk of human life and can be easier to operate. This paper studies the best banner design to be towed by an RC aircraft. This is done by conducting wind tunnel testing on an array of banners with different materials and designs. A pull gauge is used to record the drag force during testing, which is then used to calculate the coefficient of drag, Cd. The testing results show that the best banner design would be a hybrid design with a solid and mesh material. The design with the lowest Cd of 0.082 was a half ripstop nylon half polyester mesh design. On the other hand, the design with the highest Cd of 0.305 involved incorporating a tail chute to decrease fluttering.

Keywords: aerodynamics of banner, banner design, banner towing, drag coefficients of banner, RC aircraft banner

Procedia PDF Downloads 224

Authors: M. Devaki, K. B. Jayanthi

Abstract:

The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Khan R. Rahaman, Quazi K. Hassan

Abstract:

Global changes in climate, environment, economies, populations, governments, institutions, and cultures converge in localities. Changes at a local scale, in turn, contribute to global changes as well as being affected by them. Our hypothesis is built on a consideration that temperature does vary at local level (i.e., termed as local warming) in comparison to the predicted models at the regional and/or global scale. To date, the bulk of the research relating local places to global climate change has been top-down, from the global toward the local, concentrating on methods of impact analysis that use as a starting point climate change scenarios derived from global models, even though these have little regional or local specificity. Thus, our focus is to understand such trends over the southern Alberta, which will enable decision makers, scientists, researcher community, and local people to adapt their policies based on local level temperature variations and to act accordingly. Specific objectives in this study are: (i) to understand the local warming (temperature in particular) trend in context of temperature normal during the period 1961-2010 at point locations using meteorological data; (ii) to validate the data by using specific yearly data, and (iii) to delineate the spatial extent of the local warming trends and understanding influential factors to adopt situation by local governments. Existing data has brought the evidence of such changes and future research emphasis will be given to validate this hypothesis based on remotely sensed data (i.e. MODIS product by NASA).

Keywords: local warming, climate change, urban area, Alberta, Canada

Procedia PDF Downloads 329

Authors: Tatiana Pratt, Benyamin Hanasabzadeh, Panayiota Courelli

Abstract:

The COVID-19 pandemic is one of the largest global public health issues of this current century. COVID-19 puts people diagnosed with obesity at higher risk of not only contracting the virus but also being hospitalized and dying, making this a vital time to implement obesity prevention programs. However, COVID-19 is predicted to rapidly increase the obesity rate in the United States due to the mandatory sedentary lifestyle the pandemic demands; this is especially harmful to adolescent-aged children because it creates lifelong unhealthy habits and behaviors. Adolescent obesity prevention programs have been rigorously implemented throughout the last century to help diminish the ever-increasing adolescent obesity rate. Since the pandemic kept adolescents inside and away from in-person school, many programs have now become ineffective due to their in-person participation. Examples of in-person participation programs include school lunch programs, OSNAP and New Moves. Therefore, online programs or remote intervention measures are now more essential. This leads to programs such as Time2bHealthy, HEALTH[e]TEEN, and SWITCH should be looked at with more vitality. Adolescents have intertwined their lives with technology and screen usage. Therefore, online and remote prevention programs will continue to play a large role in the post-pandemic era. This literature review will be reviewing past and current adolescent obesity prevention programs and their effectiveness with the new remote, sedentary lifestyle adolescents. Furthermore, it will suggest new ways to more productively decrease adolescent obesity rates by analyzing the harmful factors that COVID-19 introduced into their lifestyles.

Keywords: adolescent, obesity, overweight, COVID-19, preventative care, public health, public policy, obesity prevention programs, online programs

Procedia PDF Downloads 215

Authors: Chenlu Zhang, Wanni Zhang, Florian Schaule

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Indoor environment in office buildings directly affects comfort, productivity, health, and well-being of building occupants. Wireless environmental sensor networks have been deployed in many modern offices to monitor and control the indoor environments. However, indoor environmental variables are not strong enough predictors of comfort and productivity levels of every occupant due to personal differences, both physiologically and psychologically. This study proposes human-centric sensor networks that integrate wireless environmental sensors, body area network sensors and participatory sensing technologies to collect data from both environment and human and support building operations. The sensor networks have been tested in one small-size and one medium-size office rooms with 22 participants for five months. Indoor environmental data (e.g., air temperature and relative humidity), physiological data (e.g., skin temperature and Galvani skin response), and physiological responses (e.g., comfort and self-reported productivity levels) were obtained from each participant and his/her workplace. The data results show that: (1) participants have different physiological and physiological responses in the same environmental conditions; (2) physiological variables are more effective predictors of comfort and productivity levels than environmental variables. These results indicate that the human-centric sensor networks can support human-centric building control and improve comfort and productivity in offices.

Keywords: body area network, comfort and productivity, human-centric sensors, internet of things, participatory sensing

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Authors: Pukhtoon Yar

Abstract:

Peshawar City is experiencing a rapid spatial urban growth primarily as a result of high rate of urbanization along with economic development. This paper was designed to understand the impacts of urbanization on agriculture land use change by particularly focusing on land use change trajectories from the past (1991-2014). We used Landsat imageries (30 meters) for1991along with Spot images (2.5 meters) for year 2014. . The ground truthing of the satellite data was performed by collecting information from Peshawar Development Authority, revenue department, real estate agents and interviews with the officials of city administration. The temporal satellite images were processed by applying supervised maximum likelihood classification technique in ArcGIS 9.3. The procedure resulted into five main classes of land use i.e. built-up area, farmland, barren land, cultivable-wasteland and water bodies. The analysis revealed that, in Peshawar City the built-up environment has been doubled from 8.1 percent in 1991 to over 18.2 percent in 2014 by predominantly encroaching land producing food. Furthermore, the CA-Markov Model predicted that the area under impervious surfaces would continue to flourish during the next three decades. This rapid increase in built-up area is accredited to the lack of proper land use planning and management, which has caused chaotic urban sprawl with detrimental social and environmental consequences.

Keywords: Urban Expansion, Land use, GIS, Remote Sensing, Markov Model, Peshawar City

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Authors: M. Naveed Iqbal, Sheza Fatima, Noman Shabbir

Abstract:

In the presence of energy crisis in Pakistan, off-grid remote areas are not on priority list. The use of new large scale coal fired power plants will also make this situation worst. Therefore, the greatest challenge in our society is to explore new ways to power off grid remote areas with renewable energy sources. It is time for a sustainable energy policy which puts consumers, the environment, human health, and peace first. The renewable energy is one of the biggest growing sectors of the energy industry. Therefore, the large scale use of micro grid is thus described here with modeling, simulation, planning and operating of the micro grid. The goal of this research paper is to go into detail of a library of major components of micro grid. The introduction will go through the detail view of micro grid definition. Then, the simulation of Micro Grid in MATLAB/ Simulink including the Photo Voltaic Cell will be described with the detailed modeling. The simulation with the design and modeling will be introduced too.

Keywords: micro grids, distribution generation, PV, off-grid operations

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Authors: A. Bagherzadhalimi, E. Di Maria

Abstract:

The feedbacks obtained regarding the sense of presence from pilot users operating a Mobile Robotic presence (MRP) system to visit a simulated museum are reported in this paper. The aim is to investigate how much the perception of system’s usefulness and ease of use is affected by operators’ sense of social telepresence (presence) in the remote location. Therefore, scenarios of visiting a museum are simulated and the user operators are supposed to perform some regular tasks inside the remote environment including interaction with local users, navigation and visiting the artworks. Participants were divided into two groups, those who had previous experience of operation and interaction with a MRP system and those who never had experience. Based on the results, both groups provided different feedbacks. Moreover, there was a significant association between user’s sense of presence and their perception of system usefulness and ease of use.

Keywords: mobile robotic telepresence, museum, social telepresence, usability test

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

Abstract:

Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Arash M. Shahidi, Tilak Dias, Gayani K. Nandasiri

Abstract:

While graduated compression is the foundation of treatment and management of many medical complications such as leg ulcer, varicose veins, and lymphedema, monitoring the interface pressure has been conducted using different sensors that operate based on diverse approaches. The variations existed from the pressure readings collected using different interface pressure measurement systems would cause difficulties in taking a decision regarding the compression therapy. It is crucial to acknowledge the differences existing between direct and indirect pressure measurement systems while considering the commercially available systems such as AMI, Picopress and OPM which are under direct measurements systems, and HATRA (BSI), HOSY (RAL-GZ) and FlexiForce which comes under the indirect measurement system. Furthermore, Piezo-resistive sensors (Flexiforce) can measure the changes in resistance corresponding to the applied force on the sensing area. Direct pressure measuring systems are capable of measuring interface pressure on the three-dimensional states, while the indirect pressure measuring systems stretch the fabric in the two-dimensional direction and extrapolate pressure from surface tension measured on the device and neglect the vital factor which is the radius of curvature. In this study, a leg mannequin of known dimensions is selected with a knitted class 3 compression stocking. It has been decided to evaluate the data collected from different available systems (AMI, PicoPress, FlexiForce, and HATRA) and compare the results. The results showed a discrepancy between Hatra, AMI, Picopress, and Flexiforce against the pressure standard used to generate class 3 compression stocking. As predicted a higher pressure value with direct interface measuring systems were monitored against HATRA due to the effect of the radius of curvature.

Keywords: AMI, FlexiForce, graduated compression, HATRA, interface pressure, PicoPress

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Authors: Naoki Yamamoto, Hidenobu Ozaki, Taiichiro Ookawa, Youming Liu, Kazunori Okada, Aiping Zheng

Abstract:

Rice sheath blight is one of the destructive fungal diseases in rice. We have thought that rice sheath blight resistance is a polygenic trait. Host-pathogen interactions and secondary metabolites such as lignin and phytoalexins are likely to be involved in defense against R. solani. However, to our knowledge, it is still unknown how sheath blight resistance can be enhanced in rice breeding. To seek for an alternative genetic factor that contribute to sheath blight resistance, we mined relevant allelic variations from rice core collections created in Japan. Based on disease lesion length on detached leaf sheath, we selected 30 varieties of the top tail-end and the bottom tail-end, respectively, from the core collections to perform genome-wide association mapping. Re-sequencing reads for these varieties were used for calling single nucleotide polymorphisms among the 60 varieties to create a SNP panel, which contained 1,137,131 homozygous variant sites after filitering. Association mapping highlighted a locus on the long arm of chromosome 11, which is co-localized with three sheath blight QTLs, qShB11-2-TX, qShB11, and qSBR-11-2. Based on the localization of the trait-associated alleles, we identified an ankyryn repeat-containing protein gene (ANK-M) as an uncharacterized candidate factor for rice sheath blight resistance. Allelic distributions for ANK-M in the whole rice population supported the reliability of trait-allele associations. Gene expression characteristics were checked to evaluiate the functionality of ANK-M. Since an ANK-M homolog (OsPIANK1) in rice seems a basal defense regulator against rice blast and bacterial leaf blight, ANK-M may also play a role in the rice immune system.

Keywords: allele mining, GWAS, QTL, rice sheath blight

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Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

Abstract:

Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: Mostafa Ghasemi, Andrew Urquhart

Abstract:

In this study, fluorescent carbon dots (CDs) were synthesized in a green way using a one-step hydrothermal method. Carbon dots are carbon-based nanomaterials with a size of less than 10 nm, unique structure, and excellent properties such as low toxicity, good biocompatibility, tunable fluorescence, excellent photostability, and easy functionalization. These properties make them a good candidate to use in different fields such as biological sensing, photocatalysis, photodynamic, and drug delivery. Fourier transformed infrared (FTIR) spectra approved OH/NH groups on the surface of the as-synthesized CDs, and UV-vis spectra showed excellent fluorescence quenching effect of Fe (III) ion on the as-synthesized CDs with high selectivity detection compared with other metal ions. The probe showed a linear response concentration range (0–2.0 mM) to Fe (III) ion, and the limit of detection was calculated to be about 0.50 μM. In addition, CDs also showed good sensitivity to the pH value in the range from 2 to 14, indicating great potential as a pH sensor.

Keywords: carbon dots, fluorescence, pH sensing, metal ions sensor

Procedia PDF Downloads 56