Search results for: spatial patterns

Authors: Pulakesh Das, Mukunda Dev Behera, Manchiraju Sri Ramachandra Murthy

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Large numbers of people living in and around the Hindu Kush Himalaya (HKH) region, depends on this diverse mountainous region for ecosystem services. Following the global trend, this region also experiencing rapid population growth, and demand for timber and agriculture land. The eight countries sharing the HKH region have different forest resources utilization and conservation policies that exert varying forces in the forest ecosystem. This created a variable spatial as well altitudinal gradient in rate of deforestation and corresponding forest patch fragmentation. The quantitative relationship between fragmentation and demography has not been established before for HKH vis-à-vis along elevation gradient. This current study was carried out to attribute the overall and different nature in landscape fragmentations along the altitudinal gradient with the demography of each sharing countries. We have used the tree canopy cover data derived from Landsat data to analyze the deforestation and afforestation rate, and corresponding landscape fragmentation observed during 2000 – 2010. Area-weighted mean radius of gyration (AMN radius of gyration) was computed owing to its advantage as spatial indicator of fragmentation over non-spatial fragmentation indices. Using the subtraction method, the change in fragmentation was computed during 2000 – 2010. Using the tree canopy cover data as a surrogate of forest cover, highest forest loss was observed in Myanmar followed by China, India, Bangladesh, Nepal, Pakistan, Bhutan, and Afghanistan. However, the sequence of fragmentation was different after the maximum fragmentation observed in Myanmar followed by India, China, Bangladesh, and Bhutan; whereas increase in fragmentation was seen following the sequence of as Nepal, Pakistan, and Afghanistan. Using SRTM-derived DEM, we observed higher rate of fragmentation up to 2400m that corroborated with high human population for the year 2000 and 2010. To derive the nature of fragmentation along the altitudinal gradients, the Statistica software was used, where the user defined function was utilized for regression applying the Gauss-Newton estimation method with 50 iterations. We observed overall logarithmic decrease in fragmentation change (area-weighted mean radius of gyration), forest cover loss and population growth during 2000-2010 along the elevation gradient with very high R2 values (i.e., 0.889, 0.895, 0.944 respectively). The observed negative logarithmic function with the major contribution in the initial elevation gradients suggest to gap filling afforestation in the lower altitudes to enhance the forest patch connectivity. Our finding on the pattern of forest fragmentation and human population across the elevation gradient in HKH region will have policy level implication for different nations and would help in characterizing hotspots of change. Availability of free satellite derived data products on forest cover and DEM, grid-data on demography, and utility of geospatial tools helped in quick evaluation of the forest fragmentation vis-a-vis human impact pattern along the elevation gradient in HKH.

Keywords: area-weighted mean radius of gyration, fragmentation, human impact, tree canopy cover

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Authors: Ayodele James Akinola

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This study investigated the use of English in doctor-patient interaction in a university teaching hospital from a southwestern state in Nigeria with the aim of identifying the role of communication in an L2, patterns of communication, discourse strategies, pragmatic acts, and contexts that shape the interaction. Jacob Mey’s Pragmatic Acts notion complemented with Emanuel and Emanuel’s model of doctor-patient relationship provided the theoretical standpoint. Data comprising 7 audio-recorded doctors-patient interactions were collected from a University Hospital in Oyo state, Nigeria. Interactions involving the use of English language were purposefully selected. These were supplemented with patients’ case notes and interviews conducted with doctors. Transcription was patterned alongside modified Arminen’s notations of conversation analysis. In the study, interaction in English between doctor and patients has the preponderance of direct-translation, code-mixing and switching, Nigerianism and use of cultural worldviews to express medical experience. Irrespective of these, three patterns communication, namely the paternalistic, interpretive, and deliberative were identified. These were exhibited through varying discourse strategies. The paternalistic model reflected slightly casual conversational conventions and registers. These were achieved through the pragmemic activities of situated speech acts, psychological and physical acts, via patients’ quarrel-induced acts, controlled and managed through doctors’ shared situation knowledge. All these produced empathising, pacifying, promising and instructing practs. The patients’ practs were explaining, provoking, associating and greeting in the paternalistic model. The informative model reveals the use of adjacency pairs, formal turn-taking, precise detailing, institutional talks and dialogic strategies. Through the activities of the speech, prosody and physical acts, the practs of declaring, alerting and informing were utilised by doctors, while the patients exploited adapting, requesting and selecting practs. The negotiating conversational strategy of the deliberative model featured in the speech, prosody and physical acts. In this model, practs of suggesting, teaching, persuading and convincing were utilised by the doctors. The patients deployed the practs of questioning, demanding, considering and deciding. The contextual variables revealed that other patterns (such as phatic and informative) are also used and they coalesced in the hospital within the situational and psychological contexts. However, the paternalistic model was predominantly employed by doctors with over six years in practice, while the interpretive, informative and deliberative models were found among registrar and others below six years of medical practice. Doctors’ experience, patients’ peculiarities and shared cultural knowledge influenced doctor-patient communication in the study.

Keywords: pragmatics, communication pattern, doctor-patient interaction, Nigerian hospital situation

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Authors: R. Lhissou , A. El Harti , K. Chokmani, E. Bachaoui, A. El Ghmari

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Soil salinity is a serious environmental hazard in many countries around the world especially the arid and semi-arid countries like Morocco. Salinization causes negative effects on the ground; it affects agricultural production, infrastructure, water resources and biodiversity. Remote sensing can provide soil salinity information for large areas, and in a relatively short time. In addition, remote sensing is not limited by extremes in terrain or hazardous condition. Contrariwise, experimental methods for monitoring soil salinity by direct measurements in situ are very demanding of time and resources, and also very limited in spatial coverage. In the irrigated perimeter of Tadla plain in central Morocco, the increased use of saline groundwater and surface water, coupled with agricultural intensification leads to the deterioration of soil quality especially by salinization. In this study, we assessed several spectral indices of soil salinity cited in the literature using Landsat TM satellite images and field measurements of electrical conductivity (EC). Three Landsat TM satellite images were taken during 3 months in the dry season (September, October and November 2011). Based on field measurement data of EC collected in three field campaigns over the three dates simultaneously with acquisition dates of Landsat TM satellite images, a two assessment techniques are used to validate a soil salinity spectral indices. Firstly, the spectral indices are validated locally by pixel. The second validation technique is made using a window of size 3x3 pixels. The results of the study indicated that the second technique provides getting a more accurate validation and the assessment has shown its limits when it comes to assess across the pixel. In addition, the EC values measured from field have a good correlation with some spectral indices derived from Landsat TM data and the best results show an r² of 0.88, 0.79 and 0.65 for Salinity Index (SI) in the three dates respectively. The results have shown the usefulness of spectral indices as an auxiliary variable in the spatial estimation and mapping salinity in irrigated land.

Keywords: remote sensing, spectral indices, soil salinity, irrigated land

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Authors: Berhanu Keno Terfa

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Flash floods are among the most dangerous natural disasters that pose a significant threat to human existence. They occur frequently and can cause extensive damage to homes, infrastructure, and ecosystems while also claiming lives. Although flash floods can happen anywhere in the world, their impact is particularly severe in developing countries due to limited financial resources, inadequate drainage systems, substandard housing options, lack of early warning systems, and insufficient preparedness. To address these challenges, a comprehensive study has been undertaken to analyze and map flood inundation using Geographic Information System (GIS) techniques by considering various factors that contribute to flash flood resilience and developing effective mitigation strategies. Key factors considered in the analysis include slope, drainage density, elevation, Curve Number, rainfall patterns, land-use/cover classes, and soil data. These variables were computed using ArcGIS software platforms, and data from the Sentinel-2 satellite image (with a 10-meter resolution) were utilized for land-use/cover classification. Additionally, slope, elevation, and drainage density data were generated from the 12.5-meter resolution of the ALOS Palsar DEM, while other relevant data were obtained from the Ethiopian Meteorological Institute. By integrating and regularizing the collected data through GIS and employing the analytic hierarchy process (AHP) technique, the study successfully delineated flash flood hazard zones (FFHs) and generated a suitable land map for urban agriculture. The FFH model identified four levels of risk in Bishoftu City: very high (2106.4 ha), high (10464.4 ha), moderate (1444.44 ha), and low (0.52 ha), accounting for 15.02%, 74.7%, 10.1%, and 0.004% of the total area, respectively. The results underscore the vulnerability of many residential areas in Bishoftu City, particularly the central areas that have been previously developed. Accurate spatial representation of flood-prone areas and potential agricultural zones is crucial for designing effective flood mitigation and agricultural production plans. The findings of this study emphasize the importance of flood risk mapping in raising public awareness, demonstrating vulnerability, strengthening financial resilience, protecting the environment, and informing policy decisions. Given the susceptibility of Bishoftu City to flash floods, it is recommended that the municipality prioritize urban agriculture adaptation, proper settlement planning, and drainage network design.

Keywords: remote sensing, flush flood hazards, Bishoftu, GIS.

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Authors: A. Alzahrani, G. Arnold, W. Wang

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Background: Stroke commonly occurs in middle-aged and elderly populations, and the diagnosis of early stroke is still difficult. Patients who have suffered a stroke have different balance and gait patterns from healthy people. Advanced techniques of motion analysis have been routinely used in the clinical assessment of cerebral palsy. However, so far, little research has been done on the direct diagnosis of early stroke patients using motion analysis. Objectives: The aim of this study was to investigate whether patients with stroke have different balance and gait from healthy people and which biomechanical parameters could be used to predict and diagnose potential patients who are at a potential risk to stroke. Methods: Thirteen patients with stroke were recruited as subjects whose gait and balance was analysed. Twenty normal subjects at the matched age participated in this study as a control group. All subjects’ gait and balance were collected using Vicon Nexus® to obtain the gait parameters, kinetic, and kinematic parameters of the hip, knee, and ankle joints in three planes of both limbs. Participants stood on force platforms to perform a single leg balance test. Then, they were asked to walk along a 10 m walkway at their comfortable speed. Participants performed 6 trials of single-leg balance for each side and 10 trials of walking. From the recorded trials, three good ones were analysed using the Vicon Plug-in-Gait model to obtain gait parameters, e.g., walking speed, cadence, stride length, and joint parameters, e.g., joint angle, force, moments, etc. Result: The temporal-spatial variables of Stroke subjects were compared with the healthy subjects; it was found that there was a significant difference (p < 0.05) between the groups. The step length, speed, cadence were lower in stroke subjects as compared to the healthy groups. The stroke patients group showed significantly decreased in gait speed (mean and SD: 0.85 ± 0.33 m/s), cadence ( 96.71 ± 16.14 step/min), and step length (0.509 ± 017 m) in compared to healthy people group whereas the gait speed was 1.2 ± 0.11 m/s, cadence 112 ± 8.33 step/min, and step length 0.648 ± 0.43 m. Moreover, it was observed that patients with stroke have significant differences in the ankle, hip, and knee joints’ kinematics in the sagittal and coronal planes. Also, the result showed that there was a significant difference between groups in the single-leg balance test, e.g., maintaining single-leg stance time in the stroke patients showed shorter duration (5.97 ± 6.36 s) in compared to healthy people group (14.36 ± 10.20 s). Conclusion: Our result showed that there are significantly differences between stroke patients and healthy subjects in the various aspects of gait analysis and balance test, as a consequences of these findings some of the biomechanical parameters such as joints kinematics, gait parameters, and single-leg stance balance test could be used in clinical practice to predict and diagnose potential patients who are at a high risk of further stroke.

Keywords: gait analysis, kinetics, kinematics, single-leg stance, Stroke

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Authors: I. Asanuma, T. Yamaguchi, J. Park, K. J. Mackin

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Fishery lights on the surface could be detected by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi-NPP). The DNB covers the spectral range of 500 to 900 nm and realized a higher sensitivity. The DNB has a difficulty of identification of fishing lights from lunar lights reflected by clouds, which affects observations for the half of the month. Fishery lights and lights of the surface are identified from lunar lights reflected by clouds by a method using the DNB and the infrared band, where the detection limits are defined as a function of the brightness temperature with a difference from the maximum temperature for each level of DNB radiance and with the contrast of DNB radiance against the background radiance. Fishery boats or structures on islands could be detected by the Synthetic Aperture Radar (SAR) on the polar orbit satellites using the reflected microwave by the surface reflecting targets. The SAR has a difficulty of tradeoff between spatial resolution and coverage while detecting the small targets like fishery boats. A distribution of fishery boats and island activities were detected by the scan-SAR narrow mode of Radarsat-2, which covers 300 km by 300 km with various combinations of polarizations. The fishing boats were detected as a single pixel of highly scattering targets with the scan-SAR narrow mode of which spatial resolution is 30 m. As the look angle dependent scattering signals exhibits the significant differences, the standard deviations of scattered signals for each look angles were taken into account as a threshold to identify the signal from fishing boats and structures on the island from background noise. It was difficult to validate the detected targets by DNB with SAR data because of time lag of observations for 6 hours between midnight by DNB and morning or evening by SAR. The temporal changes of island activities were detected as a change of mean intensity of DNB for circular area for a certain scale of activities. The increase of DNB mean intensity was corresponding to the beginning of dredging and the change of intensity indicated the ending of reclamation and following constructions of facilities.

Keywords: day night band, SAR, fishery, South China Sea

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Authors: Javad Sadidi, Ehsan Babaei, Hani Rezayan

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The advent of web 2.0 gives a possibility to scale down the costs of data collection and mapping, specifically if the process is done by volunteers. Every volunteer can be thought of as a free and ubiquitous sensor to collect spatial, descriptive as well as multimedia data for tourist services. The lack of large-scale information, such as real-time climate and weather conditions, population density, and other related data, can be considered one of the important challenges in developing countries for tourists to make the best decision in terms of time and place of travel. The current research aims to design and implement a spatiotemporal web map service using volunteer-submitted data. The service acts as a tourist-guide service in which tourists can search interested places based on their requested time for travel. To design the service, three tiers of architecture, including data, logical processing, and presentation tiers, have been utilized. For implementing the service, open-source software programs, client and server-side programming languages (such as OpenLayers2, AJAX, and PHP), Geoserver as a map server, and Web Feature Service (WFS) standards have been used. The result is two distinct browser-based services, one for sending spatial, descriptive, and multimedia volunteer data and another one for tourists and local officials. Local official confirms the veracity of the volunteer-submitted information. In the tourist interface, a spatiotemporal search engine has been designed to enable tourists to find a tourist place based on province, city, and location at a specific time of interest. Implementing the tourist-guide service by this methodology causes the following: the current tourists participate in a free data collection and sharing process for future tourists, a real-time data sharing and accessing for all, avoiding a blind selection of travel destination and significantly, decreases the cost of providing such services.

Keywords: VGI, tourism, spatiotemporal, browser-based, web mapping

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Authors: Elizaveta Petelina, Anton Sizo

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Environmental remediation projects deal with a wide spectrum of data, including data collected during site assessment, execution of remediation activities, and environmental monitoring. Therefore, an appropriate data management is required as a key factor for well-grounded decision making. The Environmental Data Management System (EDMS) was developed to address all necessary data management aspects, including efficient data handling and data interoperability, access to historical and current data, spatial and temporal analysis, 2D and 3D data visualization, mapping, and data sharing. The system focuses on support of well-grounded decision making in relation to required mitigation measures and assessment of remediation success. The EDMS is a combination of enterprise and desktop level data management and Geographic Information System (GIS) tools assembled to assist to environmental remediation, project planning, and evaluation, and environmental monitoring of mine sites. EDMS consists of seven main components: a Geodatabase that contains spatial database to store and query spatially distributed data; a GIS and Web GIS component that combines desktop and server-based GIS solutions; a Field Data Collection component that contains tools for field work; a Quality Assurance (QA)/Quality Control (QC) component that combines operational procedures for QA and measures for QC; Data Import and Export component that includes tools and templates to support project data flow; a Lab Data component that provides connection between EDMS and laboratory information management systems; and a Reporting component that includes server-based services for real-time report generation. The EDMS has been successfully implemented for the Project CLEANS (Clean-up of Abandoned Northern Mines). Project CLEANS is a multi-year, multimillion-dollar project aimed at assessing and reclaiming 37 uranium mine sites in northern Saskatchewan, Canada. The EDMS has effectively facilitated integrated decision-making for CLEANS project managers and transparency amongst stakeholders.

Keywords: data management, environmental remediation, geographic information system, GIS, decision making

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Authors: Shirin jalili, Hadi Shirzad, Mahasti Modarresi, Samaneh Nabavi, Somayeh Khanjani

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Identifying the source tissue of biological material found at crime scenes can be very informative in a number of cases. Despite their usefulness, current visual, catalytic, enzymatic, and immunologic tests for presumptive and confirmatory tissue identification are applicable only to a subset of samples, might suffer limitations such as low specificity, lack of sensitivity, and are substantially impacted by environmental insults. In addition their results are operator-dependent. Recently the possibility of discriminating body fluids using mRNA expression differences in tissues has been described but lack of long term stability of that Molecule and the need to normalize samples for each individual are limiting factors. The use of DNA should solve these issues because of its long term stability and specificity to each body fluid. Cells in the human body have a unique epigenome, which includes differences in DNA methylation in the promoter of genes. DNA methylation, which occurs at the 5′-position of the cytosine in CpG dinucleotides, has great potential for forensic identification of body fluids, because tissue-specific patterns of DNA methylation have been demonstrated, and DNA is less prone to degradation than proteins or RNA. Previous studies have reported several body fluid-specific DNA methylation markers.The presence or absence of a methyl group on the 5’ carbon of the cytosine pyridine ring in CpG dinucleotide regions called ‘CpG islands’ dictates whether the gene is expressed or silenced in the particular body fluid. Were described methylation patterns at tissue specific differentially methylated regions (tDMRs) to be stable and specific, making them excellent markers for tissue identification. The results demonstrate that methylation-based tissue identification is more than a proof-of-concept. The methodology holds promise as another viable forensic DNA analysis tool for characterization of biological materials.

Keywords: DNA methylation, forensic science, epigenome, tDMRs

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Authors: Chao-Ton Su, Li-Fei Chen

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

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

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

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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: C. Bejrananda, Y. Lee, T. Khamkaew

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With the rise of the importance of air transportation in the 21st century, the role of economics in airport planning and decision-making has become more important to the urban structure and land value around it. Therefore, this research aims to examine the relationship between an airport and its impacts on the distribution of urban land uses and land values by applying the Alonso’s bid rent model. The New Bangkok International Airport (Suvarnabhumi International Airport) was taken as a case study. The analysis was made over three different time periods of airport development (after the airport site was proposed, during airport construction, and after the opening of the airport). The statistical results confirm that Alonso’s model can be used to explain the impacts of the new airport only for the northeast quadrant of the airport, while proximity to the airport showed the inverse relationship with the land value of all six types of land use activities through three periods of time. It indicates that the land value for commercial land use is the most sensitive to the location of the airport or has the strongest requirement for accessibility to the airport compared to the residential and manufacturing land use. Also, the bid-rent gradients of the six types of land use activities have declined dramatically through the three time periods because of the Asian Financial Crisis in 1997. Therefore, the lesson learned from this research concerns about the reliability of the data used. The major concern involves the use of different areal units for assessing land value for different time periods between zone block (1995) and grid block (2002, 2009). As a result, this affect the investigation of the overall trends of land value assessment, which are not readily apparent. In addition, the next concern is the availability of the historical data. With the lack of collecting historical data for land value assessment by the government, some of data of land values and aerial photos are not available to cover the entire study area. Finally, the different formats of using aerial photos between hard-copy (1995) and digital photo (2002, 2009) made difficult for measuring distances. Therefore, these problems also affect the accuracy of the results of the statistical analyses.

Keywords: airport development area, economic rents, spatial pattern, suvarnabhumi international airport

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Authors: Lisa Kasmer

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Teachers’ instructional decisions shape the structure and content of mathematics lessons and influence the mathematics that students are given the opportunity to learn. Therefore, it is important to better understand how teachers make instructional decisions and thus find new ways to help practicing and future teachers give their students a more effective and robust learning experience. Understanding the relationship between teachers’ instructional decisions and their goals, resources, and orientations (beliefs) is important given the heightened focus on geometric transformations in the middle school mathematics curriculum. This work is significant as the development and support of current and future teachers need more effective ways to teach geometry to their students. The following research questions frame this study: (1) As middle school mathematics teachers plan and enact instruction related to teaching transformations, what thinking processes do they engage in to make decisions about teaching transformations with or without a coordinate system and (2) How do the goals, resources and orientations of these teachers impact their instructional decisions and reveal about their understanding of teaching transformations? Teachers and students alike struggle with understanding transformations; many teachers skip or hurriedly teach transformations at the end of the school year. However, transformations are an important mathematical topic as this topic supports students’ understanding of geometric and spatial reasoning. Geometric transformations are a foundational concept in mathematics, not only for understanding congruence and similarity but for proofs, algebraic functions, and calculus etc. Geometric transformations also underpin the secondary mathematics curriculum, as features of transformations transfer to other areas of mathematics. Teachers’ instructional decisions in terms of goals, orientations, and resources that support these instructional decisions were analyzed using open-coding. Open-coding is recognized as an initial first step in qualitative analysis, where comparisons are made, and preliminary categories are considered. Initial codes and categories from current research on teachers’ thinking processes that are related to the decisions they make while planning and reflecting on the lessons were also noted. Surfacing ideas and additional themes common across teachers while seeking patterns, were compared and analyzed. Finally, attributes of teachers’ goals, orientations and resources were identified in order to begin to build a picture of the reasoning behind their instructional decisions. These categories became the basis for the organization and conceptualization of the data. Preliminary results suggest that teachers often rely on their own orientations about teaching geometric transformations. These beliefs are underpinned by the teachers’ own mathematical knowledge related to teaching transformations. When a teacher does not have a robust understanding of transformations, they are limited by this lack of knowledge. These shortcomings impact students’ opportunities to learn, and thus disadvantage their own understanding of transformations. Teachers’ goals are also limited by their paucity of knowledge regarding transformations, as these goals do not fully represent the range of comprehension a teacher needs to teach this topic well.

Keywords: coordinate plane, geometric transformations, instructional decisions, middle school mathematics

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Authors: Muhammad Yayat Afianto, Darmawan, Agung Putra Utama, Hari Kushardanto

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Fish Forever, Rare’s innovative coastal fisheries program, combined community-based conservation management approach with spatial management to restore and protect Indonesia’s small-scale fisheries by establishing Fishing Managed Access Area. A ‘TURF-Reserve’ is a fishery management approach that positions fishers at the center of fisheries management, empowering them to take care of and make decisions about the future of their fishery. After two years of the program, social marketing campaigns succeeded in changing their behavior by adopting the new conservation behavior. The Pride-TURF-R campaigns developed an overarching hypothesis of impact that captured the knowledge, attitude and behavior changes needed to reduce threats and achieve conservation results. Rare help Batu Belah fishers to develop their group, developed with their roles, sustainable fisheries plan, and the budget plan. On 12th February 2017, the Head of Loka Kawasan Konservasi Perairan Nasional (LKKPN) which is a Technical Implementation Unit for National Marine Conservation Areas directly responsible to the Directorate General for Marine Spatial Management in the Ministry of Marine Affairs and Fisheries had signed a Partnership Agreement with the Head of Batu Belah Village to manage a TURF+Reserve area as wide as 909 hectares. The fishers group have been collecting the catch and submitting the report monthly, initiated the installation of the buoy markers for the No Take Zone, and formed the Pokmaswas (community-based surveillance group). Prior to this behavior adoption, they don’t have any fisheries data, no group of fishers, and they have still fishing inside the No Take Zone. This is really a new behavior adoption for them. This paper will show the process and success story of the social marketing campaign to conserve marine habitat in Anambas through Pride-TURF-R program.

Keywords: behavior adoption, community participation, no take zone, pride-TURF-R

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Authors: Sabir Hussain, Muhammad Naeem, Yousif Aldryhim, Susan E. Halbert, Qingjun Wu

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Plant viruses annually cause severe economic losses in crop production and globally, different aphid species are responsible for the transmission of such viruses. Additionally, aphids are also serious pests of trees, and agricultural crops. Al Bahah Province, Kingdom of Saudi Arabia (KSA) has a high native and introduced plant species with a temperate climate that provides ample habitats for aphids. In this study, we surveyed virus-transmitting aphids from the Province to highlight their spatial distributions and hot spot areas for their target control strategies. During our fifteen month's survey in Al Bahah Province, three hundred and seventy samples of aphids were collected using both beating sheets and yellow water pan traps. Consequently, fifty-four aphid species representing 30 genera belonging to four families were recorded from Al Bahah Province. Alarmingly, 35 aphid species from our records are virus transmitting species. The most common virus transmitting aphid species based on number of collecting samples, were Macrosiphum euphorbiae (Thomas, 1878), Brachycaudus rumexicolens (Patch, 1917), Uroleucon sonchi (Linnaeus, 1767), Brachycaudus helichrysi (Kaltenbach, 1843), and Myzus persicae (Sulzer, 1776). The numbers of samples for the forementioned species were 66, 24, 23, 22, and 20, respectively. The widest range of plant hosts were found for M. euphorbiae (39 plant species), B. helichrysi (12 plant species), M. persicae (12 plant species), B. rumexicolens (10 plant species), and U. sonchi (9 plant species). The hottest spot areas were found in Al-Baha, Al Mekhwah and Biljarashi cities of the province on the basis of their abundance. This study indicated that Al Bahah Province has relatively rich aphid diversity due to the relatively high plant diversity in a favorable climatic condition. ArcGIS tools can be helpful for biologists to implement the target control strategies against these pests in the integrated pest management, and ultimately to save money and time.

Keywords: Al Bahah province, aphid-virus interaction, biodiversity, global information system

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Authors: Akhila Potluru

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Worldwide, more than 250 bodies of water are transboundary, meaning they cross the political boundaries of multiple countries. This creates a system of hydrological, economic, and social interdependence between communities reliant on these water sources. Transboundary water conflicts can occur as a result of this intense interdependence. Many factors contribute to the sparking of transboundary water conflicts, ranging from natural hydrological factors to hydro-political interactions. Previous attempts to predict transboundary water conflicts by analysing changes or trends in the contributing factors have typically failed because patterns in the data are hard to identify. However, there is potential for artificial intelligence and machine learning to fill this gap and identify future ‘hotspots’ up to a year in advance by identifying patterns in data where humans can’t. This research determines the extent to which AI can be used to predict and prevent transboundary water conflicts. This is done via a critical literature review of previous case studies and datasets where AI was deployed to predict water conflict. This research not only delivered a more nuanced understanding of previously undervalued factors that contribute toward transboundary water conflicts (in particular, culture and disinformation) but also by detecting conflict early, governance bodies can engage in processes to de-escalate conflict by providing pre-emptive solutions. Looking forward, this gives rise to significant policy implications and water-sharing agreements, which may be able to prevent water conflicts from developing into wide-scale disasters. Additionally, AI can be used to gain a fuller picture of water-based conflicts in areas where security concerns mean it is not possible to have staff on the ground. Therefore, AI enhances not only the depth of our knowledge about transboundary water conflicts but also the breadth of our knowledge. With demand for water constantly growing, competition between countries over shared water will increasingly lead to water conflict. There has never been a more significant time for us to be able to accurately predict and take precautions to prevent global water conflicts.

Keywords: artificial intelligence, machine learning, transboundary water conflict, water management

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Authors: M. A. Barros, M. V. Barros

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The aim of this work is to analyze the discursive dynamics of preservice teachers during the implementation of a didactic sequence on topics of Quantum Mechanics for High School. Our research methodology was qualitative, case study type, in which we selected two prospective teachers on the Physics Teacher Training Course of the Sao Carlos Institute of Physics, at the University of Sao Paulo/Brazil. The set of modes of communication analyzed were the intentions and interventions of the teachers, the established communicative approach, the patterns and the contents of the interactions between teachers and students. Data were collected through video recording, interviews and questionnaires conducted before and after an 8 hour mini-course, which was offered to a group of 20 secondary students. As teaching strategy we used an active learning methodology, called: Peer Instruction. The episodes pointed out that both future teachers used interactive dialogic and authoritative communicative approaches to mediate the discussion between peers. In the interactive dialogic dimension the communication pattern was predominantly I-R-F (initiation-response-feedback), in which the future teachers assisted the students in the discussion by providing feedback to their initiations and contributing to the progress of the discussions between peers. Although the interactive dialogic dimension has been preferential during the use of the Peer Instruction method the authoritative communicative approach was also employed. In the authoritative dimension, future teachers used predominantly the type I-R-E (initiation-response-evaluation) communication pattern by asking the students several questions and leading them to the correct answer. Among the main implications the work contributes to the improvement of the practices of future teachers involved in applying active learning methodologies in classroom by identifying the types of communicative approaches and communication patterns used, as well as researches on curriculum innovation in physics in high school.

Keywords: curricular innovation, high school, physics teaching, discursive dynamics

Procedia PDF Downloads 181

Authors: Adu-Ampomah Yaw Junior

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Local procurement has become one of the latest trends in the discourse of sustainable tourism due to the economic benefits it generates for tourist destinations in developing countries. Local procurement helps in creating jobs which consequently helps in alleviating poverty. However, there have been limited studies on local procurement patterns in developing countries. Research on hotel procurement practices has mainly emphasized the challenges that hoteliers face when procuring locally, leaving questions regarding their motivations to engage in local procurement unanswered. The institutional theory provides a suitable framework to better understand these motivations as it underlines the importance of individual cognitive perceptions on issues in shaping organizational response strategies. More specifically, the extent to which an issue is perceived to belong to the organization’s responsibility. Also the organizational actors’ belief of losses or gains resultant from acting or not acting on an issue (degree of importance). Furthermore the organizational actors’ belief of the probability of resolving an issue (degree of feasibility). These factors influence how an organization will act on this issue. Hence, this paper adopts an institutional perspective to examine local procurement patterns of food by hoteliers in Ghana. Qualitative interviews with 20 procurement managers about their procurement practices and motivations, as well as interviews with different stakeholders for data triangulation purposes, indicated that most hotels sourced their food from middlemen who imported most of their products. However, direct importation was more prevalent foreign owned hotels as opposed to locally owned ones. Notwithstanding, the importation and the usage of foreign foods as opposed to local ones can be explained by the lack of pressure from NGOs and trade associations on hotels to act responsibly. Though guests’ menu preferences were perceived as important to hoteliers business operations, western tourists demand foreign food primarily with the foreign owned hotels make it less important to procure local produce. Lastly hoteliers, particularly those in foreign owned ones, perceive local procurement to be less feasible, raising concerns about quality and variety of local produce. The paper outlines strategies to improve the perception and degree of local Firstly, there is the need for stakeholder engagement in order to make hoteliers feel responsible for acting on the issue.Again it is crucial for Ghana government to promote and encourage hotels to buy local produce. Also, the government has to also make funds and storage facilities available for farmers to impact on the quality and quantity of local produce. Moreover, Sites need to be secured for farmers to engage in sustained farming.Furthermore, there is the need for collaborations between various stakeholders to organize training programs for farmers. Notwithstanding hotels need to market local produce to their guests. Finally, the Ghana hotels association has to encourage hotels to indulge in local procurement.

Keywords: sustainable tourism, feasible, important, local procurement

Procedia PDF Downloads 197

Authors: Eric Bang

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Interactions between receptors and ligands are crucial for many essential biological processes, including neurotransmission and metabolism. Ligand-receptor analyses that examine cell behavior and interactions often utilize cell type-specific RNA expressions from single-cell RNA sequencing (scRNA-seq) data. Using CellPhoneDB, a public repository consisting of ligands, receptors, and ligand-receptor interactions, the cell-cell interactions were explored in a specific scRNA-seq dataset from kidney tissue and portrayed the results with dot plots and heat maps. Depending on the type of cell, each ligand-receptor pair was aligned with the interacting cell type and calculated the positori probabilities of these associations, with corresponding P values reflecting average expression values between the triads and their significance. Using single-cell data (sample kidney cell references), genes in the dataset were cross-referenced with ones in the existing CellPhoneDB dataset. For example, a gene such as Pleiotrophin (PTN) present in the single-cell data also needed to be present in the CellPhoneDB dataset. Using the single-cell transcriptomics data via slide-seq and reference data, the CellPhoneDB program defines cell types and plots them in different formats, with the two main ones being dot plots and heat map plots. The dot plot displays derived measures of the cell to cell interaction scores and p values. For the dot plot, each row shows a ligand-receptor pair, and each column shows the two interacting cell types. CellPhoneDB defines interactions and interaction levels from the gene expression level, so since the p-value is on a -log10 scale, the larger dots represent more significant interactions. By performing an interaction analysis, a significant interaction was discovered for myeloid and T-cell ligand-receptor pairs, including those between Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1), which is consistent with previous findings. It was proposed that an effective protocol would involve a filtration step where cell types would be filtered out, depending on which ligand-receptor pair is activated in that part of the tissue, as well as the incorporation of the CellPhoneDB data in a streamlined workflow pipeline. The filtration step would be in the form of a Python script that expedites the manual process necessary for dataset filtration. Being in Python allows it to be integrated with the CellPhoneDB dataset for future workflow analysis. The manual process involves filtering cell types based on what ligand/receptor pair is activated in kidney cells. One limitation of this would be the fact that some pairings are activated in multiple cells at a time, so the manual manipulation of the data is reflected prior to analysis. Using the filtration script, accurate sorting is incorporated into the CellPhoneDB database rather than waiting until the output is produced and then subsequently applying spatial data. It was envisioned that this would reveal wherein the cell various ligands and receptors are interacting with different cell types, allowing for easier identification of which cells are being impacted and why, for the purpose of disease treatment. The hope is this new computational method utilizing spatially explicit ligand-receptor association data can be used to uncover previously unknown specific interactions within kidney tissue.

Keywords: bioinformatics, Ligands, kidney tissue, receptors, spatial transcriptome

Procedia PDF Downloads 139

Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

Procedia PDF Downloads 42

Authors: Alfonsina Buoniconto

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The aim of this study is to investigate the degree of cross-linguistic and intra-linguistic variation in the encoding of motion events (MEs) in English and Italian, these being typologically different languages both showing signs of disobedience to their respective types. As a matter of fact, the traditional typological classification of MEs encoding distributes languages into two macro-types, based on the preferred locus for the expression of Path, the main ME component (other components being Figure, Ground and Manner) characterized by conceptual and structural prominence. According to this model, Satellite-framed (SF) languages typically express Path information in verb-dependent items called satellites (e.g. preverbs and verb particles) with main verbs encoding Manner of motion; whereas Verb-framed languages (VF) tend to include Path information within the verbal locus, leaving Manner to adjuncts. Although this dichotomy is valid altogether, languages do not always behave according to their typical classification patterns. English, for example, is usually ascribed to the SF type due to the rich inventory of postverbal particles and phrasal verbs used to express spatial relations (i.e. the cat climbed down the tree); nevertheless, it is not uncommon to find constructions such as the fog descended slowly, which is typical of the VF type. Conversely, Italian is usually described as being VF (cf. Paolo uscì di corsa ‘Paolo went out running’), yet SF constructions like corse via in lacrime ‘She ran away in tears’ are also frequent. This paper will try to demonstrate that such a typological overlapping is due to the fact that the semantic units making up MEs are distributed within several loci of the sentence –not only verbs and satellites– thus determining a number of different constructions stemming from convergent factors. Indeed, the linguistic expression of motion events depends not only on the typological nature of languages in a traditional sense, but also on a series morphological, lexical, and syntactic resources, as well as on inferential, discursive, usage-related, and cultural factors that make semantic information more or less accessible, frequent, and easy to process. Hence, rather than describe English and Italian in dichotomic terms, this study focuses on the investigation of cross-linguistic and intra-linguistic variation in the use of all the strategies made available by each linguistic system to express motion. Evidence for these assumptions is provided by parallel corpora analysis. The sample texts are taken from two contemporary Italian novels and their respective English translations. The 400 motion occurrences selected (200 in English and 200 in Italian) were scanned according to the MODEG (an acronym for Motion Decoding Grid) methodology, which grants data comparability through the indexation and retrieval of combined morphosyntactic and semantic information at different levels of detail.

Keywords: construction typology, motion event encoding, parallel corpora, satellite-framed vs. verb-framed type

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Authors: Pouya Karimi, Ramin Ghasemi Shayan

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Conclusions of the sort and setting of observational treatment for immunocompromised patients with fever are confused by the qualities of the hidden disease and the impacts of medications previously got, just as by changing microbiological examples and patterns in sedate obstruction at national and institutional levels. A few frameworks have been proposed to recognize patients who could profit by outpatient anti-infection treatment from patients who require hospitalization. Useful contemplations may choose whether the fundamental checking during the time of neutropenia can be accomplished.

Keywords: microbiology, infectious, neutropenia, epidemiology

Procedia PDF Downloads 162

Authors: Retang A. Mokua, Julia Glenday, Jacobus M. Nel

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Understanding hydrological processes in mountain headwater catchments, such as the Jonkershoek Valley, is crucial for improving the predictive capability of hydrologic modeling in the Cape Fold Mountain region of South Africa, incorporating the influence of the Table Mountain Group fractured rock aquifers. Determining the contributions of various possible surface and subsurface flow pathways in such catchments has been a challenge due to the complex nature of the fractured rock geology, low ionic concentrations, high rainfall, and streamflow variability. The study aimed to describe the mechanisms of streamflow generation during two seasons (dry and wet). In this study, stable isotopes of water (18O and 2H), hydrochemical tracer electrical conductivity (EC), hydrometric data were used to assess the spatial and temporal variation in flow pathways and geographic sources of stream water. Stream water, groundwater, two shallow piezometers, and spring samples were routinely sampled at two adjacent headwater sub-catchments and analyzed for isotopic ratios during baseflow conditions between January 2018 and January 2019. From these results, no significance (p > 0.05) in seasonal variations in isotopic ratios were observed, the stream isotope signatures were consistent throughout the study period. However, significant seasonal and spatial variations in the EC were evident (p < 0.05). The findings suggest that, in the dry season, baseflow generation mechanisms driven by groundwater and interflow as discharge from perennial springs in these catchments are the primary contributors. The wet season flows were attributed to interflow and perennial and ephemeral springs. Furthermore, the observed seasonal variations in EC were indicative of a greater proportion of sub-surface water inputs. With these results, a conceptual model of streamflow generation processes for the two seasons was constructed.

Keywords: electrical conductivity, Jonkershoek valley, stable isotopes, table mountain group

Procedia PDF Downloads 109

Authors: Amanda Kavner, Richard Lamb

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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.

Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience

Procedia PDF Downloads 119

Authors: Hisham Mortada

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Transition in the urban configuration of Arab cities has never been as radical and visible as it has been since the turn of the last century. The emergence of new cities near historical settlements of Arabia has spawned a series of developments in and around the old city precincts. New developments are based on advanced technology and conform to globally prevalent standards of city planning, superseding the vernacular arrangements based on traditional norms that guided so-called ‘city planning’. Evidence to this fact are the extant Arab buildings present at the urban core of modern cities, which inform us about intricate spatial organization. Organization that subscribed to multiple norms such as, satisfying gender segregation and socialization, economic sustainability, and ensuring security and environmental coherence etc., within settlement compounds. Several participating factors achieved harmony in such an inclusive city—an organization that was challenged and apparently replaced by the new planning order in the face of growing needs of globalized, economy-centric and high-tech models of development. Communities found it difficult to acclimatize with the new western planning models that were implemented at a very large scale throughout the Kingdom, which later experienced spatial re-structuring to suit users’ needs. A closer look the ancient city of Yanbu, now flanked with such new developments, allows us to differentiate and track the beginnings of this unprecedented transition in settlement formations. This paper aims to elaborate the Arabian context offered to both the ‘traditional’ and ‘modern’ planning approaches, in order to understand challenges and solutions offered by both at different times. In the process it will also establish the inconsistencies and conflicts that arose with the shift in planning paradigm, from traditional-'cultural norms’, to modern-'physical planning', in the Arabian context. Thus, by distinguishing the two divergent planning philosophies, their impact of the Arabian morphology, relevance to lifestyle and suitability to the biophysical environment, it concludes with a perspective on sustainability particularly for in case of Yanbu.

Keywords: Yanbu, traditional architecture, Hijaz, coral building, Saudi Arabia

Procedia PDF Downloads 321

Authors: Brendah Nagula, Omolo Fredrick Okalebo, Ronald Ssengendo, Ivan Bamweyana

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The Kampala Physical Development Plan (KPDP) was developed in 2012 and projected both long term and short term developments within the City .The purpose of the plan was to not only shape the city into a spatially planned area but also to control the urban sprawl trends that had expanded with pronounced instances of informal settlements. This plan was approved by the National Physical Planning Board and a signature was appended by the Minister in 2013. Much as the KPDP plan has been implemented using different approaches such as detailed planning, development control, subdivision planning, carrying out construction inspections, greening and beautification, there is still limited knowledge on the level of conformance towards this plan. Therefore, it is yet to be determined whether it has been effective in shaping the City into an ideal spatially planned area. Attaining a clear picture of the level of conformance towards the KPDP 2012 through evaluation between the planned and the existing land use in Kampala City was performed. Methods such as Supervised Classification and Post Classification Change Detection were adopted to perform this evaluation. Scrutiny of findings revealed Central Division registered the lowest level of conformance to the planning standards specified in the KPDP 2012 followed by Nakawa, Rubaga, Kawempe, and Makindye. Furthermore, mixed-use development was identified as the land use with the highest level of non-conformity of 25.11% and institutional land use registered the highest level of conformance of 84.45 %. The results show that the aspect of location was not carefully considered while allocating uses in the KPDP whereby areas located near the Central Business District have higher land rents and hence require uses that ensure profit maximization. Also, the prominence of development towards mixed-use denotes an increased demand for land towards compact development that was not catered for in the plan. Therefore in order to transform Kampala city into a spatially planned area, there is need to carefully develop detailed plans especially for all the Central Division planning precincts indicating considerations for land use densification.

Keywords: spatial plan, post classification change detection, Kampala city, landuse

Procedia PDF Downloads 92

Authors: Saeed Farhadypour, Majid Azadi, Habibolla Sayyari, Mahmood Mosavi, Shahram Irani, Aliakbar Bidokhti, Omid Alizadeh Choobari, Ziba Hamidi

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In the recent decades, frequencies of dust events have increased significantly in west and south west of Iran. First, a survey on the dust events during the period (1990-2013) is investigated using historical dust data collected at 6 weather stations scattered over west and south-west of Iran. After statistical analysis of the observational data, one of the most severe dust storm event that occurred in the region from 3rd to 6th July 2009, is selected and analyzed. WRF-Chem model is used to simulate the amount of PM10 and how to transport it to the areas. The initial and lateral boundary conditions for model obtained from GFS data with 0.5°×0.5° spatial resolution. In the simulation, two aerosol schemas (GOCART and MADE/SORGAM) with 3 options (chem_opt=106,300 and 303) were evaluated. Results of the statistical analysis of the historical data showed that south west of Iran has high frequency of dust events, so that Bushehr station has the highest frequency between stations and Urmia station has the lowest frequency. Also in the period of 1990 to 2013, the years 2009 and 1998 with the amounts of 3221 and 100 respectively had the highest and lowest dust events and according to the monthly variation, June and July had the highest frequency of dust events and December had the lowest frequency. Besides, model results showed that the MADE / SORGAM scheme has predicted values and trends of PM10 better than the other schemes and has showed the better performance in comparison with the observations. Finally, distribution of PM10 and the wind surface maps obtained from numerical modeling showed that the formation of dust plums formed in Iraq and Syria and also transportation of them to the West and Southwest of Iran. In addition, comparing the MODIS satellite image acquired on 4th July 2009 with model output at the same time showed the good ability of WRF-Chem in simulating spatial distribution of dust.

Keywords: dust storm, MADE/SORGAM scheme, PM10, WRF-Chem

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Authors: Abdel Rahman Khider Hassan

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This paper describes a multi-criteria geospatial model for prediction of landslide hazard zonation (LHZ) for Lake Naivasha catchment (Kenya), based on spatial analysis of integrated datasets of location intrinsic parameters (slope stability factors) and external landslides triggering factors (natural and man-made factors). The intrinsic dataset included: lithology, geometry of slope (slope inclination, aspect, elevation, and curvature) and land use/land cover. The landslides triggering factors included: rainfall as the climatic factor, in addition to the destructive effects reflected by proximity of roads and drainage network to areas that are susceptible to landslides. No published study on landslides has been obtained for this area. Thus, digital datasets of the above spatial parameters were conveniently acquired, stored, manipulated and analyzed in a Geographical Information System (GIS) using a multi-criteria grid overlay technique (in ArcGIS 10.2.2 environment). Deduction of landslide hazard zonation is done by applying weights based on relative contribution of each parameter to the slope instability, and finally, the weighted parameters grids were overlaid together to generate a map of the potential landslide hazard zonation (LHZ) for the lake catchment. From the total surface of 3200 km² of the lake catchment, most of the region (78.7 %; 2518.4 km²) is susceptible to moderate landslide hazards, whilst about 13% (416 km²) is occurring under high hazards. Only 1.0% (32 km²) of the catchment is displaying very high landslide hazards, and the remaining area (7.3 %; 233.6 km²) displays low probability of landslide hazards. This result confirms the importance of steep slope angles, lithology, vegetation land cover and slope orientation (aspect) as the major determining factors of slope failures. The information provided by the produced map of landslide hazard zonation (LHZ) could lay the basis for decision making as well as mitigation and applications in avoiding potential losses caused by landslides in the Lake Naivasha catchment in the Kenya Highlands.

Keywords: decision making, geospatial, landslide, multi-criteria, Naivasha

Procedia PDF Downloads 206

Authors: Recep Kesli, Onur Turkyilmaz, Cengiz Demir

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Objective: Autoimmune collagen diseases occur with the immune reactions against the body’s own cell or tissues which cause inflammation and damage the tissues and organs. In this study, it was aimed to compare seropositivity rates and patterns of the anti-nuclear antibodies (ANA) in the diagnosis of four different autoimmune collagen tissue diseases (Rheumatoid Arthritis-RA, Systemic Lupus Erythematous-SLE, Scleroderma-SSc and Sjogren Syndrome-SS) with each other. Methods: One hundred eighty-eight patients applied to different clinics in Afyon Kocatepe University ANS Practice and Research Hospital between 11.07.2014 and 14.07.2015 that thought the different collagen disease such as RA, SLE, SSc and SS have participated in the study retrospectively. All the data obtained from the patients participated in the study were evaluated according to the included criteria. The historical archives belonging to the patients have been screened, assessed in terms of ANA positivity. The obtained data was analysed by using the descriptive statistics; chi-squared, Fischer's exact test. The evaluations were performed by SPSS 20.0 version and p < 0.05 level was considered as significant. Results: Distribution rates of the totally one hundred eighty-eight patients according to the diagnosis were found as follows: 82 (43.6%) were RA, 38 (20.2%) were SLE, 22 (11.7%) were SSc, and 46 (24.5%) were SS. Distribution of ANA positivity rates according to the collagen tissue diseases were found as follows; for RA were 54 (65,9 %), for SLE were 36 (94,7 %), for SSc were 18 (81,8 %), and for SS were 43 (93,5 %). Rheumatoid arthritis should be evaluated and classified as a different class among all the other investigated three autoimmune illnesses. ANA positivity rates were found as differently higher (91.5 %) in the SLE, SSc, and SS, from the RA (65.9 %). Differences at ANA positivity rates for RA and the other three diseases were found as statistically significant (p=0.015). Conclusions: Systemic autoimmune illnesses show broad spectrum. ANA positivity was found as an important predictor marker in the diagnosis of the rheumatologic illnesses. ANA positivity should be evaluated as more valuable and sensitive a predictor diagnostic marker in the laboratory findings of the SLE, SSc, and SS according to RA.

Keywords: antinuclear antibody (ANA), rheumatoid arthritis, scleroderma, Sjogren syndrome, systemic lupus Erythemotosus

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Authors: Remo Waser, Simon Maranda, Anastasia Stamatiou, Ludger J. Fischer, Joerg Worlitschek

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In latent heat storage, a phase change material (PCM) is used to store thermal energy. The heat transfer rate during solidification is limited and considered as a key challenge in the development of latent heat storages. Thus, finned heat exchangers (HEX) are often utilized to increase the heat transfer rate of the storage system. In this study, a new modeling approach to calculating the heat transfer rate in latent thermal energy storages with complex HEX geometries is presented. This model allows for an optimization of the HEX design in terms of costs and thermal performance of the system. Modeling solidification processes requires the calculation of time-dependent heat conduction with moving boundaries. Commonly used computational fluid dynamic (CFD) methods enable the analysis of the heat transfer in complex HEX geometries. If applied to the entire storage, the drawback of this approach is the high computational effort due to small time steps and fine computational grids required for accurate solutions. An alternative to describe the process of solidification is the so-called temperature-based approach. In order to minimize the computational effort, a quasi-stationary assumption can be applied. This approach provides highly accurate predictions for tube heat exchangers. However, it shows unsatisfactory results for more complex geometries such as finned tube heat exchangers. The presented simulation model uses a temporal and spatial discretization of heat exchanger tube. The spatial discretization is based on the smallest possible symmetric segment of the HEX. The heat flow in each segment is calculated using finite volume method. Since the heat transfer fluid temperature can be derived using energy conservation equations, the boundary conditions at the inner tube wall is dynamically updated for each time step and segment. The model allows a prediction of the thermal performance of latent thermal energy storage systems using complex HEX geometries with considerably low computational effort.

Keywords: modelling of solidification, finned tube heat exchanger, latent thermal energy storage

Procedia PDF Downloads 268