Search results for: data mapping

Authors: Zulkiflee Abd Latif, Sitinor Atikah Nordin, Alawi Sulaiman

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Different tree species possess different and various benefits. Arenga Pinnata tree species own several potential uses that is valuable for the economy and the country. Mapping vegetation using remote sensing technique involves various process, techniques and consideration. Using satellite imagery, this method enables the access of inaccessible area and with the availability of near infra-red band; it is useful in vegetation analysis, especially in identifying tree species. Pixel-based and object-based classification technique is used as a method in this study. Pixel-based classification technique used in this study divided into unsupervised and supervised classification. Object based classification technique becomes more popular another alternative method in classification process. Using spectral, texture, color and other information, to classify the target make object-based classification is a promising technique for classification. Classification of Arenga Pinnata trees is overlaid with elevation, slope and aspect, soil and river data and several other data to give information regarding the tree character and living environment. This paper will present the utilization of remote sensing technique in order to map Arenga Pinnata tree species

Keywords: Arenga Pinnata, pixel-based classification, object-based classification, remote sensing

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Authors: Mohd Azraei Pangah Pa'at, Mohd Ruzlin Mohd Mokhtar, Norhidayu Rameli, Tashia Marie Anthony, Huzainie Shafi Abd Halim

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Partial Discharge (PD) diagnostic mapping testing is one of the main diagnostic testing techniques that are widely used in the field or onsite testing for underground power cable in medium voltage level. The existence of PD activities is an early indication of insulation weakness hence early detection of PD activities can be determined and provides an initial prediction on the condition of the cable. To effectively manage the results of PD Mapping test, it is important to have acceptable criteria to facilitate prioritization of mitigation action. Tenaga Nasional Berhad (TNB) through Distribution Network (DN) division have developed PD severity model name Severity Index (SI) for offline PD mapping test since 2007 based on onsite test experience. However, this severity index recommendation action had never been revised since its establishment. At presence, PD measurements data have been extensively increased, hence the severity level indication and the effectiveness of the recommendation actions can be analyzed and verified again. Based on the new revision, the recommended action to be taken will be able to reflect the actual defect condition. Hence, will be accurately prioritizing preventive action plan and minimizing maintenance expenditure.

Keywords: partial discharge, severity index, diagnostic testing, medium voltage, power cable

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Authors: Felix Damilola Ajibade, Opeyemi O. Enoch, Taiwo Paul Fajusigbe

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This paper is centered on conducting an inquiry into the stability of the F* iterative algorithm to the fixed point of a strongly pseudo-contractive mapping in the framework of uniformly convex Banach spaces. To achieve the desired result, certain existing inequalities in convex Banach spaces were utilized, as well as the stability criteria of Harder and Hicks. Other necessary conditions for the stability of the F* algorithm on strong pseudo-contractive mapping were also obtained. Through a numerical approach, we prove that the F* iterative algorithm is H-stable for strongly pseudo-contractive mapping. Finally, the solution of the mixed-type Volterra-Fredholm functional non-linear integral equation is estimated using our results.

Keywords: stability, F* -iterative algorithm, pseudo-contractive mappings, uniformly convex Banach space, mixed-type Volterra-Fredholm integral equation

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Authors: Moschos Vogiatzis, K. Perakis

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Spatial-explicit and up-to-date land use/land cover information is fundamental for spatial planning, land management, sustainable development, and sound decision-making. In the last decade, many satellite-derived land cover products at different spatial, spectral, and temporal resolutions have been developed, such as the European Copernicus Land Cover product. However, more efficient and detailed information for land use/land cover is required at the regional or local scale. A typical Mediterranean basin with a complex landscape comprised of various forest types, crops, artificial surfaces, and wetlands was selected to test and develop our approach. In this study, we investigate the improvement of Copernicus Land Cover product (CLC2018) using Landsat 8 and Sentinel-2 pixel-based classification based on all available existing geospatial data (Forest Maps, LPIS, Natura2000 habitats, cadastral parcels, etc.). We examined and compared the performance of the Random Forest classifier for land use/land cover mapping. In total, 10 land use/land cover categories were recognized in Landsat 8 and 11 in Sentinel-2A. A comparison of the overall classification accuracies for 2018 shows that Landsat 8 classification accuracy was slightly higher than Sentinel-2A (82,99% vs. 80,30%). We concluded that the main land use/land cover types of CLC2018, even within a heterogeneous area, can be successfully mapped and updated according to CLC nomenclature. Future research should be oriented toward integrating spatiotemporal information from seasonal bands and spectral indexes in the classification process.

Keywords: classification, land use/land cover, mapping, random forest

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Authors: Jana Gutierez Chvalkovska, Michal Mejstrik, Matej Urban

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There are pending discussions over the mapping of country export potential in order to refocus export strategy of firms and its evidence-based promotion by the Export Credit Agencies (ECAs) and other permitted vehicles of governments. In this paper we develop our version of an applied model that offers “stepwise” elimination of unattractive markets. We modify and calibrate the model for the particular features of the Czech Republic and specific pilot cases where we apply an individual approach to each sector.

Keywords: export strategy, modeling export, calibration, export promotion

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Authors: S. Benchelha, H. Chennaoui, M. Hakdaoui, L. Baidder, H. Mansouri, H. Ejjaaouani, T. Benchelha

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Northern Morocco is characterized by relatively young mountains experiencing a very important dynamic compared to other areas of Morocco. The dynamics associated with the formation of the Rif chain (Alpine tectonics), is accompanied by instabilities essentially related to tectonic movements. The realization of important infrastructures (Roads, Highways,...) represents a triggering factor and favoring landslides. This paper is part of the establishment of landslides susceptibility map and concerns the mapping of unstable areas in the province of Taounate. The landslide was identified using the components of the false color (FCC) of images Landsat OLI: i) the first independent component (IC1), ii) The main component (PC), iii) Normalized difference index (NDI). This mapping for landslides class is validated by in-situ surveys.

Keywords: landslides, False Color Composite (FCC), Independent Component Analysis (ICA), Principal Component Analysis (PCA), Normalized Difference Index (NDI), Normalized Difference Mid Red Index (NDMIDR)

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Authors: Musyimi Mbathi

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Information regarding social, political, demographic, economic and other attributes of human settlement is important for decision makers at all levels of planning, as they have to grapple with dynamic environments often associated with settlements. At the local level, it is particularly important for both communities and urban managers to have accurate and reliable information regarding all planning attributes. Settlement mapping, in particular, informal settlements mapping in Kenya, has over the past few years been carried out using modern tools like Geographic information systems (GIS) and remote sensing for spatial data analysis and planning. GIS tools offer a platform for integration of spatial and non-spatial data as well as visualisation of the settlements. The capabilities offered by these tools have enabled communities to participate especially in the planning and management of new infrastructure as well as settlement upgrading. Land tenure based projects within informal settlements have also relied on GIS and related tools with considerable success. Additionally, the adoption of participatory approaches and use of geo-information tools helped to provide a basis for all inclusive planning thus promoting accountability, transparency, legitimacy, and other dimensions of governance within human settlement planning. The paper examines the context and application of geo-information tools for planning within low-income settlements of Kenya. A case study of Kiambiu settlement will be used to demonstrate how the tools have been applied for planning and decision-making purposes.

Keywords: informal settlements, GIS, governance, modern tools

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Authors: Noman Ahmed, Fariha Tahseen

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Since several decades, unplanned urbanization and rapid growth of informal settlements have evolved and increased in size and number. Large cities such as Karachi have been impacted with sprawl and rising share of unplanned settlements where poor communities reside. Threats of eviction, deteriorating law and order situation, lack of essential amenities and infrastructure, extortion and bullying from local and non-local musclemen and feeble response of government agencies towards their development needs are some predicaments. Non-governmental organizations (NGOs) have caused important interventions in such locations. Appraisal of the community-based mapping as a tool in supporting the development work in less privileged areas in Karachi has been the objective of this research. The Orangi Pilot Project (OPP), under the leadership of its slain director Perween Rahman had a significant role to play in developing and extending this approach in low income locations in Karachi and beyond. The paper investigates the application of mapping in the process of peri urban land invasion causing rapid transformation of traditional settlements in Karachi. Mixed methodology components comprising literature review, archival research, and unstructured interviews with key informants and case studies have been used.

Keywords: squatters (katchi abadis), land grabbing, community empowerment, housing rights, mapping, infrastructure development

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Authors: Anne C. Richer-De-Forges, Dominique Arrouays, Songchao Chen, Mercedes Roman Dobarco

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Most of the digital soil mapping (DSM) products rely on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs. However, many other observations (often qualitative, nominal, or ordinal) could be used as proxies of lab measurements or as input data for ML of PTF predictions. DSM and ML are briefly described with some examples taken from the literature. Then, we explore the potential of an ordinal qualitative variable, i.e., the hand-feel soil texture (HFST) estimating the mineral particle distribution (PSD): % of clay (0-2µm), silt (2-50µm) and sand (50-2000µm) in 15 classes. The PSD can also be measured by lab measurements (LAST) to determine the exact proportion of these particle-sizes. However, due to cost constraints, HFST are much more numerous and spatially dense than LAST. Soil texture (ST) is a very important soil parameter to map as it is controlling many of the soil properties and functions. Therefore, comes an essential question: is it possible to use HFST as a proxy of LAST for calibration and/or validation of DSM predictions of ST? To answer this question, the first step is to compare HFST with LAST on a representative set where both information are available. This comparison was made on ca 17,400 samples representative of a French region (34,000 km2). The accuracy of HFST was assessed, and each HFST class was characterized by a probability distribution function (PDF) of its LAST values. This enables to randomly replace HFST observations by LAST values while respecting the PDF previously calculated and results in a very large increase of observations available for the calibration or validation of PTF and ML predictions. Some preliminary results are shown. First, the comparison between HFST classes and LAST analyses showed that accuracies could be considered very good when compared to other studies. The causes of some inconsistencies were explored and most of them were well explained by other soil characteristics. Then we show some examples applying these relationships and the increase of data to several issues related to DSM. The first issue is: do the PDF functions that were established enable to use HSFT class observations to improve the LAST soil texture prediction? For this objective, we replaced all HFST for topsoil by values from the PDF 100 time replicates). Results were promising for the PTF we tested (a PTF predicting soil water holding capacity). For the question related to the ML prediction of LAST soil texture on the region, we did the same kind of replacement, but we implemented a 10-fold cross-validation using points where we had LAST values. We obtained only preliminary results but they were rather promising. Then we show another example illustrating the potential of using HFST as validation data. As in numerous countries, the HFST observations are very numerous; these promising results pave the way to an important improvement of DSM products in all the countries of the world.

Keywords: digital soil mapping, improvement of digital soil mapping predictions, potential of using hand-feel soil texture, soil texture prediction

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Authors: Danuvasin Charoen

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This research investigates cluster development in the area called the Greater Mekong Subregion (GMS), which consists of Thailand, the People’s Republic of China (PRC), the Yunnan Province and Guangxi Zhuang Autonomous Region, Myanmar, the Lao People’s Democratic Republic (Lao PDR), Cambodia, and Vietnam. The study utilized Porter’s competitiveness theory and the cluster mapping approach to analyze the competitiveness of the region. The data collection consists of interviews, focus groups, and the analysis of secondary data. The findings identify some evidence of cluster development in the GMS; however, there is no clear indication of collaboration among the components in the clusters. GMS clusters tend to be stand-alone. The clusters in Vietnam, Lao PDR, Myanmar, and Cambodia tend to be labor intensive, whereas the clusters in Thailand and the PRC (Yunnan) have the potential to successfully develop into innovative clusters. The collaboration and integration among the clusters in the GMS area are promising, though it could take a long time. The most likely relationship between the GMS countries could be, for example, suppliers of the low-end, labor-intensive products will be located in the low income countries such as Myanmar, Lao PDR, and Cambodia, and these countries will be providing input materials for innovative clusters in the middle income countries such as Thailand and the PRC.

Keywords: cluster, GMS, competitiveness, development

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Authors: Abida Haddouche, Ahmed Chrif Toubal

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The Neogene basin of the Eastern Mitidja, object of the study area, represents potential water resources and especially groundwater reserves. This water is an important economic; this resource is highly sensitive which need protection and preservation. Unfortunately, these waters are exposed to various forms of pollution, whether from urban, agricultural, industrial or merely accidental. This pollution is a permanent risk of limiting resource. In this context, the work aims to evaluate the intrinsic vulnerability of the aquifer to protect and preserve the quality of this resource. It will focus on the disposal of water and land managers a cartographic document accessible to locate the areas where the water has a high vulnerability. Vulnerability mapping of the Easter Mitidja quaternary aquifer is performed by applying three methods (DRASTIC, DRIST, and GOD). Comparison and validation results show that the DRASTIC method is the most suitable method for aquifer vulnerability of the study area.

Keywords: Aquifer of Mitidja, DRASTIC method, geographic information system (GIS), vulnerability mapping

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Authors: Pavel Chmelar, Martin Dobrovolny

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Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

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Authors: Masood Beheshtirad

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Identification of regions having potential for landslide occurrence is one of the basic measures in natural resources management. Different landslide hazard mapping models are proposed based on the environmental condition and goals. In this research landslide hazard map using multiple regression model were provided and applicability of this model is investigated in Baghdasht watershed. Dependent variable is landslide inventory map and independent variables consist of information layers as Geology, slope, aspect, distance from river, distance from road, fault and land use. For doing this, existing landslides have been identified and an inventory map made. The landslide hazard map is based on the multiple regression provided. The level of similarity potential hazard classes and figures of this model were compared with the landslide inventory map in the SPSS environments. Results of research showed that there is a significant correlation between the potential hazard classes and figures with area of the landslides. The multiple regression model is suitable for application in the Baghdasht Watershed.

Keywords: landslide, mapping, multiple model, regression

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Authors: Jaechun No

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As the technology of NAND flash memory rapidly grows, SSD is becoming an excellent alternative for storage solutions, because of its high random I/O throughput and low power consumption. These SSD potentials have drawn great attention from IT enterprises that seek for better I/O performance. However, high SSD cost per capacity makes it less desirable to construct a large-scale storage subsystem solely composed of SSD devices. An alternative is to build a hybrid storage subsystem where both HDD and SSD devices are incorporated in an economic manner, while employing the strengths of both devices. This paper presents a hybrid file system, called hybridFS, that attempts to utilize the advantages of HDD and SSD devices, to provide a single, virtual address space by integrating both devices. HybridFS not only proposes an efficient implementation for the file management in the hybrid storage subsystem but also suggests an experimental framework for making use of the excellent features of existing file systems. Several performance evaluations were conducted to verify the effectiveness and suitability of hybridFS.

Keywords: hybrid file mapping, data layout, hybrid device integration, extent allocation

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Authors: Techale B., Hongxu Dong, Mihrete Getinet, Aregash Gabizew, Andrew H. Paterson, Kassahun Bantte

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The genetic architecture of drought tolerance is expected to involve multiple loci that are unlikely to all segregate for alternative alleles in a single bi-parental population. Therefore, the identification of quantitative trait loci (QTL) that are expressed in diverse genetic backgrounds of multiple bi-parental populations provides evidence about both background-specific and common genetic variants. The purpose of this study was to map QTL related to drought tolerance using three connected mapping populations of different genetic backgrounds to gain insight into the genomic landscape of this important trait in elite Ethiopian germplasm. The three bi-parental populations, each with 207 F₂:₃ lines, were evaluated using an alpha lattice design with two replications under two moisture stress environments. Drought tolerance related traits were analyzed separately for each population using composite interval mapping, finding a total of 105 QTLs. All the QTLs identified from individual populations were projected on a combined consensus map, comprising a total of 25 meta QTLs for seven traits. The consensus map allowed us to deduce locations of a larger number of markers than possible in any individual map, providing a reference for genetic studies in different genetic backgrounds. The mQTL identified in this study could be used for marker-assisted breeding programs in sorghum after validation. Only one trait, reduced leaf senescence, showed a striking bias of allele distribution, indicating substantial standing variation among present varieties that might be employed in improving drought tolerance of Ethiopian and other sorghums.

Keywords: Drought tolerance , Mapping populations, Meta QTL, QTL mapping, Sorghum

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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: Poonam Yadav, Dong Bok Lee

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Raman spectroscopy was used for characterization of multi-wall carbon nanotube (MWNT) and Polycarbonate/multi-wall carbon nanotube (PC/MWNT) based fibers with 0.55% and 0.75% of MWNT (PC/MWNT55 and PC/MWNT75). PC/MWNT55 and PC/MWNT75 fibers was prepared by melt spinning device using nanocomposites made by two different route, viz., solvent casting and melt extrusion. Fibers prepared from melt extruded nanocomposites showed smooth and uniform morphology as compared to solvent casting based nanocomposites. The Raman mapping confirmed that the melt extruded based nanocomposites had better dispersion of MWNT in Polycarbonate (PC) than solvent casting carbon nanotube.

Keywords: dispersion, melt extrusion, multi-wall carbon nanotube, mapping

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Authors: Tanapat Chongkamunkong

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The objective of this paper is to present a practical use of Geographic Information System (GIS) to the public health from spatial correlation between multiple factors and dengue fever outbreak. Meteorological factors, demographic factors and environmental factors are compiled using GIS techniques along with the Global Satellite Mapping Remote Sensing (RS) data. We use monthly dengue fever cases, population density, precipitation, Digital Elevation Model (DEM) data. The scope cover study area under climate change of the El Niño–Southern Oscillation (ENSO) indicated by sea surface temperature (SST) and study area in 12 provinces of Thailand as remote sensing (RS) data from January 2007 to December 2014.

Keywords: dengue fever, sea surface temperature, Geographic Information System (GIS), remote sensing

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Authors: Isa Muhammad Zumo

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Malaria is one of the worst illnesses that may affect humans. It is typically transmitted by the bite of a female Anopheles mosquito and is caused by parasitic protozoans from the Plasmodium parasite. Government and non-governmental organizations made numerous initiatives to combat the threat of malaria in communities. Nevertheless, the necessary attention was not paid to accurate and current information regarding the size and location of these favourable locations for mosquito development. Because mosquitoes can only reproduce in specific habitats with surface water, this study will locate and map those favourable sites that act as mosquito breeding grounds. Spatial and attribute data relating to favourable mosquito breeding places will be collected and analysed using Geographic Information Systems (GIS). The major findings will be in five classes, showing the vulnerable and risky areas for malaria cases. These risk categories are very high, high, moderate, low, and extremely low vulnerable areas. The maps produced by this study will be of great use to the health department in combating the malaria pandemic.

Keywords: Malaria, vulnerability, mapping, space, Damaturu

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Authors: Busiswa Madikazi

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This systematic mapping study explores the underrepresentation of women's contributions to farming in the Global South within the development of Information and Communication Technologies (ICT)-based extension methods. Despite women farmers constituting 70% of the agricultural labour force, their productivity is hindered by various constraints, including illiteracy, household commitments, and limited access to credit and markets. A systematic mapping approach was employed with the aim of identifying evidence gaps in existing ICT extension for women farmers. The data collection protocol follows a structured approach, incorporating key criteria for inclusion, exclusion, search strategy, and coding and the PICO strategy (Population, Intervention, Comparator, and Outcome). The results yielded 119 articles that qualified for inclusion. The findings highlight that mobile phone apps (WhatsApp) and radio/television programming are the primary extension methods employed while integrating ICT with training, field visits, and demonstrations are underutilized. Notably, the study emphasizes the inadequate attention to critical issues such as food security, gender equality, and attracting youth to farming within ICT extension efforts. These findings indicate a significant policy and practice gap, neglecting community-driven approaches that cater to women's specific needs and enhance their agricultural production. Map highlights the importance of refocusing ICT extension efforts to address women farmers’ unique challenges, thereby contributing to their empowerment and improving agricultural practices.

Keywords: agricultural extension, ICT, women farmers, smallholders

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Authors: Deepak Kumar, Debasish Deb, Reena Mamgain

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Radar signal processing requires high number crunching capability. Most often this is achieved using multiprocessor platform. Though multiprocessor platform provides the capability of meeting the real time computational challenges, the architecture of the same along with mapping of the algorithm on the architecture plays a vital role in efficiently using the platform. Towards this, along with standard performance metrics, few additional metrics are defined which helps in evaluating the multiprocessor platform along with the algorithm mapping. A generic multiprocessor architecture can not suit all the processing requirements. Depending on the system requirement and type of algorithms used, the most suitable architecture for the given problem is decided. In the paper, we study different architectures and quantify the different performance metrics which enables comparison of different architectures for their merit. We also carried out case study of different architectures and their efficiency depending on parallelism exploited on algorithm or data or both.

Keywords: radar signal processing, multiprocessor architecture, efficiency, load imbalance, buffer requirement, pipeline, parallel, hybrid, cluster of processors (COPs)

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Authors: Fitri CaturLestari

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According to National Population and Family Planning Board (BKKBN), demographic bonus will occur in 2025-2035, when the number of people within the productive age bracket is higher than the number of elderly people and children. This time will be a gold moment for Indonesia to achieve maximum productivity and prosperity. But it will be a demographic bomb if it isn’t balanced by economic and social aspect considerations. Therefore it is important to make a prediction mapping of all provinces in Indonesia whether in demographic bomb or bonus condition after 100 years Indonesian independence. The purpose of this research were to make the demographic mapping based on the economic and social aspects of the provinces in Indonesia and categorizing them into demographic bomb and bonus condition. The research data are gained from Statistics Indonesia (BPS) as the secondary data. The multiregional component method, regression and quadrant analysis were used to predict the number of people, economic growth, Human Development Index (HDI), and gender equality in education and employment. There were different characteristic of provinces in Indonesia from economic aspect and social aspect. The west Indonesia was already better developed than the east one. The prediction result, many provinces in Indonesia will get demographic bonus but the others will get demographic bomb. It is important to prepare particular strategy to particular provinces with all of their characteristic based on the prediction result so the demographic bomb can be minimalized.

Keywords: demography, economic growth, gender, HDI

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Authors: K. C. R. Perera, B. M. Hapuwatte

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This paper presents an effective method to divide panels for mesh-less methods of source, vortex and doublet panel methods. In this research study the physical domain of air-foils were transformed into computational domain of a circle using conformal mapping technique of Joukowsky transformation. Then the circle is divided into panels of equal length and the co-ordinates were remapped into physical domain of the air-foil. With this method the leading edge and the trailing edge of the air-foil is panelled with a high density of panels and the rest of the body is panelled with low density of panels. The high density of panels in the leading edge and the trailing edge will increase the accuracy of the solutions obtained from panel methods where the fluid flow at the leading and trailing edges are complex.

Keywords: conformal mapping, Joukowsky transformation, physical domain, computational domain

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Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

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Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

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Authors: Barbora Haltofová

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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: Seonaid Hume, Gordon Dobie, Graeme West

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Detecting and localizing radioactive sources is a necessity for safe and secure decommissioning of nuclear facilities. An important aspect for the management of the sort-and-segregation process is establishing the spatial distributions and quantities of the waste radionuclides, their type, corresponding activity, and ultimately classification for disposal. The data received from surveys directly informs decommissioning plans, on-site incident management strategies, the approach needed for a new cell, as well as protecting the workforce and the public. Manual classification of nuclear waste from a nuclear cell is time-consuming, expensive, and requires significant expertise to make the classification judgment call. Also, in-cell decommissioning is still in its relative infancy, and few techniques are well-developed. As with any repetitive and routine tasks, there is the opportunity to improve the task of classifying nuclear waste using autonomous systems. Hence, this paper proposes a new framework for the automatic classification of nuclear waste. This framework consists of five main stages; 3D spatial mapping and object detection, object classification, radiological mapping, source localisation based on gathered evidence and finally, waste classification. The first stage of the framework, 3D visual mapping, involves object detection from point cloud data. A review of related applications in other industries is provided, and recommendations for approaches for waste classification are made. Object detection focusses initially on cylindrical objects since pipework is significant in nuclear cells and indeed any industrial site. The approach can be extended to other commonly occurring primitives such as spheres and cubes. This is in preparation of stage two, characterizing the point cloud data and estimating the dimensions, material, degradation, and mass of the objects detected in order to feature match them to an inventory of possible items found in that nuclear cell. Many items in nuclear cells are one-offs, have limited or poor drawings available, or have been modified since installation, and have complex interiors, which often and inadvertently pose difficulties when accessing certain zones and identifying waste remotely. Hence, this may require expert input to feature match objects. The third stage, radiological mapping, is similar in order to facilitate the characterization of the nuclear cell in terms of radiation fields, including the type of radiation, activity, and location within the nuclear cell. The fourth stage of the framework takes the visual map for stage 1, the object characterization from stage 2, and radiation map from stage 3 and fuses them together, providing a more detailed scene of the nuclear cell by identifying the location of radioactive materials in three dimensions. The last stage involves combining the evidence from the fused data sets to reveal the classification of the waste in Bq/kg, thus enabling better decision making and monitoring for in-cell decommissioning. The presentation of the framework is supported by representative case study data drawn from an application in decommissioning from a UK nuclear facility. This framework utilises recent advancements of the detection and mapping capabilities of complex radiation fields in three dimensions to make the process of classifying nuclear waste faster, more reliable, cost-effective and safer.

Keywords: nuclear decommissioning, radiation detection, object detection, waste classification

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Authors: T. Yuri, M. Zagloel, Inaki M. Hakim, Tegu Bintang Nugraha

Abstract:

In an era of customer centricity, automotive parts manufacturer in Indonesia must be able to keep up with the uncertainty and fluctuation of consumer demand. Flexible Manufacturing System (FMS) is a strategy to react to predicted and unpredicted changes of demand in automotive industry. This research is about flexible mixed model assembly line design through Value Stream Mapping (VSM) and Line Balancing in mixed model assembly line prior to simulation. It uses value stream mapping to identify and reduce waste while finding the best position to add or reduce manpower. Line balancing is conducted to minimize or maximize production rate while increasing assembly line productivity and efficiency. Results of this research is a recommendation of standard work combination for specifics demand scenario which can enhance assembly line efficiency and productivity.

Keywords: automotive industry, demand uncertainty, flexible assembly system, line balancing, value stream mapping

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Authors: Hina Iqbal, Mustansar Ali Ghazanfar, Sandor Szedmak

Abstract:

Recommender systems uses artificial intelligence practices for filtering obscure information and can predict if a user likes a specified item. Kernel mapping Recommender systems have been proposed which are accurate and state-of-the-art algorithms and resolve recommender system’s design objectives such as; long tail, cold-start, and sparsity. The aim of research is to propose hybrid framework that can efficiently integrate different versions— namely item-based and user-based KMR— of KMR algorithm. We have proposed various heuristic algorithms that integrate different versions of KMR (into a unified framework) resulting in improved accuracy and elimination of problems associated with conventional recommender system. We have tested our system on publically available movies dataset and benchmark with KMR. The results (in terms of accuracy, precision, recall, F1 measure and ROC metrics) reveal that the proposed algorithm is quite accurate especially under cold-start and sparse scenarios.

Keywords: Kernel Mapping Recommender Systems, hybrid recommender systems, cold start, sparsity, long tail

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Authors: Susanna Pho

Abstract:

With the rise in frequency of high impact flooding events and continued growth across the state, communities in Florida are increasingly turning to innovative higher regulatory standards to keep residents safe. Using models and maps that take future conditions into account can help coastal communities at high risk of flooding adapt, but the associated responsibilities of enforcing and educating stakeholders about floodplain management can be a barrier to adoption. This is especially true in communities that are already managing multiple maps, as adding more regulatory mapping may overwhelm resource-constrained building departments. Without effective workflow solutions, even small tasks like communicating regulations to residents or determining the most restrictive mapping for a permit application can become challenging when dealing with complex maps. Using the case study of Forerunner’s work with a partner community, this session will outline how the community combines technology with robust outreach strategies to boost resident communication. We’ll discuss how software like Forerunner can help communities pull together disparate datasets and mobilize information for property-specific outreach to provide smarter resources to a variety of stakeholders. it’ll explore how incorporating digital workflows into outreach can ensure faster response time, better compliance enforcement, and stronger data continuity. The presentation will also include suggestions on how other communities might be able to leverage data to strengthen their floodplain management programs.

Keywords: floodplain management, flood response, flood risk adaptation, flood protection - products and processes, flood risk assessment and recovery, innovative approaches

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Authors: G. Yakubova, A. Kavetskiy, S. A. Prior, H. A. Torbert

Abstract:

In-situ soil carbon determination over large soil surface areas (several hectares) is required in regard to carbon sequestration and carbon credit issues. This capability is important for optimizing modern agricultural practices and enhancing soil science knowledge. Collecting and processing representative field soil cores for traditional laboratory chemical analysis is labor-intensive and time-consuming. The neutron-stimulated gamma analysis method can be used for in-situ measurements of primary elements in agricultural soils (e.g., Si, Al, O, C, Fe, and H). This non-destructive method can assess several elements in large soil volumes with no need for sample preparation. Neutron-gamma soil elemental analysis utilizes gamma rays issued from different neutron-nuclei interactions. This process has become possible due to the availability of commercial portable pulse neutron generators, high-efficiency gamma detectors, reliable electronics, and measurement/data processing software complimented by advances in state-of-the-art nuclear physics methods. In Pulsed Fast Thermal Neutron Analysis (PFTNA), soil irradiation is accomplished using a pulsed neutron flux, and gamma spectra acquisition occurs both during and between pulses. This method allows the inelastic neutron scattering (INS) gamma spectrum to be separated from the thermal neutron capture (TNC) spectrum. Based on PFTNA, a mobile system for field-scale soil elemental determinations (primarily carbon) was developed and constructed. Our scanning methodology acquires data that can be directly used for creating soil elemental distribution maps (based on ArcGIS software) in a reasonable timeframe (~20-30 hectares per working day). Created maps are suitable for both agricultural purposes and carbon sequestration estimates. The measurement system design, spectra acquisition process, strategy for acquiring field-scale carbon content data, and mapping of agricultural fields will be discussed.

Keywords: neutron gamma analysis, soil elemental content, carbon sequestration, carbon credit, soil gamma spectroscopy, portable neutron generators, ArcMap mapping

Procedia PDF Downloads 61