Search results for: DC ground faults

Authors: Albert Herve Nkolo Mpoko

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The Foreign Direct Investment (FDI) landscape in Cameroon has garnered significant attention from both European and Asian nations due to perceived benefits such as capital infusion, technology transfer, and potential for economic expansion. However, it is noteworthy that South Africa's investment presence remains comparatively subdued in Cameroon, lagging behind that of Europe and Asia. Equally surprising is the limited footprint of Africa's economic powerhouse within other African economies. This study delved into four specific facets of South African investment in Cameroon. Initially, it focused on identifying South African companies operating within Cameroon. Subsequently, the analysis encompassed assessing the correlation between South African investment and poverty alleviation. Additionally, the study examined the nexus between South African investment and technological advancement, and underscored the significance of investment incentives in both countries Key findings of the research shed light on several crucial points. South Africa ought to reassess its economic engagement with Francophone Africa, particularly Cameroon. Despite existing policies aimed at fostering investment, there remains substantial ground to cover in this realm. The proliferation of South African enterprises in Cameroon holds the potential to ameliorate poverty and foster employment opportunities across both nations. The advent of South African firms in Cameroon can catalyse technological advancements within the region. Data collection involved surveying 100 executives from the respective administrations and conducting ten interviews. The gathered data underwent triangulation, wherein quantitative findings were juxtaposed with qualitative insights. In conclusion, the study underscores the underutilization of Cameroon by South Africa, emphasizing the untapped potential for mutual economic growth. Furthermore, it posits that the success of South Africa's multinational corporations abroad could serve as a pivotal pillar for sustaining its domestic economy.

Keywords: FDI, transfer of technology, South-South cooperation, mutual economic growth

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Authors: Julian Y. Raheema, Michael R. Hess, Raymond C. Provost, Mark Bilinski

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The world is rapidly moving towards advancing and utilizing artificial intelligence and autonomous robotics. The ground-breaking Boston Dynamics quadruped robot, SPOT, was designed for industrial and commercial tasks requiring limited autonomous navigation. Out of the box, SPOT has route memorization and playback – it can repeat a path that it has been manually piloted through, but it cannot autonomously navigate an area that has not been previously explored. The presented SPOT payload package is built on ROS framework to support autonomous navigation and mapping of an unexplored environment. The package is fully integrated with SPOT to take advantage of motor controls and collision avoidance that comes natively with the robot. The payload runs all computations onboard, takes advantage of visual odometry SLAM and uses an Intel RealSense depth camera and Velodyne LiDAR sensor to generate 2D and 3D maps while in autonomous navigation mode. These maps are fused into the navigation stack to generate a costmap to enable the robot to safely navigate the environment without causing damage to the surroundings or the robot. The operator defines the operational zone and start location and then sends the explore command to have SPOT explore, generate 2D and 3D maps of the environment and return to the start location to await the operator's next command. The benefit of the presented package is that it is much lighter weight and less expensive than previous approaches and, importantly, operates in GPS-denied scenarios, which is ideal for indoor mapping. There are numerous applications that are hazardous to humans for SPOT enhanced with the autonomy payload, including disaster response, nuclear inspection, mine inspection, and so on. Other less extreme uses cases include autonomous 3D and 2D scanning of facilities for inspection, engineering and construction purposes.

Keywords: autonomous, SLAM, quadruped, mapping, exploring, ROS, robotics, navigation

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Authors: Tz-Bang Du, Cheng-Han Hsieh, Li-Ping Ju, Hung-Jie Liou

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Polyether amines synthesize by secondary hydroxyl polyether diol play an important role in epoxy hardener. The low molecular weight product is used in low viscosity and high transparent polyamine product for the logo, ground cover, especially for wind turbine blade, while the high molecular weight products are used in advanced agricultures such as a high-speed railway. High-pressure reductive amination process is required for producing these amines. In the condition of higher than 150 atm pressure and 200 degrees Celsius temperature, supercritical ammonia is used as a reactant and also a solvent. It would be a great challenge to select a catalyst support for such high-temperature alkaline circumstance. In this study, we have established a six-autoclave-type (SAT) high-pressure reactor for amination catalyst screening, which six experiment conditions with different temperature and pressure could be examined at the same time. We synthesized copper-nickel catalyst on different shaped alumina catalyst support and evaluated the catalyst activity for high-pressure reductive amination of polypropylene glycol (PPG) by SAT reactor. Ball type gamma alumina, ball type activated alumina and pellet type gamma alumina catalyst supports are evaluated in this study. Gamma alumina supports have shown better activity on PPG reductive amination than activated alumina support. In addition, the catalysts are evaluated in fixed bed reactor. The diamine product was successfully synthesized via this catalyst and the strength of the catalysts is measured. The crush strength of blank supports is about 13.5 lb for both gamma alumina and activated alumina. The strength increases to 20.3 lb after synthesized to be copper-nickel catalyst. After test in the fixed bed high-pressure reductive amination process for 100 hours, the crush strength of the used catalyst is 3.7 lb for activated alumina support, 12.0 lb for gamma alumina support. The gamma alumina is better than activated alumina to use as catalyst support in high-pressure reductive amination process.

Keywords: high pressure reductive amination, copper nickel catalyst, polyether amine, alumina

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Authors: Orod Zarrin, Mohesn Ramezan Shirazi, Hassan Moniri

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The use of pile foundations technique is developed to support structures and buildings on soft soil. The most important dynamic load that can affect the pile structure is earthquake vibrations. From the 1960s the comprehensive investigation of pile foundations during earthquake excitation indicate that, piles are subject to damage by affecting the superstructure integrity and serviceability. The main part of these research has been focused on the behavior of liquefiable soil and lateral spreading load on piles. During an earthquake, two types of stresses can damage the pile head, inertial load that is caused by superstructure and deformation which caused by the surrounding soil. Soil deformation and inertial load are associated with the acceleration developed in an earthquake. The acceleration amplitude at the ground surface depends on the magnitude of earthquakes, soil properties and seismic source distance. According to the investigation, the damage is between the liquefiable and non-liquefiable layers and also soft and stiff layers. This damage crushes the pile head by increasing the inertial load which is applied by the superstructure. On the other hand, the cracks on the piles due to the surrounding soil are directly related to the soil profile and causes cracks from small to large. And researchers have been listed the large cracks reason such as liquefaction, lateral spreading and inertial load. In the field of designing, elastic response of piles are always a challenge for designer in liquefaction soil, by allowing deflection at top of piles. Moreover, absence of plastic hinges in piles should be insured, because the damage in the piles is not observed directly. In this study, the performance and behavior of pile foundations during liquefaction and lateral spreading are investigated. And emphasize on the soil behavior in the liquefiable and non-liquefiable layers by different aspect of piles damage such as ranking, location and degree of damage are going to discuss.

Keywords: self-compacting concrete, fiber, tensile strength, post-cracking, direct and inverse technique

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Authors: Asis Kumar Khan, Rajeev Kumar Goel

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Recent infrastructure growth all around the world lead to increase in demand for concrete day by day. Cement being binding material for concrete the usage of cement also gone up significantly. Cement manufacturing utilizes abundant natural resources and causes environment pollution by releasing a huge quantity of CO₂ into the atmosphere. So, it is high time to look for alternates to reduce the cement consumption in concrete. Geopolymer concrete is one such material which utilizes the industrial waste such as fly ash, ground granulated blast furnace slag and low-cost alkaline liquids such as sodium hydroxide and sodium silicate to produce the concrete. On the other side, river sand is becoming very expensive due to its large-scale depletion at source and the high cost of transportation. In this view, river sand is replaced by crushed sand in this study. In this work, an attempt has been made to understand the durability parameters of geopolymer concrete by partially replacing fly ash with cement. Fly ash is replaced by cement at various levels e.g., from 0 to 50%. Concrete cubes of 100x100x100mm were used for investigating different durability parameters. The various parameters studied includes compressive strength, split tensile strength, drying shrinkage, sodium sulphate attack resistance, sulphuric acid attack resistance and chloride permeability. Highest compressive strength & highest split tensile strength is observed in 30% replacement level. Least drying is observed with 30% replacement level. Very good resistance for sulphuric acid & sodium sulphate is found with 30% replacement. However, it was not possible to find out the chloride permeability due to the high conductivity of geopolymer samples of all replacement levels.

Keywords: crushed sand, compressive strength, drying shrinkage, geopolymer concrete, split tensile strength, sodium sulphate attack resistance, sulphuric acid attack resistance

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Authors: Hadj Sahraoui Omar, Kebir Lahcen Wahib, Bennia Ahmed

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Interferometric Synthetic Aperture Radar (InSAR) coherence is a crucial parameter for accurately monitoring ground deformation and environmental changes. However, coherence can be degraded by various factors such as temporal decorrelation, atmospheric disturbances, and geometric misalignments, limiting the reliability of InSAR measurements (Omar Hadj‐Sahraoui and al. 2019). To address this challenge, we propose an innovative hybrid approach that combines artificial intelligence (AI) with advanced filtering techniques to optimize interferometric coherence in InSAR data. Specifically, we introduce a Convolutional Neural Network (CNN) integrated with the Lee filter to enhance the performance of radar interferometry. This hybrid method leverages the strength of CNNs to automatically identify and mitigate the primary sources of decorrelation, while the Lee filter effectively reduces speckle noise, improving the overall quality of interferograms. We develop a deep learning-based model trained on multi-temporal and multi-frequency SAR datasets, enabling it to predict coherence patterns and enhance low-coherence regions. This hybrid CNN-SAR with Lee filtering significantly reduces noise and phase unwrapping errors, leading to more precise deformation maps. Experimental results demonstrate that our approach improves coherence by up to 30% compared to traditional filtering techniques, making it a robust solution for challenging scenarios such as urban environments, vegetated areas, and rapidly changing landscapes. Our method has potential applications in geohazard monitoring, urban planning, and environmental studies, offering a new avenue for enhancing InSAR data reliability through AI-powered optimization combined with robust filtering techniques.

Keywords: CNN-SAR, Lee Filter, hybrid optimization, coherence, InSAR phase unwrapping, speckle noise reduction

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Authors: D. Díaz Fernández, I. Csízi, K. Pető, G. Nagy

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An outstanding part of the animal products are based on the grasslands, due to the fact that the grassland ecosystems can be found all over the globe. In places where economical and successful crop production cannot be managed, the grassland based animal husbandry can be an efficient way of food production. In addition, these ecosystems have an important role in carbon sequestration, and with their rich flora – and fauna connected to it – in conservation of biodiversity. The protection of nature, and the sustainable agriculture is getting more and more attention in the European Union, but, looking at the consumers’ needs, the production of healthy food cannot be neglected either. Because of these facts, the effects of two specific composts - which are officially authorized in organic farming, in Agri-environment Schemes and Natura 2000 programs – on grass yields and sward compositions were investigated in a field trial. The investigation took place in Hungary, on a natural grassland based on solonetz soil. Three rates of compost (10 t/ha, 20 t/ha, 30 t/ha) were tested on 3 m X 10 m experimental plots. Every treatment had four replications and both type of compost had four-four control plots too, this way 32 experimental plots were included in the investigations. The yield of the pasture was harvested two-times (in May and in September) and before cutting the plots, measurements on botanical compositions were made. Samples for laboratory analysis were also taken. Dry matter yield of pasture showed positive responses to the rates of composts. The increase in dry matter yield was partly due to some positive changes in sward composition. It means that the proportions of grass species with higher yield potential increased in ground cover of the sward without depressing out valuable native species of diverse natural grasslands. The research results indicate that the use of organic compost can be an efficient way to increase grass yields in a sustainable way.

Keywords: compost application, dry matter yield, native grassland, sward composition

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Authors: Marriette Sakah, Samuel Gyamfi, Morkporkpor Delight Sedzro, Christoph Kuhn

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Ghana is experiencing rapid economic development and its cities command an increasingly dominant role as centers of both production and consumption. Cities run on energy and are extremely vulnerable to energy scarcity, energy price escalations and health impacts of very poor air quality. The overriding concern in Ghana and other West African states is bridging the gap between energy demand and supply. Energy efficiency presents a cost-effective solution for supply challenges by enabling more coverage with current power supply levels and reducing the need for investment in additional generation capacity and grid infrastructure. In Ghana, major issues for energy policy formulation in residential applications include lack of disaggregated electrical energy consumption data and lack of thorough understanding with regards to socio-economic influences on energy efficiency investment. This study uses a bottom up approach to estimate baseline electricity end-use as well as the energy consumption of best available technologies to enable estimation of energy-efficiency resource in terms of relative reduction in total energy use for Tema city, Ghana. A ground survey was conducted to assess the probable consumer behavior in response to energy efficiency initiatives to enable estimation of the amount of savings that would occur in response to specific policy interventions with regards to funding and incentives provision targeted at households. Results show that 16% - 54% reduction in annual electricity consumption is reasonably achievable depending on the level of incentives provision. The saved energy could supply 10000 - 34000 additional households if the added households use only best available technology. Political support and consumer awareness are necessary to translate energy efficiency resources into real energy savings.

Keywords: achievable energy savings, energy efficiency, Ghana, household appliances

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Authors: Saleh Nabiyev

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Renewable energy is becoming increasingly important in today's world due to its significant impact on the green economy, ecology, environment, and climate change. Renewable energy sources, such as solar and wind, are clean and sustainable, making them an ideal solution to reduce carbon emissions and mitigate the effects of climate change. The Karabakh region is located in the South Caucasus and covers an area of approximately 11,500 km². The region has a mountainous terrain, which can affect the availability of wind and solar resources. The Karabakh region has significant wind power potential, particularly in its mountainous areas where wind speeds are typically higher. According to a study conducted by the European Commission Joint Research Centre, the average wind speed in the Karabakh region is between 4 and 6 meters per second (m/s) at a height of 50 meters above ground level (AGL). However, wind speeds can be higher in some areas, reaching up to 10 m/s in some mountainous areas. The region also has significant solar power potential, with an average of 2,000 to 2,200 hours of sunshine per year. The region's high altitude and clear skies make it particularly suitable for the development of solar power projects. In this research, the application of satellite images, solar radiation, wind speed and direction, as well as various other materials to determine suitable areas for alternative energy sources, is investigated. The methodology for selecting suitable locations for solar and wind energy consists of four main parts: identification of factors, evaluation of factors, data preparation, and application of suitability analysis. At the end of the research, the territory of the Kalbajar and Lachin districts is suitable for wind energy. The southern plain part of Karabakh is highly evaluated in terms of solar energy potential, especially Jabrayil district. Generally, outcomes taken from this research are essential data for increasing of rational using natural resources, as well as combating climate change.

Keywords: GIS, remote sensing, suitability analysis, solar energy, wind energy

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Authors: Sudip Kumar Kundu, Charu Singh

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As a great physiographic divide, the Himalayas affecting a large system of water and air circulation which helps to determine the climatic condition in the Indian subcontinent to the south and mid-Asian highlands to the north. It creates obstacles by defending chill continental air from north side into India in winter and also defends rain-bearing southwesterly monsoon to give up maximum precipitation in that area in monsoon season. Nowadays extreme weather conditions such as heavy precipitation, cloudburst, flash flood, landslide and extreme avalanches are the regular happening incidents in the region of North Western Himalayan (NWH). The present study has been planned to investigate the suitable model(s) to find out the rainfall pattern over that region. For this investigation, selected models from Coordinated Regional Climate Downscaling Experiment (CORDEX) and Coupled Model Intercomparison Project Phase 5 (CMIP5) has been utilized in a consistent framework for the period of 1976 to 2000 (historical). The ability of these driving models from CORDEX domain and CMIP5 has been examined according to their capability of the spatial distribution as well as time series plot of rainfall over NWH in the rainy season and compared with the ground-based Indian Meteorological Department (IMD) gridded rainfall data set. It is noted from the analysis that the models like MIROC5 and MPI-ESM-LR from the both CORDEX and CMIP5 provide the best spatial distribution of rainfall over NWH region. But the driving models from CORDEX underestimates the daily rainfall amount as compared to CMIP5 driving models as it is unable to capture daily rainfall data properly when it has been plotted for time series (TS) individually for the state of Uttarakhand (UK) and Himachal Pradesh (HP). So finally it can be said that the driving models from CMIP5 are better than CORDEX domain models to investigate the rainfall pattern over NWH region.

Keywords: global warming, rainfall, CMIP5, CORDEX, NWH

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Authors: Daniele Calvi, Loris Franchi, Sabrina Corpino

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Thanks to the latest Mars mission, the planetary exploration has made enormous strides over the past ten years increasing the interest of the scientific community and beyond. These missions aim to fulfill many complex operations which are of paramount importance to mission success. Among these, a special mention goes to the Entry, Descent and Landing (EDL) functions which require a dedicated system to overcome all the obstacles of these critical phases. The general objective of the system is to safely bring the spacecraft from orbital conditions to rest on the planet surface, following the designed mission profile. For this reason, this work aims to develop a simulation tool integrating the re-entry trajectory algorithm in order to support the EDL design during the preliminary phase of the mission. This tool was used on a reference unmanned mission, whose objective is finding bio-evidence and bio-hazards on Martian (sub)surface in order to support the future manned mission. Regarding the concept of operations (CONOPS) of the mission, it concerns the use of Space Penetrator Systems (SPS) that will descend on Mars surface following a ballistic fall and will penetrate the ground after the impact with the surface (around 50 and 300 cm of depth). Each SPS shall contain all the instrumentation required to sample and make the required analyses. Respecting the low-cost and low-mass requirements, as result of the tool, an Entry Descent and Impact (EDI) system based on inflatable structure has been designed. Hence, a solution could be the one chosen by Finnish Meteorological Institute in the Mars Met-Net mission, using an inflatable Thermal Protection System (TPS) called Inflatable Braking Unit (IBU) and an additional inflatable decelerator. Consequently, there are three configurations during the EDI: at altitude of 125 km the IBU is inflated at speed 5.5 km/s; at altitude of 16 km the IBU is jettisoned and an Additional Inflatable Braking Unit (AIBU) is inflated; Lastly at about 13 km, the SPS is ejected from AIBU and it impacts on the Martian surface. Since all parameters are evaluated, it is possible to confirm that the chosen EDI system and strategy verify the requirements of the mission.

Keywords: EDL, Mars, mission, SPS, TPS

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Authors: Thierry Sammour Sawaya, Heikki Deschacht

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In commercial aircraft operations, almost half of the accidents happen during approach or landing phases. Automatic guidance and automatic landings have proven to bring significant safety value added for this challenging landing phase. This is why Airbus and ScioTeq have decided to work together to explore the capability of image-based landing solutions as additional landing aids to further expand the possibility to perform automatic approach and landing to runways where the current guiding systems are either not fitted or not optimum. Current systems for automated landing often depend on radio signals provided by airport ground infrastructure on the airport or satellite coverage. In addition, these radio signals may not always be available with the integrity and performance required for safe automatic landing. Being independent from these radio signals would widen the operations possibilities and increase the number of automated landings. Airbus and ScioTeq are joining their expertise in the field of Computer Vision in the European Program called Clean Sky 2 Large Passenger Aircraft, in which they are leading the IMBALS (IMage BAsed Landing Solutions) project. The ultimate goal of this project is to demonstrate, develop, validate and verify a certifiable automatic landing system guiding an airplane during the approach and landing phases based on an onboard camera system capturing images, enabling automatic landing independent from radio signals and without precision instrument for landing. In the frame of this project, ScioTeq is responsible for the development of the Image Processing Platform (IPP), while Airbus is responsible for defining the functional and system requirements as well as the testing and integration of the developed equipment in a Large Passenger Aircraft representative environment. The aim of this paper will be to describe the system as well as the associated methods and tools developed for validation and verification.

Keywords: aircraft landing system, aircraft safety, autoland, avionic system, computer vision, image processing

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Authors: Ankit Kamboj, Shikha Talwar, Nilesh Powar

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To successfully deliver our products in the market, the employees need to be in a safe environment, especially in an industrial and manufacturing environment. The consequences of delinquency in wearing safety glasses while working in industrial plants could be high risk to employees, hence the need to develop a real-time automatic detection system which detects the persons (violators) not wearing safety glasses. In this study a convolutional neural network (CNN) algorithm called faster region based CNN (Faster RCNN) with rotated bounding box has been used for detecting safety glasses on persons; the algorithm has an advantage of detecting safety glasses with different orientation angles on the persons. The proposed method of rotational bounding boxes with a convolutional neural network first detects a person from the images, and then the method detects whether the person is wearing safety glasses or not. The video data is captured at the entrance of restricted zones of the industrial environment (manufacturing plant), which is further converted into images at 2 frames per second. In the first step, the CNN with pre-trained weights on COCO dataset is used for person detection where the detections are cropped as images. Then the safety goggles are labelled on the cropped images using the image labelling tool called roLabelImg, which is used to annotate the ground truth values of rotated objects more accurately, and the annotations obtained are further modified to depict four coordinates of the rectangular bounding box. Next, the faster RCNN with rotated bounding box is used to detect safety goggles, which is then compared with traditional bounding box faster RCNN in terms of detection accuracy (average precision), which shows the effectiveness of the proposed method for detection of rotatory objects. The deep learning benchmarking is done on a Dell workstation with a 16GB Nvidia GPU.

Keywords: CNN, deep learning, faster RCNN, roLabelImg rotated bounding box, safety goggle detection

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Authors: Radhwane Boudjelthia

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The most recent earthquakes that occurred in the world and particularly in Algeria, have killed thousands of people and severe damage. The example that is etched in our memory is the last earthquake in the regions of Boumerdes and Algiers (Boumerdes earthquake of May 21, 2003). For all the actors involved in the building process, the earthquake is the litmus test for construction. The goal we set ourselves is to contribute to the implementation of a thoughtful approach to the seismic protection of structures. For many engineers, the most conventional approach protection works (buildings and bridges) the effects of earthquakes is to increase rigidity. This approach is not always effective, especially when there is a context that favors the phenomenon of resonance and amplification of seismic forces. Therefore, the field of earthquake engineering has made significant inroads among others catalyzed by the development of computational techniques in computer form and the use of powerful test facilities. This has led to the emergence of several innovative technologies, such as the introduction of special devices insulation between infrastructure and superstructure. This approach, commonly known as "seismic isolation" to absorb the significant efforts without the structure is damaged and thus ensuring the protection of lives and property. In addition, the restraints to the construction by the ground shaking are located mainly at the supports. With these moves, the natural period of construction is increasing, and seismic loads are reduced. Thus, there is an attenuation of the seismic movement. Likewise, the insulation of the base mechanism may be used in combination with earthquake dampers in order to control the deformation of the insulation system and the absolute displacement of the superstructure located above the isolation interface. On the other hand, only can use these earthquake dampers to reduce the oscillation amplitudes and thus reduce seismic loads. The use of damping devices represents an effective solution for the rehabilitation of existing structures. Given all these acceleration reducing means considered passive, much research has been conducted for several years to develop an active control system of the response of buildings to earthquakes.

Keywords: earthquake, building, seismic forces, displacement, resonance, response

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Authors: Gao Youtao, Zhao Tanran, Jin Bingyu, Xu Bo

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Global navigation satellite system(GNSS) can deliver navigation information for spacecraft orbiting on low-Earth orbits and medium Earth orbits. However, the GNSS cannot navigate the spacecraft on high-Earth orbit or deep space probes effectively. With the deep space exploration becoming a hot spot of aerospace, the demand for a deep space satellite navigation system is becoming increasingly prominent. Many researchers discussed the feasibility and performance of a satellite navigation system on periodic orbits around the Earth-Moon libration points which can be called Lagrangian point satellite navigation system. Autonomous orbit determination (AOD) is an important performance for the Lagrangian point satellite navigation system. With this ability, the Lagrangian point satellite navigation system can reduce the dependency on ground stations. AOD also can greatly reduce total system cost and assure mission continuity. As the elliptical restricted three-body problem can describe the Earth-Moon system more accurately than the circular restricted three-body problem, we study the autonomous orbit determination of Lagrangian navigation constellation using only crosslink range based on elliptical restricted three body problem. Extended Kalman filter is used in the autonomous orbit determination. In order to compare the autonomous orbit determination results based on elliptical restricted three-body problem to the results of autonomous orbit determination based on circular restricted three-body problem, we give the autonomous orbit determination position errors of a navigation constellation include four satellites based on the circular restricted three-body problem. The simulation result shows that the Lagrangian navigation constellation can achieve long-term precise autonomous orbit determination using only crosslink range. In addition, the type of the libration point orbit will influence the autonomous orbit determination accuracy.

Keywords: extended Kalman filter, autonomous orbit determination, quasi-periodic orbit, navigation constellation

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Authors: Win Zaw Hein, Khin Sandar Linn, Su Su Yi Mon, Yoshitaka Goto

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The Earth ionosphere is located at the altitude of about 70 km to several 100 km from the ground, and it is composed of ions and electrons called plasma. In the ionosphere, these plasma makes delay in GPS (Global Positioning System) signals and reflect in radio waves. The delay along the signal path from the satellite to the receiver is directly proportional to the total electron content (TEC) of plasma, and this delay is the largest error factor in satellite positioning and navigation. Sounding observation from the top and bottom of the ionosphere was popular to investigate such ionospheric plasma for a long time. Recently, continuous monitoring of the TEC using networks of GNSS (Global Navigation Satellite System) observation stations, which are basically built for land survey, has been conducted in several countries. However, in these stations, multi-frequency support receivers are installed to estimate the effect of plasma delay using their frequency dependence and the cost of multi-frequency support receivers are much higher than single frequency support GPS receiver. In this research, single frequency GPS receiver was used instead of expensive multi-frequency GNSS receivers to measure the ionospheric plasma variation such as vertical TEC distribution. In this measurement, single-frequency support ublox GPS receiver was used to probe ionospheric TEC. The location of observation was assigned at Mandalay Technological University in Myanmar. In the method, the ionospheric TEC distribution is represented by polynomial functions for latitude and longitude, and parameters of the functions are determined by least-squares fitting on pseudorange data obtained at a known location under an assumption of thin layer ionosphere. The validity of the method was evaluated by measurements obtained by the Japanese GNSS observation network called GEONET. The performance of measurement results using single-frequency of GPS receiver was compared with the results by dual-frequency measurement.

Keywords: ionosphere, global positioning system, GPS, ionospheric delay, total electron content, TEC

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Authors: Andrew R. Willis, Kevin Brink, Kathleen Dipple

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This article describes a software package called ROS-georegistration intended for use with the robot operating system (ROS) and the Gazebo 3D simulation environment. ROSgeoregistration provides tools for the simulation, test, and deployment of aerial georegistration algorithms and is available at github.com/uncc-visionlab/rosgeoregistration. A model creation package is provided which downloads multi-spectral images from the Google Earth Engine database and, if necessary, incorporates these images into a single, possibly very large, reference image. Additionally a Gazebo plugin which uses the real-time sensor pose and image formation model to generate simulated imagery using the specified reference image is provided along with related plugins for UAV relevant data. The novelty of this work is threefold: (1) this is the first system to link the massive multi-spectral imaging database of Google’s Earth Engine to the Gazebo simulator, (2) this is the first example of a system that can simulate geospatially and radiometrically accurate imagery from multiple sensor views of the same terrain region, and (3) integration with other UAS tools creates a new holistic UAS simulation environment to support UAS system and subsystem development where real-world testing would generally be prohibitive. Sensed imagery and ground truth registration information is published to client applications which can receive imagery synchronously with telemetry from other payload sensors, e.g., IMU, GPS/GNSS, barometer, and windspeed sensor data. To highlight functionality, we demonstrate ROSgeoregistration for simulating Electro-Optical (EO) and Synthetic Aperture Radar (SAR) image sensors and an example use case for developing and evaluating image-based UAS position feedback, i.e., pose for image-based Guidance Navigation and Control (GNC) applications.

Keywords: EO-to-EO, EO-to-SAR, flight simulation, georegistration, image generation, robot operating system, vision-based navigation

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Authors: Rima Almalla

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The purpose of the research project in Geography is to evaluate the applicability of urban green infrastructure approach in Finnish climate. The key focus will be on the operation and efficiency of green infrastructure on urban stormwater management. Green infrastructure approach refers to the employment of sufficient green covers as a modern and smart environmental solution to improve the quality of urban environments. Green infrastructure provides a wide variety of micro-scale ecosystem services, such as stormwater runoff management, regulation of extreme air temperatures, reduction of energy consumption, plus a variety of social benefits and human health and wellbeing. However, the cold climate of Finland with seasonal ground frost, snow cover and relatively short growing season bring about questions of whether green infrastructure works as efficiently as expected. To tackle this question, green infrastructure solutions will be studied and analyzed with manifold methods: stakeholder perspectives regarding existing and planned GI solutions will be collected by web based questionnaires, semi structured interviews and group discussions, and analyzed in both qualitative and quantitative methods. Targeted empirical field campaigns will be conducted on selected sites. A systematic literature review with global perspective will support the analyses. The findings will be collected, compiled and analyzed using geographic information systems (GIS). The findings of the research will improve our understanding of the functioning of green infrastructure in the Finnish environment in urban stormwater management, as a landscape element for citizens’ wellbeing, and in climate change mitigation and adaptation. The acquired information will be shared with stakeholders in interactive co-design workshops. As green covers have great demand and potential globally, the conclusions will have relevance in other cool climate regions and may support Finnish business in green infrastructure sector.

Keywords: climate change adaptation, climate change, green infrastructure, stormwater

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Authors: Ergün Şakalar, Şeyma Özçirak Ergün, Emrah Yalazi̇, Emine Altinkaya, Cengiz Ataşoğlu

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In recent years, food allergies which cause serious health problems affect to public health around the world. Foodstuffs which contain allergens are either intentionally used as ingredients or are encased as contaminant in food products. The prevalence of clinical allergy to peanuts and nuts is estimated at about 0.4%-1.1% of the adult population, representing the allergy to pistachio the 7% of the cases of tree nut causing allergic reactions. In order to protect public health and enforce the legislation, methods for sensitive analysis of pistachio and peanut contents in food are required. Pea, pistachio and peanut are used together, to reduce the cost in food production such as baklava, snack foods.DNA technology-based methods in food analysis are well-established and well-roundedtools for species differentiation, allergen detection. Especially, the probe-based TaqMan real-time PCR assay can amplify target DNA with efficiency, specificity, and sensitivity.In this study, pistachio, peanut and pea were finely ground and three separate series of triplet mixtures containing 0.1, 1, 10, 100, 1000, 10,000 and 100,000 mg kg-1 of each sample were prepared for each series, to a final weight of 100 g. DNA from reference samples and industrial products was successfully extracted with the GIDAGEN® Multi-Fast DNA Isolation Kit. TaqMan probes were designed for triplex determination of ITS, Ara h 3 and pea lectin genes which are specific regions for identification pistachio, peanut and pea, respectively.The real-time PCR as quantitative detected pistachio, peanut and pea in these mixtures down to the lowest investigated level of 0.1, 0.1 and 1 mg kg-1, respectively. Also, the methods reported here are capable of detecting of as little as 0.001% level of peanut DNA, 0,000001% level of pistachio DNA and 0.000001% level of pea DNA. We accomplish that the quantitative triplex real-time PCR method developed in this study canbe applied to detect pistachio, peanut and peatraces for three allergens at once in commercial food products.

Keywords: allergens, DNA, real-time PCR, TaqMan probe

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Authors: Iacopo Testi, Diego Pajarito, Nicoletta Roberto, Carmen Greco

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Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

Keywords: data science, spatial analysis, composite index, Rome, urban planning, youth economic discomfort index

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Authors: Pranita Shivankar, Arun Suryawanshi, Prabodhachandra Deshmukh, S. V. C. Kameswara Rao

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Many undesirable significant changes in landscapes and the regions in the vicinity of historically important structures occur as impacts due to anthropogenic activities over a period of time. A better understanding of such influences using recently developed satellite remote sensing techniques helps in planning the strategies for minimizing the negative impacts on the existing environment. In 1982, a fossilized hominid skull cap was discovered at a site located along the northern bank of the east-west flowing river Narmada in the village Hathnora. Close to the same site, the presence of Late Acheulian and Middle Palaeolithic tools have been discovered in the immediately overlying pebbly gravel, suggesting that the ‘Narmada skull’ may be from the Middle Pleistocene age. The reviews of recently carried out research studies relevant to hominid remains all over the world from Late Acheulian and Middle Palaeolithic sites suggest succession and contemporaneity of cultures there, enhancing the importance of Hathnora as a rare precious site. In this context, the maximum likelihood classification using digital interpretation techniques was carried out for this study area using the satellite imagery from Landsat ETM+ for the year 2006 and Landsat TM (OLI and TIRS) for the year 2016. The overall accuracy of Land Use Land Cover (LULC) classification of 2016 imagery was around 77.27% based on ground truth data. The significant reduction in the main river course and agricultural activities and increase in the built-up area observed in remote sensing data analysis are undoubtedly the outcome of human encroachments in the vicinity of the eminent heritage site.

Keywords: cultural succession, digital interpretation, Hathnora, Homo Sapiens, Late Acheulian, Middle Palaeolithic

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Authors: Zulkifli Ahmad, Mohd Razlan Azizan, Nasrul Hadi Johari

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This paper presents a study on development and conducting of a wearable sensor system for gait analysis measurement. For validation, the method of plantar surface measurement by force plate was prepared. In general gait analysis, force plate generally represents a studies about barefoot in whole steps and do not allow analysis of repeating movement step in normal walking and running. The measurements that were usually perform do not represent the whole daily plantar pressures in the shoe insole and only obtain the ground reaction force. The force plate measurement is usually limited a few step and it is done indoor and obtaining coupling information from both feet during walking is not easily obtained. Nowadays, in order to measure pressure for a large number of steps and obtain pressure in each insole part, it could be done by placing sensors within an insole. With this method, it will provide a method for determine the plantar pressures while standing, walking or running of a shoe wearing subject. Inserting pressure sensors in the insole will provide specific information and therefore the point of the sensor placement will result in obtaining the critical part under the insole. In the wearable shoe sensor project, the device consists left and right shoe insole with ten FSR. Arduino Mega was used as a micro-controller that read the analog input from FSR. The analog inputs were transmitted via bluetooth data transmission that gains the force data in real time on smartphone. Blueterm software which is an android application was used as an interface to read the FSR reading on the shoe wearing subject. The subject consist of two healthy men with different age and weight doing test while standing, walking (1.5 m/s), jogging (5 m/s) and running (9 m/s) on treadmill. The data obtain will be saved on the android device and for making an analysis and comparison graph.

Keywords: gait analysis, plantar pressure, force plate, earable sensor

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Authors: Hilal Keklicek, Baris Cetin, Yeliz Salci, Ayla Fil, Umut Altinkaynak, Kadriye Armutlu

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Objectives and Goals: Spasticity is a common symptom characterized with a velocity dependent increase in tonic stretch reflexes (muscle tone) in patient with multiple sclerosis (MS). Hypertonic muscles affect the normal plantigrade contact by disturbing accommodation of foot to the ground while walking. It is important to know the differences between healthy and neurologic foot features for management of spasticity related deformities and/or determination of rehabilitation purposes and contents. This study was planned with the aim of investigating the dynamic plantar pressure distribution in individuals with MS and determining the differences between healthy individuals (HI). Methods: Fifty-five individuals with MS (108 foot with spasticity according to Modified Ashworth Scale) and 20 HI (40 foot) were the participants of the study. The dynamic pedobarograph was utilized for evaluation of dynamic loading parameters. Participants were informed to walk at their self-selected speed for seven times to eliminate learning effect. The parameters were divided into 2 categories including; maximum loading pressure (N/cm2) and time of maximum pressure (ms) were collected from heal medial, heal lateral, mid foot, heads of first, second, third, fourth and fifth metatarsal bones. Results: There were differences between the groups in maximum loading pressure of heal medial (p < .001), heal lateral (p < .001), midfoot (p=.041) and 5th metatarsal areas (p=.036). Also, there were differences between the groups the time of maximum pressure of all metatarsal areas, midfoot, heal medial and heal lateral (p < .001) in favor of HI. Conclusions: The study provided basic data about foot pressure distribution in individuals with MS. Results of the study primarily showed that spasticity of lower extremity muscle disrupted the posteromedial foot loading. Secondarily, according to the study result, spasticity lead to inappropriate timing during load transfer from hind foot to forefoot.

Keywords: multiple sclerosis, plantar pressure distribution, gait, norm values

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Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

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Authors: Kassahun Tilahun Dessie

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The purpose of this study was to explore the awareness of teachers and the attitude they have to the curriculum they implement as well as to assess the actual and desired magnitude of teachers' participation in curriculum development process. It also aimed at investigating the factors that affect teachers' level of conception and perception towards the new higher education curriculum. The study was carried out in Debre Birhan University. Teachers, course coordinators, team leaders and presidents were included in the study as research subjects. Teachers were proportionally selected from each department (of the six faculties) based on available sampling technique. Accordingly, a total of 103 teachers were chosen as a subject of the study. In order to collect first hand data from the teachers, a questionnaire with four parts was developed by the researcher. To this end, scales were designed for measuring the extent of teachers' awareness and attitude. Each of the scales encompasses 11 and 17 items respectively. An open ended questionnaire was also attached for the purpose of obtaining elaborated data on the issue. Information was also obtained from interviews with presidents, team leaders and course coordinators. The data obtained were analyzed qualitatively using descriptive statistical tools. The overall results of the analysis revealed that the awareness of teachers on the curriculum was low. The meager participation of teachers in the process of curriculum development and the deficiency of trainings on the concern were major factors. Teachers' perception towards the existence and implementation of the new curriculum was also inclined to the negative, though difficult to generalize. Lack of awareness, administrators poor approach and lack of facilitating appropriate incentives as well as absence of room for evaluating the curriculum etc plays big role in endangering teachers attitude while the up to datedness of the new curriculum, involvement of teachers in the curriculum development process, the wide ranging quality of the new curriculum etc laid a better ground to boost teachers attitude towards the curriculum. This may have implication to the university in that there is a need to facilitate workshops or awareness creation trainings, to have positive and cooperative administrators, and embracing committed teachers to implement the curriculum efficiently.

Keywords: conception, perception, curriculum, higher education, Ethiopia

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Authors: Claudia Huerta, Pepijn Doornenbal, Walaa Elsiddig

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Rising waves of nationalism around the world have led first-world migration receiving countries to exploit the ambiguity of international refugee law and establish asylum application processes that deter applications, allow for bureaucratic deniability, and violate human rights. This case study of Greek asylum application practices argues that the 'pre-application' asylum process in Greece violates the spirit of international law by making it incredibly difficult for potential asylum seekers to apply for asylum, in essence violating the human rights of thousands of asylum seekers. This study’s focus is on the Greek mainland’s asylum 'pre-application' process, which in 2016 began to require those wishing to apply for asylum to do so during extremely restricted hours via a basic Skype line. The average wait to simply begin the registration process to apply for asylum is 81 days, during which time applicants are forced to live illegally in Greece. This study’s methodology in analyzing the 'pre-application' process consists of hours of interviews with asylum seekers, NGOs, and the Asylum Service office on the ground in Athens, as well as an analysis of the Greek Asylum Service historical asylum registration statistics. This study presents three main findings: the delays associated with the Skype system in Greece are the result of system design, as proven by a statistical analysis of Greek asylum registrations, NGOs have been co-opted by the state to perform state functions during the process, and the government’s use of technology is both purposefully lazy and discriminatory. In conclusion, the study argues that such asylum practices are part of a pattern of first-world migration receiving countries policies’ which discourage asylum seekers from applying and fall short of the standards in international law.

Keywords: asylum, European Union, governance, Greece, irregular, migration, policy, refugee, Skype

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Authors: Prem, Norhaya, Vwrene C., Mohammad Harris A., Amarjit, Fazir M.

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Upper limb surgery is a common orthopedic procedure. After surgery, it is necessary to raise the patient's arm to reduce limb swelling and promote recovery. After an injury or surgery, swelling (edema) in the limbs is common. This swelling can be painful, cause stiffness, and affect movement and ability to do daily activities. One of the easiest ways to manage swelling is to elevate the swollen limb. The goal is to elevate the swollen limb slightly above the level of the heart. This helps the extra fluid move back towards the heart for circulation to the rest of the body. Conventional arm sling or pillows are usually placed under the arm to raise it, but in this way the arm cannot be fixed well and easily slide down, without ideal raising effect. Conventional arm sling need experience to tie the sling and this delay in the application process. To reduce the waiting time and cost, modified Norhaya upper limb elevation sling was designed and made readily available. The sling is made from calico fabric, readily available in the ward. Measurements of patients’ arm lengths are obtained, and fabric sizes are cut into the average arm lengths, as well as 1 size above and below. The cut calico fabric is then sewn together with thick sewing threads. Its application is easy and junior most staff or doctor will be able to apply it on patient. The time taken to set up the sling is also reduced. Feedback gathered from ground staff regarding ease of setting up the sling was tremendous and patient also feel comfort in the modified Norhaya sling. The device can freely adjust the raising height of the affected limb and effectively fix the affected limb to reduce its swelling, thus promoting recovery. This device is worthy to be clinically popularized and applied. The Modified Norhaya upper limb elevation sling is the quickest to set up and the delay in elevating the patient’s hand is significantly reduced. Moreover, it is reproducible and there is also significant cost savings.

Keywords: elevate, effective, sling, timely

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Authors: Sarchil H. Qader, Andrew Harfoot, Mathias Kuepie, Sabrina Juran, Attila Lazar, Andrew J. Tatem

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The need for high-quality, reliable, and timely population data, including demographic information, to support the achievement of the sustainable development goals (SDGs) in all countries was recognized by the United Nations' 2030 Agenda for sustainable development. However, many low and middle-income countries lack reliable and recent census data. To achieve reliable and accurate census and survey outputs, up-to-date census enumeration areas and digital national sampling frames are critical. Census enumeration areas (EAs) are the smallest geographic units for collection, disseminating, and analyzing census data and are often used as a national sampling frame to serve various socio-economic surveys. Even for countries that are wealthy and stable, creating and updating EAs is a difficult yet crucial step in preparing for a national census. Such a process is commonly done manually, either by digitizing small geographic units on high-resolution satellite imagery or walking the boundaries of units, both of which are extremely expensive. We have developed a user-friendly tool that could be employed to generate draft EA boundaries automatically. The tool is based on high-resolution gridded population and settlement datasets, GPS household locations, building footprints and uses publicly available natural, man-made and administrative boundaries. Initial outputs were produced in Burkina Faso, Paraguay, Somalia, Togo, Niger, Guinea, and Zimbabwe. The results indicate that the EAs are in line with international standards, including boundaries that are easily identifiable and follow ground features, have no overlaps, are compact and free of pockets and disjoints, and the boundaries are nested within administrative boundaries.

Keywords: enumeration areas, national sampling frame, gridded population data, preEA tool

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Authors: Samuel O. Akande

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The human-induced climate change is likely to have severe consequences on forest ecosystems in Nigeria. Recent discussions and emphasis on issues concerning the environment justify the need for this research which examined deforestation monitoring in Oban Forest, Nigeria using Remote Sensing techniques. The Landsat images from TM (1986), ETM+ (2001) and OLI (2015) sensors were obtained from Landsat online archive and processed using Erdas Imagine 2014 and ArcGIS 10.3 to obtain the land use/land cover and Normalized Differential Vegetative Index (NDVI) values. Ground control points of deforested areas were collected for validation. It was observed that the forest cover decreased in area by about 689.14 km² between 1986 and 2015. The NDVI was used to determine the vegetation health of the forest and its implications on agricultural sustainability. The result showed that the total percentage of the healthy forest cover has reduced to about 45.9% from 1986 to 2015. The results obtained from analysed questionnaires shown that there was a positive correlation between the causes and effects of deforestation in the study area. The coefficient of determination value was calculated as R² ≥ 0.7, to ascertain the level of anthropogenic activities, such as fuelwood harvesting, intensive farming, and logging, urbanization, and engineering construction activities, responsible for deforestation in the study area. Similarly, temperature and rainfall data were obtained from Nigerian Meteorological Agency (NIMET) for the period of 1986 to 2015 in the study area. It was observed that there was a significant increase in temperature while rainfall decreased over the study area. Responses from the administered questionnaires also showed that futile destruction of forest ecosystem in Oban forest could be reduced to its barest minimum if fuelwood harvesting is disallowed. Thus, the projected impacts of climate change on Nigeria’s forest ecosystems and environmental stability is better imagined than experienced.

Keywords: deforestation, ecosystems, normalized differential vegetative index, sustainability

Procedia PDF Downloads 193

Authors: Abhisek Dash

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This study had three neural networks, one for number segmentation, one for number detection and one for number recognition all of which are coupled to one another. All networks were trained on the MNIST dataset and were convolutional. It was assumed that the images had lighter background and darker foreground. The segmentation network took 28x28 images as input and had sixteen outputs. Segmentation training starts when a dark pixel is encountered. Taking a window(7x7) over that pixel as focus, the eight neighborhood of the focus was checked for further dark pixels. The segmentation network was then trained to move in those directions which had dark pixels. To this end the segmentation network had 16 outputs. They were arranged as “go east”, ”don’t go east ”, “go south east”, “don’t go south east”, “go south”, “don’t go south” and so on w.r.t focus window. The focus window was resized into a 28x28 image and the network was trained to consider those neighborhoods which had dark pixels. The neighborhoods which had dark pixels were pushed into a queue in a particular order. The neighborhoods were then popped one at a time stitched to the existing partial image of the number one at a time and trained on which neighborhoods to consider when the new partial image was presented. The above process was repeated until the image was fully covered by the 7x7 neighborhoods and there were no more uncovered black pixels. During testing the network scans and looks for the first dark pixel. From here on the network predicts which neighborhoods to consider and segments the image. After this step the group of neighborhoods are passed into the detection network. The detection network took 28x28 images as input and had two outputs denoting whether a number was detected or not. Since the ground truth of the bounds of a number was known during training the detection network outputted in favor of number not found until the bounds were not met and vice versa. The recognition network was a standard CNN that also took 28x28 images and had 10 outputs for recognition of numbers from 0 to 9. This network was activated only when the detection network votes in favor of number detected. The above methodology could segment connected and overlapping numbers. Additionally the recognition unit was only invoked when a number was detected which minimized false positives. It also eliminated the need for rules of thumb as segmentation is learned. The strategy can also be extended to other characters as well.

Keywords: convolutional neural networks, OCR, text detection, text segmentation

Procedia PDF Downloads 163