Search results for: aerial mapping

Authors: Anne C. Okwedadi, Samson Ng’ambi, Ian Jefferson

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Collapsible soils go through radical rearrangement of their particles when triggered by water, stress or/and vibration, causing loss of volume. This loss of volume in soil as seen in foundation failures has caused millions of dollars’ worth of damages to public facilities and infrastructure and so has an adverse effect on the society and people. Despite these consequences and the several studies that are available, more research is still required in the study of soil collapsibility. Discerning the pedogenesis (formation) of soils and investigating the combined effects of the different geological soil properties is key to elucidating and quantifying soils collapsibility. This study presents a novel laboratory testing regime that would be undertaken on soil samples where the effects of soil type, compactive variables (moisture content, density, void ratio, degree of saturation) and loading are analyzed. It is anticipated that results obtained would be useful in mapping the trend of the combined effect thus the basis for evaluating soil collapsibility or collapse potentials encountered in construction with volume loss problems attributed to collapse.

Keywords: collapsible soil, geomorphological process, soil collapsibility properties, soil test

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Authors: P. R. Rahul, A. Kannan

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Ultrasound-aided adsorption of phenol by Granular Activated Carbon (GAC) was investigated at different frequencies ranging from 35 kHz, 58 kHz, and 192 kHz. Other factors influencing adsorption such as Adsorbent dosage (g/L), the initial concentration of the phenol solution (ppm) and RPM was also considered along with the frequency variable. However, this study involved calorimetric measurements which helped is determining the effect of frequency on the % removal of phenol from the power dissipated to the system was normalized. It was found that low frequency (35 kHz) cavitation effects had a profound influence on the % removal of phenol per unit power. This study also had cavitation mapping of the ultrasonic baths, and it showed that the effect of cavitation on the adsorption system is irrespective of the position of the vessel. Hence, the vessel was placed at the center of the bath. In this study, novel temperature control and monitoring system to make sure that the system is under proper condition while operations. From the BET studies, it was found that there was only 5% increase in the surface area and hence it was concluded that ultrasound doesn’t profoundly alter the equilibrium value of the adsorption system. DOE studies indicated that adsorbent dosage has a higher influence on the % removal in comparison with other factors.

Keywords: ultrasound, adsorption, granulated activated carbon, phenol

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Authors: Abdur Rahim, Lauro Tatsuo Kubota, Yoshitaka Gushikem

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Carbon ceramic mesoporous SiO2/50wt%C (SBET= 170 m2g-1), where C is graphite, was prepared by the sol gel method. Scanning electron microscopy images and the respective element mapping showed that, within the magnification used, no phase segregation was detectable. It presented the electric conductivities of 0.49 S cm-1. This material was used to support cobalt phthalocyanine, prepared in situ, to assure a homogeneous dispersion of the electro active complex in the pores of the matrix. The surface density of cobalt phthalocyanine, on the matrix surfaces was 0.015 mol cm-2. Pressed disk, made with SiO2/50wt%C/CoPc, was used to fabricate an electrode and tested as sensors for nitrite determination by electro chemical technique. A linear response range between 0.039 and 0.42 mmol l−1,and correlation coefficient r=0.9996 was obtained. The electrode was chemically very stable and presented very high sensitivity for this analyte, with a limit of detection, LOD = 1.087 x 10-6 mol L-1.

Keywords: SiO2/C/CoPc, sol-gel method, electrochemical sensor, nitrite oxidation, carbon ceramic material, cobalt phthalocyanine

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Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: computed tomography, enhancement techniques, increasing contrast, PSNR and MSE

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Authors: Han Run-Sheng, Li Wen-Yao, Wang Feng, Liu Fei, Qiu Wen-Long, Lei Li

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Accurately positioning detection of concealed deposits or ore-bodies is one of the difficult problems in mineral exploration field. Theory calculation and exploration practices for tunnel gravity indicate that 3D high-precision Tunnel Gravity Exploration Method (TGEM) can find concealed high-density three-dimensional ore-bodies in the depth. The ore-finding breakthroughs at the depth of the Zhaotong Maoping carbonate-hosted Zn–Pb–(Ag–Ge) deposit in Northeastern Yunnan have proved that the exploration method in combination with MEAHFZ method is effective to detect concealed high-density ore-bodies. TGEM may overcome anomalous ambiguity of other geophysical methods for 3D positioning of concealed ore-bodies.

Keywords: 3D tunnel gravity exploration method, concealed high-density Ore-bodies, Zn–Pb–(Ag–Ge) deposit, Zaotong mapping, Northeastern Yunnan

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Authors: Juan David Sepulveda

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This article reflects the current stage of progress in the project “Determining technological trends in energy generation”. At first it was oriented towards finding out those trends by employing such tools as the scientometrics community had proved and accepted as effective for getting reliable results. Because a documented methodological guide for this purpose could not be found, the decision was made to reorient the scope and aim of this project, changing the degree of interest in pursuing the objectives. Therefore it was decided to propose and implement a novel guide from the elements and techniques found in the available literature. This article begins by explaining the elements and considerations taken into account when implementing and applying this methodology, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.

Keywords: energy, technology mapping, patents, univariate analysis

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Authors: K. M. G. T. R. Waidyarathna, S. M. Vidanagamachchi

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Public Health System exists in Sri Lanka has a satisfactory complete information flow when compared to other systems in developing countries. The availability of a good health information system contributed immensely to achieve health indices that are in line with the developed countries like US and UK. The health information flow at the moment is completely paper based. In Sri Lanka, the fields like banking, accounting and engineering have incorporated information and communication technology to the same extent that can be observed in any other country. The field of medicine has behind those fields throughout the world mainly due to its complexity, issues like privacy, confidentially and lack of people with knowledge in both fields of Information Technology (IT) and Medicine. Sri Lanka’s situation is much worse and the gap is rapidly increasing with huge IT initiatives by private-public partnerships in all other countries. The major goal of the framework is to support minimizing the spreading diseases. To achieve that a web based framework should be implemented for this application domain with web mapping. The aim of this GIS based public health system is a secure, flexible, easy to maintain environment for creating and maintaining public health records and easy to interact with relevant parties.

Keywords: DHIS2, GIS, public health, Sri Lanka

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Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

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Authors: D. S. Palimkar

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Random fixed point theory has received much attention in recent years, and it is needed for the study of various classes of random equations. The study of random fixed point theorems was initiated by the Prague school of probabilistic in the 1950s. The existence and uniqueness of fixed points for the self-maps of a metric space by altering distances between the points with the use of a control function is an interesting aspect in the classical fixed point theory. In a new category of fixed point problems for a single self-map with the help of a control function that alters the distance between two points in a metric space which they called an altering distance function. In this paper, we prove the results of existence of random common fixed point and its uniqueness for a pair of random mappings under weakly contractive condition for generalizing alter distance function in polish spaces using Random Common Fixed Point Theorem for Generalized Weakly Contractions.

Keywords: Polish space, random common fixed point theorem, weakly contractive mapping, altering function

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Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Mads Dyrmann, Robert Poulsen

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For the past three years, the Danish project, RoboWeedSupport, has sought to bridge the gap between the potential herbicide savings using a decision support system and the required weed inspections. In order to automate the weed inspections it is desired to generate a map of the weed species present within the field, to generate the map images must be captured with samples covering the field. This paper investigates the economical cost of performing this data collection based on a camera system mounted on a all-terain vehicle (ATV) able to drive and collect data at up to 50 km/h while still maintaining a image quality sufficient for identifying newly emerged grass weeds. The economical estimates are based on approximately 100 hectares recorded at three different locations in Denmark. With an average image density of 99 images per hectare the ATV had an capacity of 28 ha per hour, which is estimated to cost 6.6 EUR/ha. Alternatively relying on a boom solution for an existing tracktor it was estimated that a cost of 2.4 EUR/ha is obtainable under equal conditions.

Keywords: weed mapping, integrated weed management, weed recognition, image acquisition

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Authors: Nassim Belkacem, Amina Azzam, Dalila Haouchine, Kahina Bennacer, Samira Soufit

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Objective: To evaluate the antioxidant activity of the methanolic extract along with the antimicrobial activity of the essential oil of the aerial parts of Rosmarinus officinalis L. collected in the region of Bejaia (northern center of Algeria). Materials and methods: The polyphenols and flavonoids contents of the methanolic extract were measured. The antioxidant activity was evaluated using two methods: the ABTS method and DPPH assay. The antimicrobial activity was studied by the agar diffusion method against five bacterial strains (Three Gram positive strains and two Gram negative strains) and one fungus. Results: The total polyphenol and flavonoid content was about 43.8 mg gallic acid equivalent per gram (GA Eq/g) and 7.04 mg quercetin equivalent per gram (Q Eq/g), respectively. In the ABTS assay, the rosemary extract has shown an inhibition of 98.02% at the concentration of 500ug/ml with a half maximal inhibitory concentration value (IC50) of 194.92ug/ml. The results of DPPH assay have shown that the rosemary extract has an inhibition of 94.67 % with an IC50 value of 17.87ug/ml, which is lower than that of Butylhydroxyanisol (BHA) about 6.03ug/ml and ascorbic acid about 1.24μg/ml. The yield in essential oil of rosemary obtained by hydrodistillation was 1.42%. Based on the determination of the diameter of inhibition, different antimicrobial activity of the essential oil was revealed against the six tested microbes. Escherichia coli from the University Hospital (UH), Streptococcus aureus (UH) and Pseudomonas aeruginosa ATCC have a minimum inhibitory concentration value (MIC) of 62.5µl/ml. However, Bacillus sp (UH) and Staphylococcus aureus ATCC have an MIC value of 125μl/ml. The inhibition zone against Candida sp was about 24 mm. The aromatograms showed that the essential oil of rosemary exercises an antifungal activity more important than the antibacterial one.

Keywords: Rosmarinus officinalis L., maceration, essential oil, antioxidant, antimicrobial activity

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Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

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This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

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Authors: Gyumin Hwang, Jihong Lee

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This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1 m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: chirp spread spectrum, indoor localization, pattern-matching, time of arrival, multi-path, mahalanobis distance, reception rate, simultaneous localization and mapping, laser range finder

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Authors: Ya-Li Tsai

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Nitrogen is a vital element crucial for crop growth, significantly influencing crop yield. In rice cultivation, farmers often apply substantial nitrogen fertilizer to maximize yields. However, excessive nitrogen application increases the risk of lodging and pest infestation, leading to yield losses. Additionally, conventional flooded irrigation methods consume significant water resources, necessitating precise agricultural and intelligent water management systems. In this study, it leveraged physiological data and field images captured by unmanned aerial vehicles, considering fertilizer treatment and irrigation as key factors. Statistical models incorporating rice physiological data, yield, and vegetation indices from image data were developed. Missing physiological data were addressed using multiple imputation and regression methods, and regression models were established using principal component analysis and stepwise regression. Target nitrogen accumulation at key growth stages was identified to optimize fertilizer application, with the difference between actual and target nitrogen accumulation guiding recommendations for ear dressing dosage. Field experiments conducted in 2022 validated the recommended ear dressing dosage, demonstrating no significant difference in final yield compared to traditional fertilizer levels under alternate wetting and drying irrigation. These findings highlight the efficacy of applying recommended dosages based on fertilizer decision models, offering the potential for reduced fertilizer use while maintaining yield in rice cultivation.

Keywords: intelligent fertilizer management, nitrogen top and ear dressing fertilizer, rice, yield optimization

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Authors: Ozlem Bahadir Acikara, Mert Ilhan, Ekin Kurtul, Karel Smejkal, Esra Kupeli Akkol

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Present study is aimed to investigate in vitro inhibitory effects of the extracts prepared from the aerial parts of Podospermum canum (Asteraceae) on hyaluronidase, collagenase, and elastase enzymes using a bioassay-guided fractionation. Inhibitory effects of the extract, sub-extracts, fractions obtained by column chromatography, and isolated compounds on collagenase, elastase, and hyaluronidase were performed by using in vitro enzyme inhibitory assays based on spectrophotometric evaluation. The ethyl acetate and remaining water extracts prepared from the plant displayed significant inhibitory activities on collagenase and elastase, while petroleum ether and chloroform extracts did not show any inhibitory activity. Eleven known compounds: arbutin, 6'-O-caffeoylarbutin, cichoriin, 3,5-dicaffeoylquinic acid methyl ester, apigenin-7-O-β-glucoside, luteolin-7-O-β-glucoside, apigenin-7-O-β-rutinoside, isoorientin, orientin, vitexin, procatechuic acid, and compound 4-hydroxy-benzoic acid 4-(6-O-α-rhamnopyranosyl-β-glucopyranosyl) benzyl ester have been obtained from ethyl acetate sub-extract of the plant through bioassay-guided fractionation and isolation. Results of the present study have revealed that among the isolated compounds, apigenin-7-O-β-glucoside, luteolin-7-O-β-glucoside, apigenin-7-O-β-rutinoside and isoorientin showed potent enzyme inhibitory activities. However, methanolic extract of P. canum displayed a greater inhibitory activity than fractions and isolated compounds both on collagenase and elastase.

Keywords: Asteraceae, collagenase, elastase, hyaluronidase, Podospermum canum

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Authors: D. Madhushanka, Y. Liu, H. C. Fernando

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Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

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Authors: S. Bayona, J. Nunez, D. Paez, C. Diaz

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The application of Lean manufacturing tools continues to be an effective solution for increasing productivity, reducing costs and eliminating waste in the manufacture of goods and services. This article analyzes the production process of a hot asphalt manufacturing company from an administrative and technical perspective. Three main phases were analyzed, the first phase was related to the determination of the risk priority number of the main operations in asphalt mix production process by an FMEA (Failure Mode Effects Analysis), in the second phase the Value Stream Mapping (VSM) of the production line was performed and in the third phase a SWOT (Strengths, Weaknesses Opportunities, Threats) matrix was constructed. Among the most valued failure modes were the lack training of workers in occupational safety and health issues, the lack of signaling and classification of granulated material, and the overweight of vehicles loaded. The analysis of the results in the three phases agree on the importance of training operational workers, improve communication with external actors in order to minimize delays in material orders and strengthen control suppliers.

Keywords: asphalt, lean manufacturing, productivity, process

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Authors: D. Henninger, A. Zopey, T. Ihde, C. Mehring

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The dynamic performance of a 4-way solenoid operated hydraulic spool valve has been analyzed by means of a one-dimensional modeling approach capturing flow, magnetic and fluid forces, valve inertia forces, fluid compressibility, and damping. Increased model accuracy was achieved by analyzing the detailed three-dimensional electromagnetic behavior of the solenoids and flow behavior through the spool valve body for a set of relevant operating conditions, thereby allowing the accurate mapping of flow and magnetic forces on the moving valve body, in lieu of representing the respective forces by lower-order models or by means of simplistic textbook correlations. The resulting high-fidelity one-dimensional model provided the basis for specific and timely design modification eliminating experimentally observed valve oscillations.

Keywords: dynamic performance model, high-fidelity model, 1D-3D decoupled analysis, solenoid-operated hydraulic servo valve, CFD and electromagnetic FEA

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Authors: Salma Kaouthar Letaief

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This article investigates the experience of diaspora in the writings of Algerian diasporic writers, namely: Leila Sebbar’s Silence on the Shores (2000), Keltoum Staali’ December’s Mimosa (2012). The study discusses the collective trauma of violence in Algeria and overseas. The experience of displacement of the characters to an alien territory compel their journey with issues related to nostalgia, identity crisis, alienation, racism, and in-betweeness. The focus in this research is, thus, on Algerian immigrants’ experience in the host country and their psychological conflicts. The theories Multiculturalism and Psychoanalysis are used to analyse the novels in this paper. While Multiculturalism examines how characters negotiate and navigate their identities in multicultural settings, Psychoanalysis enables the analysis of how characters in diasporic novels grapple with issues of identity, belonging, and self-discovery. Hence, interweaving multiculturalism and psychoanalysis provides an interdisciplinary framework that addresses both the socio-cultural and psychological aspects of the diasporic experience. Accordingly, this paper is an attempt to examine the diasporic experience and cultural dialectics.

Keywords: diaspora, algerian diasporic writers, trauma, algeria, displacement, identity crisis, cultural dialects

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Authors: Adam J. Bowen

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Abstract— Should robots have rights or legal protections. Often debates concerning whether robots and AI should be afforded rights focus on conditions of personhood and the possibility of future advanced forms of AI satisfying particular intrinsic cognitive and moral attributes of rights-holding persons. Such discussions raise compelling questions about machine consciousness, autonomy, and value alignment with human interests. Although these are important theoretical concerns, especially from a future design perspective, they provide limited guidance for addressing the moral and legal standing of current and near-term AI that operate well below the cognitive and moral agency of human persons. Robots and AI are already being pressed into service in a wide range of roles, especially in healthcare and biomedical contexts. The design and large-scale implementation of robots in the context of core societal institutions like healthcare systems continues to rapidly develop. For example, we bring them into our homes, hospitals, and other care facilities to assist in care for the sick, disabled, elderly, children, or otherwise vulnerable persons. We enlist surgical robotic systems in precision tasks, albeit still human-in-the-loop technology controlled by surgeons. We also entrust them with social roles involving companionship and even assisting in intimate caregiving tasks (e.g., bathing, feeding, turning, medicine administration, monitoring, transporting). There have been advances to enable severely disabled persons to use robots to feed themselves or pilot robot avatars to work in service industries. As the applications for near-term AI increase and the roles of robots in restructuring our biomedical practices expand, we face pressing questions about the normative implications of human-robot interactions and collaborations in our collective worldmaking, as well as the moral and legal status of robots. This paper argues that robots operating in public and private spaces be afforded some protections as either moral patients or legal agents to establish prohibitions on robot abuse, misuse, and mistreatment. We already implement robots and embed them in our practices and institutions, which generates a host of human-to-machine and machine-to-machine relationships. As we interact with machines, whether in service contexts, medical assistance, or home health companions, these robots are first encountered in relationship to us and our respective roles in the encounter (e.g., surgeon, physical or occupational therapist, recipient of care, patient’s family, healthcare professional, stakeholder). This proposal aims to outline a framework for establishing limiting factors and determining the extent of moral or legal protections for robots. In doing so, it advocates for a relational approach that emphasizes the priority of mapping the complex contextually sensitive roles played and the relations in which humans and robots stand to guide policy determinations by relevant institutions and authorities. The relational approach must also be technically informed by the intended uses of the biomedical technologies in question, Design History Files, extensive risk assessments and hazard analyses, as well as use case social impact assessments.

Keywords: biomedical robots, robot ethics, robot laws, human-robot interaction

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Authors: A. Hol

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21^st century brought waves of business and industry eTransformations. The impact of change is also being seen in education. To identify the extent of this, scenario analysis methodology was utilised with the aim to assess business transformations across industry sectors ranging from craftsmanship, medicine, finance and manufacture to innovations and adoptions of new technologies and business models. Firstly, scenarios were drafted based on the current eTransformation models and its dimensions. Following this, eTransformation framework was utilised with the aim to derive the key eTransformation parameters, the essential characteristics that have enabled eTransformations across the sectors. Following this, identified key parameters were mapped to the transforming domain-education. The mapping assisted in deriving a cognitive eTransformation framework for education sector. The framework highlights the importance of context and the notion that education today needs not only to deliver content to students but it also needs to be able to meet the dynamically changing demands of specific student and industry groups. Furthermore, it pinpoints that for such processes to be supported, specific technology is required, so that instant, on demand and periodic feedback as well as flexible, dynamically expanding study content can be sought and received via multiple education mediums.

Keywords: education sector, business transformation, eTransformation model, cognitive model, cognitive systems, eTransformation

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Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: Yaner Yan, Ning Li, Yajun Qiao, Shuqing An

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Although most studies have focused on assessing and mapping terrestrial ecosystem services, there is still a knowledge gap on coastal ecosystem services and an urgent need to assess them. Lau (2013) clearly defined five types of costal ecosystem services: carbon sequestration, shoreline protection, fish nursery, biodiversity, and water quality. While high-resolution remote sensing can provide the more direct, spatially estimates of biophysical parameters, such as species distribution relating to biodiversity service, and Fluorescence information derived from remote sensing direct relate to photosynthesis, availing in estimation of carbon sequestration and the response to environmental changes in coastal wetland. Here, we review the capabilities of high-resolution and fluorescence remote sesing for describing biodiversity, vegetation condition, ecological processes and highlight how these prodicts may contribute to costal ecosystem service assessment. In so doing, we anticipate rapid progress to combine the high-resolution and fluorescence remote sesing to estimate the spatial pattern of costal ecosystem services.

Keywords: ecosystem services, high resolution, remote sensing, chlorophyll fluorescence

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Authors: William Huang

Abstract:

Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

Procedia PDF Downloads 152

Authors: Ronald Collins, Jonathon Coleman, Joel Dasari, George Holt, Carl Metelko, Matthew Murdoch, Alexander Morgan, Yan-Jie Schnellbach, Robert Mills, Gareth Edwards, Alexander Roberts

Abstract:

At the Wylfa Magnox Power Plant between 2014–2016, the VIDARR prototype anti-neutrino detector was deployed. It is comprised of extruded plastic scintillating bars measuring 4 cm × 1 cm × 152 cm and utilised wavelength shifting fibres (WLS) and multi-pixel photon counters (MPPCs) to detect and quantify radiation. During deployment, it took cosmic muon data in accidental coincidence with the anti-neutrino measurements with the power plant site buildings obscuring the muon sky. Cosmic muons have a significantly higher probability of being attenuated and/or absorbed by denser objects, and so one-sided cosmic muon tomography was utilised to image the reactor site buildings. In order to achieve clear building outlines, a control data set was taken at the University of Liverpool from 2016 – 2018, which had minimal occlusion of the cosmic muon flux by dense objects. By taking the ratio of these two data sets and using GEANT4 simulations, it is possible to perform a one-sided cosmic muon tomography analysis. This analysis can be used to discern specific buildings, building heights, and features at the Wylfa reactor site, including the reactor core/reactor core shielding using ∼ 3 hours worth of cosmic-ray detector live time. This result demonstrates the feasibility of using cosmic muon analysis to determine a segmented detector’s location with respect to surrounding buildings, assisted by aerial photography or satellite imagery.

Keywords: anti-neutrino, GEANT4, muon, tomography, occlusion

Procedia PDF Downloads 186

Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

Abstract:

There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

Procedia PDF Downloads 498

Authors: Lynndee Kemmet

Abstract:

The U.S. military plays an increasing role in supporting political stability efforts, and this includes efforts to prevent the food insecurity that can trigger political and social instability. This paper presents a model that assists military commanders in identifying variables that impact food production and distribution in their areas of operation (AO), in identifying connections between variables and in assessing the impacts of those variables on food production and distribution. Through use of the model, military units can better target their data collection efforts and can categorize and analyze data within the data categorization framework most widely-used by military forces—PMESII-PT (Political, Military, Economic, Infrastructure, Information, Physical Environment and Time). The model provides flexibility of analysis in that commanders can target analysis to be highly focused on a specific PMESII-PT domain or variable or conduct analysis across multiple PMESII-PT domains. The model is also designed to assist commanders in mapping food systems in their AOs and then identifying components of those systems that must be strengthened or protected.

Keywords: food security, food system model, political stability, US Military

Procedia PDF Downloads 195

Authors: Carlos Gonzalez, Neil Slatcher, Marcus Properzi, Kan Seah

Abstract:

In many underground mining operations, shotcrete is used for permanent rock support. Shotcrete thickness is a critical measure of the success of this process. 3D Laser Mapping, in conjunction with Jetcrete, has developed a 3D laser scanning system specifically for measuring the thickness of shotcrete. The system is mounted on the shotcrete spraying machine and measures the rock faces before and after spraying. The calculated difference between the two 3D surface models is measured as the thickness of the sprayed concrete. Typical work patterns for the shotcrete process required a rapid and automatic system. The scanning takes place immediately before and after the application of the shotcrete so no convergence takes place in the interval between scans. Automatic alignment of scans without targets was implemented which allows for the possibility of movement of the spraying machine between scans. Case studies are presented where accuracy tests are undertaken and automatic audit reports are calculated. The use of 3D imaging data for the calculation of shotcrete thickness is an important tool for geotechnical engineers and contract managers, and this could become the new state-of-the-art methodology for the mining industry.

Keywords: 3D imaging, shotcrete, surface model, tunnel stability

Procedia PDF Downloads 290