Search results for: high resolution satellite image

Authors: Rajendar Kandan, Mohammad Zakaria Alli, Hong Ong

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Cloud computing is a business model which provides an easier management of computing resources. Cloud users can request virtual machine and install additional softwares and configure them if needed. However, user can also request virtual appliance which provides a better solution to deploy application in much faster time, as it is ready-built image of operating system with necessary softwares installed and configured. Large numbers of virtual appliances are available in different image format. User can download available appliances from public marketplace and start using it. However, information published about the virtual appliance differs from each providers leading to the difficulty in choosing required virtual appliance as it is composed of specific OS with standard software version. However, even if user choses the appliance from respective providers, user doesn’t have any flexibility to choose their own set of softwares with required OS and application. In this paper, we propose a referenced architecture for dynamically customizing virtual appliance and provision them in an easier manner. We also add our experience in integrating our proposed architecture with public marketplace and Mi-Cloud, a cloud management software.

Keywords: cloud computing, marketplace, virtualization, virtual appliance

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Authors: Sisaye Tamrat Ayalew

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In Ethiopia, the relationships between different communities have been characterized by mistrust, prejudice, and conflict, resulting in mass killings, displacement, and human rights violations. These relationships are mainly based on ethnic, religious, and linguistic lines, leading to a polarized society. The aim of this study is to appraise the nature of two major community relationships, namely the I-Thou relationship, characterized by genuine dialogue and mutual understanding, and the I-It relationship, characterized by a monologue and mutual suspicion. The study also aims to analyze how these two types of relationships contribute to either resolving or aggravating conflicts and building or deteriorating peace in Ethiopia. The study adopts a qualitative approach, specifically hermeneutics, to explore the nature of the I-Thou and I-It relationships in the Ethiopian context. It also examines how political elites shape these relationships within the community. The study finds that the dominant relationship in Ethiopian society is the I-It relationship, which is manifested as "com-animation." This relationship is characterized by mutual mistrust, prejudice, hostility, and misunderstanding. As a result, conflicts have arisen, leading to violence, displacement, and human rights violations. The study concludes that there is a need to shift from the I-It (com-animation) relationship to the I-Thou (communication) relationship in Ethiopian society. This shift would involve rethinking and readjusting societal relationships, especially among political elites, to foster genuine dialogue, mutual understanding, and lasting peace. It is imperative to overcome mutual mistrust, prejudice, and misunderstanding in order to resolve conflicts and build a harmonious society in Ethiopia. The study's findings and recommendations contribute to raising awareness among both Ethiopians and the international community on the potential for conflict resolution and peacebuilding through a shift in community relationships.

Keywords: dialogue, I-Thou relationship, I-It relationship, conflict resolution, building peace

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Authors: Przemysław Adamczyk, Mirosław Wyczesany, Aleksandra Domagalik, Artur Daren, Kamil Cepuch, Piotr Błądziński, Tadeusz Marek, Andrzej Cechnicki

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The present study aimed at evaluation of neural correlates of humor comprehension impairments observed in schizophrenia. To investigate the nature of this deficit in schizophrenia and to localize cortical areas involved in humor processing we used functional magnetic resonance imaging (fMRI). The study included chronic schizophrenia outpatients (SCH; n=20), and sex, age and education level matched healthy controls (n=20). The task consisted of 60 stories (setup) of which 20 had funny, 20 nonsensical and 20 neutral (not funny) punchlines. After the punchlines were presented, the participants were asked to indicate whether the story was comprehensible (yes/no) and how funny it was (1-9 Likert-type scale). fMRI was performed on a 3T scanner (Magnetom Skyra, Siemens) using 32-channel head coil. Three contrasts in accordance with the three stages of humor processing were analyzed in both groups: abstract vs neutral stories - incongruity detection; funny vs abstract - incongruity resolution; funny vs neutral - elaboration. Additionally, parametric modulation analysis was performed using both subjective ratings separately in order to further differentiate the areas involved in incongruity resolution processing. Statistical analysis for behavioral data used U Mann-Whitney test and Bonferroni’s correction, fMRI data analysis utilized whole-brain voxel-wise t-tests with 10-voxel extent threshold and with Family Wise Error (FWE) correction at alpha = 0.05, or uncorrected at alpha = 0.001. Between group comparisons revealed that the SCH subjects had attenuated activation in: the right superior temporal gyrus in case of irresolvable incongruity processing of nonsensical puns (nonsensical > neutral); the left medial frontal gyrus in case of incongruity resolution processing of funny puns (funny > nonsensical) and the interhemispheric ACC in case of elaboration of funny puns (funny > neutral). Additionally, the SCH group revealed weaker activation during funniness ratings in the left ventro-medial prefrontal cortex, the medial frontal gyrus, the angular and the supramarginal gyrus, and the right temporal pole. In comprehension ratings the SCH group showed suppressed activity in the left superior and medial frontal gyri. Interestingly, these differences were accompanied by protraction of time in both types of rating responses in the SCH group, a lower level of comprehension for funny punchlines and a higher funniness for absurd punchlines. Presented results indicate that, in comparison to healthy controls, schizophrenia is characterized by difficulties in humor processing revealed by longer reaction times, impairments of understanding jokes and finding nonsensical punchlines more funny. This is accompanied by attenuated brain activations, especially in the left fronto-parietal and the right temporal cortices. Disturbances of the humor processing seem to be impaired at the all three stages of the humor comprehension process, from incongruity detection, through its resolution to elaboration. The neural correlates revealed diminished neural activity of the schizophrenia brain, as compared with the control group. The study was supported by the National Science Centre, Poland (grant no 2014/13/B/HS6/03091).

Keywords: communication skills, functional magnetic resonance imaging, humor, schizophrenia

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Authors: Popoola I. Olayinka, Alamu E. Oladeji, B. Maziya-Dixon

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Cassava, an indigenous crop grown locally by subsistence farmers in Nigeria has potential to bring economic benefits to the country. Consumption of bread and other confectionaries has been on the rise due to lifestyle changes of Nigerian consumers. However, wheat, being the major ingredient for bread and confectionery production does not thrive well under Nigerian climate hence the huge spending on wheat importation. To reduce spending on wheat importation, the Federal Government of Nigeria intends passing into law mandatory inclusion of 20% high-quality cassava flour (HQCF) in wheat flour. While the proposed policy may reduce post harvest loss of cassava, and also increase food security and domestic agricultural productivity, there are downsides to the policy which include reduction in nutritional quality and low sensory appeal of cassava-wheat bread, reluctance of flour millers to use HQCF, technology and processing challenges among others. The policy thus presents an ethical dilemma which must be resolved for its successful implementation. While inclusion of HQCF to wheat flour in bread and confectionery is a topic that may have been well addressed, resolving the ethical dilemma resulting from the act has not received much attention. This paper attempts to resolve this dilemma using various approaches in food ethics (cost benefits, utilitarianism, deontological and deliberative). The Cost-benefit approach did not provide adequate resolution of the dilemma as all the costs and benefits of the policy could not be stated in the quantitative term. The utilitarianism approach suggests that the policy delivers greatest good to the greatest number while the deontological approach suggests that the act (inclusion of HQCF to wheat flour) is right hence the policy is not utterly wrong. The deliberative approach suggests a win-win situation through deliberation with the parties involved.

Keywords: HQCF, ethical dilemma, food security, composite flour, cassava bread

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Authors: Aghaei Amirkhizi Navideh, Sadjadi Soodeh Sadat, Moghaddam Banaem Leila, Athari Allaf Mitra, Johari Daha Fariba

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Dendrimers are good candidates for preparing metal nanoparticles because they can structurally and chemically well-defined templates and robust stabilizers. Poly amidoamine (PAMAM) dendrimer-based multifunctional cancer therapeutic conjugates have been designed and synthesized in pharmaceutical industry. In addition, encapsulated nanoparticle surfaces are accessible to substrates so that catalytic reactions can be carried out. For preparation of dendimer-metal nanocomposite, a dendrimer solution containing an average of 55 Yb+3 ions per dendrimer was prepared. Prior to reduction, the pH of this solution was adjusted to 7.5 using NaOH. NaBH4 was used to reduce the dendrimer-encapsulated Yb+3 to the zerovalent metal. The pH of the resulting solution was then adjusted to 3, using HClO4, to decompose excess BH4-. The UV-Vis absorption spectra of the mixture were recorded to ensure the formation of Yb-G5-NH2 complex. High-resolution electron microscopy (HRTEM) and size distribution results provide additional information about dendimer-metal nanocomposite shape, size, and size distribution of the particles. The resulting mixture was irradiated in Tehran Research Reactor 2h and neutron fluxes were 3×1011 n/cm2.Sec and the specific activity was 7MBq. Radiochemical and chemical and radionuclide quality control testes were carried. Gamma Spectroscopy and High-performance Liquid Chromatography HPLC, Thin-Layer Chromatography TLC were recorded. The injection of resulting solution to solid tumor in mice shows that it could be resized the tumor. The studies about solid tumors and nano composites show that ytterbium encapsulated-dendrimer radiopharmaceutical could be introduced as a new therapeutic for the treatment of solid tumors.

Keywords: nano-radio pharmaceutical, ytterbium, PAMAM, dendrimers

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Joanna Dzieńdziora

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Lobbying is an instrument of influence in various decision-making processes. It is also the underestimated issue as a research problem. The lack of research on the modern lobbyist competencies is the most crucial element. The paper presents attempts of finding answers to the following questions: Who should run the lobbying activity? What competencies should a lobbyist possess in order to implement lobbying activities effectively? Searching for answers for the mentioned above questions requires positioning the opportunity to change the image of lobbying in the area of competencies of entities that provide lobbying activities. The aim of the paper is presenting the lobbyist competencies profile in the framework of his professional role. The essence of lobbying activity and its significance in the modern economy as well as areas, the scope of lobbying activities, diagnosis of a modern lobbyist’s competences, lobbyist’s competencies profile that is focused on the professionalization of the lobbying activity, will have been presented in this paper. Indicated research tasks let emerge lobbyist’s competencies in the way that allows identifying and elaborating the lobbyist competencies profile. The profile lets improve lobbying activities. Its elaboration is based on the author’s research results analysis. Taking into consideration the shortages within the theory and research on the lobbying activity, the implementation of this research enables to fill the cognitive gap existing in the theory of management sciences.

Keywords: competencies, competencies profile, lobbying, lobbyist

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Authors: M. Zeitoun, K. Abdallah, M. Rashwan

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Introduction: A growing body of evidence indicates that apelin, a relatively recent member of the adipokines family, has a potential anti-atherogenic effect. An association between low serum apelin state and coronary artery disease (CAD) was previously reported; however, the relationship between apelin and the atherosclerotic burden was unclear. Objectives: Our aim was to explore the correlation of serum apelin level with coronary calcium score (CCS) as a quantitative marker of coronary atherosclerosis. Methods: This observational cross-sectional study enrolled 100 consecutive subjects referred for cardiac multi-detector computed tomography (MDCT) for assessment of CAD (mean age 54 ± 9.7 years, 51 male and 49 females). Clinical parameters, glycemic and lipid profile, high sensitivity CRP (hsCRP), homeostasis model assessment of insulin resistance (HOMA-IR), serum creatinine and complete blood count were assessed. Serum apelin levels were determined using a commercially available Enzyme Immunoassay (EIA) Kit. High-resolution non-contrast CT images were acquired by a 64-raw MDCT and CCS was calculated using the Agatston scoring method. Results: Forty-three percent of the studied subjects had positive coronary artery calcification (CAC). The mean CCS was 79 ± 196.5 Agatston units. Subjects with detectable CAC had significantly higher fasting plasma glucose, HbA1c, and WBCs count than subjects without detectable CAC (p < 0.05). Most importantly, subjects with detectable CAC had significantly lower serum apelin level than subjects without CAC (1.3 ± 0.4 ng/ml vs. 2.8 ± 0.6 ng/ml, p < 0.001). In addition, there was a statistically significant inverse correlation between serum apelin levels and CCS (r = 0.591, p < 0.001); on multivariate analysis this correlation was found to be independent of traditional cardiovascular risk factors and hs-CRP. Conclusion:To the best of our knowledge, this is the first report of an independent association between apelin and CCS in patients with suspected CAD. Apelin emerges as a possible novel biomarker for CAD, but this result remains to be proved prospectively.

Keywords: HbA1c, apelin, adipokines, coronary calcium score (CCS), coronary artery disease (CAD)

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Authors: Rowan Moore, Kai Scheffler, Eugen Damoc, Jennifer Sutton, Aaron Bailey, Stephane Houel, Simon Cubbon, Jonathan Josephs

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Purpose: MS analysis of monoclonal antibodies (mAbs) at the protein and peptide levels is critical during development and production of biopharmaceuticals. The compositions of current generation therapeutic proteins are often complex due to various modifications which may affect efficacy. Intact proteins analyzed by MS are detected in higher charge states that also provide more complexity in mass spectra. Protein analysis in native or native-like conditions with zero or minimal organic solvent and neutral or weakly acidic pH decreases charge state value resulting in mAb detection at higher m/z ranges with more spatial resolution. Methods: Three commercially available mAbs were used for all experiments. Intact proteins were desalted online using size exclusion chromatography (SEC) or reversed phase chromatography coupled on-line with a mass spectrometer. For streamlined use of the LC- MS platform we used a single SEC column and alternately selected specific mobile phases to perform separations in either denaturing or native-like conditions: buffer A (20 % ACN, 0.1 % FA) with Buffer B (100 mM ammonium acetate). For peptide analysis mAbs were proteolytically digested with and without prior reduction and alkylation. The mass spectrometer used for all experiments was a commercially available Thermo Scientific™ hybrid Quadrupole-Orbitrap™ mass spectrometer, equipped with the new BioPharma option which includes a new High Mass Range (HMR) mode that allows for improved high mass transmission and mass detection up to 8000 m/z. Results: We have analyzed the profiles of three mAbs under reducing and native conditions by direct infusion with offline desalting and with on-line desalting via size exclusion and reversed phase type columns. The presence of high salt under denaturing conditions was found to influence the observed charge state envelope and impact mass accuracy after spectral deconvolution. The significantly lower charge states observed under native conditions improves the spatial resolution of protein signals and has significant benefits for the analysis of antibody mixtures, e.g. lysine variants, degradants or sequence variants. This type of analysis requires the detection of masses beyond the standard mass range ranging up to 6000 m/z requiring the extended capabilities available in the new HMR mode. We have compared each antibody sample that was analyzed individually with mixtures in various relative concentrations. For this type of analysis, we observed that apparent native structures persist and ESI is benefited by the addition of low amounts of acetonitrile and formic acid in combination with the ammonium acetate-buffered mobile phase. For analyses on the peptide level we analyzed reduced/alkylated, and non-reduced proteolytic digests of the individual antibodies separated via reversed phase chromatography aiming to retrieve as much information as possible regarding sequence coverage, disulfide bridges, post-translational modifications such as various glycans, sequence variants, and their relative quantification. All data acquired were submitted to a single software package for analysis aiming to obtain a complete picture of the molecules analyzed. Here we demonstrate the capabilities of the mass spectrometer to fully characterize homogeneous and heterogeneous therapeutic proteins on one single platform. Conclusion: Full characterization of heterogeneous intact protein mixtures by improved mass separation on a quadrupole-Orbitrap™ mass spectrometer with extended capabilities has been demonstrated.

Keywords: disulfide bond analysis, intact analysis, native analysis, mass spectrometry, monoclonal antibodies, peptide mapping, post-translational modifications, sequence variants, size exclusion chromatography, therapeutic protein analysis, UHPLC

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Authors: Murat Demir Aydin, Elanur Celebi

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Adhesively bonded joints are used as an alternative to traditional joining methods due to the important advantages they provide. The most important consideration in the use of adhesively bonded joints is that these joints have appropriate requirements for their use in terms of safety. In order to ensure control of this condition, damage analysis of the adhesively bonded joints should be performed by determining the mechanical properties of the adhesives. When the literature is investigated; it is generally seen that the mechanical properties of adhesives are determined by traditional measurement methods. In this study, to determine the mechanical properties of adhesives, the Digital Image Correlation (DIC) method, which can be an alternative to traditional measurement methods, has been used. The DIC method is a new optical measurement method which is used to determine the parameters of displacement and strain in an appropriate and correct way. In this study, tensile tests of Thick Adherent Shear Test (TAST) samples formed using DP410 liquid structural adhesive and steel materials and bulk tensile specimens formed using and DP410 liquid structural adhesive was performed. The displacement and strain values of the samples were determined by DIC method and the shear stress-strain curves of the adhesive for TAST specimens and the tensile strain curves of the bulk adhesive specimens were obtained. Various methods such as numerical methods are required as conventional measurement methods (strain gauge, mechanic extensometer, etc.) are not sufficient in determining the strain and displacement values of the very thin adhesive layer such as TAST samples. As a result, the DIC method removes these requirements and easily achieves displacement measurements with sufficient accuracy.

Keywords: structural adhesive, adhesively bonded joints, digital image correlation, thick adhered shear test (TAST)

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Authors: Mohit Kalra, Varun S., Mayuri Gandhi

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CeF3 nanophosphors has been extensively investigated in the recent years for lighting and numerous bio-applications. Down conversion emissions in CeF3:Eu3+/Tb3+ phosphors were studied with the aim of obtaining a white light emitting composition, by a simple co-precipitation method. The material was characterized by X-ray Diffraction (XRD), High Resolution Transmission Electron Microscopy (HR-TEM), Fourier Transform Infrared Spectroscopy (FT-IR) and Photoluminescence (PL). Uniformly distributed nanoparticles were obtained with an average particle size 8-10 nm. Different doping concentrations were performed and fluorescence study was carried out to optimize the dopants concentration for maximum luminescence intensity. The steady state and time resolved luminescence studies confirmed efficient energy transfer from the host to activator ions. Different concentrations of Tb 3+, Eu 3+ were doped to achieve a white light emitting phosphor for UV-based Light Emitting Diodes (LEDs). The nanoparticles showed characteristic emission of respective dopants (Eu 3+, Tb3+) when excited at the 4f→5d transition of Ce3+. The chromaticity coordinates for these samples were calculated and the CeF3 doped with Eu 3+ and Tb3+ gave an emission very close to white light. These materials may find its applications in optoelectronics and various bio applications.

Keywords: white light down-conversion, nanophosphors, LEDs, rare earth, cerium fluoride, lanthanides

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Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

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Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas

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Authors: Fentie, Belay, Mulat

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In today’s high decrement figure of the global economy, nations are facing many economic, social and political challenges; universally, there is high distress of food and other survival insecurity. Further, as a result of conflict, natural disasters, and leadership influences, youths are existentially less empowered and unemployed, especially in developing countries. With this situation to handle well challenges, it’s important to search, investigate and deliberate about youth, unemployment, empowerment and possible management fashions, as youths have the potential to carry and fight such battles. The method adopted is a qualitative analysis of secondary data sources in youth empowerment, unemployment and development as an inclusive framework. Youth unemployment is a major development headache for most African countries. In Ethiopia, following weak youth empowerment, youth unemployment has increased from time to time, and quality education and organization linkage matter as an important constraint. As a management challenge, although accessibility of quality education for Ethiopian youths is an important constraint, the country's youths are fortified deceptively and harassed in a vicious political challenge in their struggle to fetch social and economic changes in the country. Further, thousands of youths are inactivated, criminalized and lost their lives and this makes youths hopeless anger in their lives and pushes them further to be exposed for addictions, prostitution, violence, and illegitimate migrations. This youth challenge wasn’t only destined for African countries; rather, indeed, it was a global burden and headed as a global agenda. As a resolution, the construction of a healthy education system can create independent youths who acquire success and accelerate development. Developing countries should ensue development in the cultivation of empowerment tools through long and short-term education, implementing policy in action, diminishing wide-ranging gaps of (religion, ethnicity & region), and take high youth population as an opportunity and empower them. Further managing and empowering youths to be involved in decision-making, giving political weight and building a network of organizations to easily access job opportunities are important suggestions to save youths in work, for both increasing their income and the country's food security balance.

Keywords: development, Ethiopia, management, unemployment, youth empowerment

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Laura Pytel, Georg Baumann, Gregor Gstrein, Corina Klug

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Premium cars often coat the instrument panels with a bilaminate consisting of a soft foam and a plastic skin. The coating is torn open during the passenger airbag deployment under high strain rates. Characterizing and simulating the top coat layer is crucial for predicting the attenuation that delays the airbag deployment, effecting the design of the restrain system and to reduce the demand of simulation adjustments through expensive physical component testing.Up to now, bilaminates used within cars either have been modelled by using a two-dimensional shell formulation for the whole coating system as one which misses out the interaction of the two layers or by combining a three-dimensional formulation foam layer with a two-dimensional skin layer but omitting the foam in the significant parts like the expected tear line area and the hinge where high compression is expected. In both cases, the properties of the coating causing the attenuation are not considered. Further, at present, the availability of material information, as there are failure dependencies of the two layers, as well as the strain rate of up to 200 1/s, are insufficient. The velocity of the passenger airbag flap during an airbag shot has been measured with about 11.5 m/s during first ripping; the digital image correlation evaluation showed resulting strain rates of above 1500 1/s. This paper provides a high strain rate material characterization of a bilaminate consisting of a thin polypropylene foam and a thermoplasctic olefins (TPO) skin and the creation of validated material models. With the help of a Split Hopkinson tension bar, strain rates of 1500 1/s were within reach. The experimental data was used to calibrate and validate a more physical modelling approach of the forced ripping of the bilaminate. In the presented model, the three-dimensional foam layer is continuously tied to the two-dimensional skin layer, allowing failure in both layers at any possible position. The simulation results show a higher agreement in terms of the trajectory of the flaps and its velocity during ripping. The resulting attenuation of the airbag deployment measured by the contact force between airbag and flaps increases and serves usable data for dimensioning modules of an airbag system.

Keywords: bilaminate ripping behavior, High strain rate material characterization and modelling, induced material failure, TPO and foam

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Emily Kislik, Gabriel Mantilla Saltos, Gladys Torres, Mercy Borbor-Córdova

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The Galápagos Marine Reserve (GMR) is an internationally-recognized region of consistent upwelling events, high productivity, and rich biodiversity. Despite its high-nutrient, low-chlorophyll condition, the archipelago has experienced phytoplankton blooms, especially in the western section between Isabela and Fernandina Islands. However, little is known about how climate variability will affect future phytoplankton standing stock in the Galápagos, and no consistent protocols currently exist to quantify phytoplankton biomass, identify species, or monitor for potential harmful algal blooms (HABs) within the archipelago. This analysis investigates physical, chemical, and biological oceanic variables that contribute to algal blooms within the GMR, using 4 km Aqua MODIS satellite imagery and 0.125-degree wind stress data from January 2003 to December 2016. Furthermore, this study analyzes chlorophyll-a concentrations at varying spatial scales— within the greater archipelago, as well as within five smaller bioregions based on species biodiversity in the GMR. Seasonal and interannual trend analyses, correlations, and hotspot identification were performed. Results demonstrate that chlorophyll-a is expressed in two seasons throughout the year in the GMR, most frequently in September and March, with a notable hotspot in the Elizabeth Bay bioregion. Interannual chlorophyll-a trend analyses revealed highest peaks in 2003, 2007, 2013, and 2016, and variables that correlate highly with chlorophyll-a include surface temperature and particulate organic carbon. This study recommends future in situ sampling locations for phytoplankton monitoring, including the Elizabeth Bay bioregion. Conclusions from this study contribute to the knowledge of oceanic drivers that catalyze primary productivity and consequently affect species biodiversity within the GMR. Additionally, this research can inform policy and decision-making strategies for species conservation and management within bioregions of the Galápagos.

Keywords: bioregions, ecological monitoring, phytoplankton, remote sensing

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Rahmi Kafadar, Levent Genc

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In present study, it was aimed to determine potential agricultural lands (PALs) in Gokceada (Imroz) Island of Canakkale province, Turkey. Seven-band Landsat 8 OLI images acquired on July 12 and August 13, 2013, and their 14-band combination image were used to identify current Land Use Land Cover (LULC) status. Principal Component Analysis (PCA) was applied to three Landsat datasets in order to reduce the correlation between the bands. A total of six Original and PCA images were classified using supervised classification method to obtain the LULC maps including 6 main classes (“Forest”, “Agriculture”, “Water Surface”, “Residential Area-Bare Soil”, “Reforestation” and “Other”). Accuracy assessment was performed by checking the accuracy of 120 randomized points for each LULC maps. The best overall accuracy and Kappa statistic values (90.83%, 0.8791% respectively) were found for PCA images which were generated from 14-bands combined images called 3-B/JA. Digital Elevation Model (DEM) with 15 m spatial resolution (ASTER) was used to consider topographical characteristics. Soil properties were obtained by digitizing 1:25000 scaled soil maps of rural services directorate general. Potential Agricultural Lands (PALs) were determined using Geographic information Systems (GIS). Procedure was applied considering that “Other” class of LULC map may be used for agricultural purposes in the future properties. Overlaying analysis was conducted using Slope (S), Land Use Capability Class (LUCC), Other Soil Properties (OSP) and Land Use Capability Sub-Class (SUBC) properties. A total of 901.62 ha areas within “Other” class (15798.2 ha) of LULC map were determined as PALs. These lands were ranked as “Very Suitable”, “Suitable”, “Moderate Suitable” and “Low Suitable”. It was determined that the 8.03 ha were classified as “Very Suitable” while 18.59 ha as suitable and 11.44 ha as “Moderate Suitable” for PALs. In addition, 756.56 ha were found to be “Low Suitable”. The results obtained from this preliminary study can serve as basis for further studies.

Keywords: digital elevation model (DEM), geographic information systems (GIS), gokceada (Imroz), lANDSAT 8 OLI-TIRS, land use land cover (LULC)

Procedia PDF Downloads 353

Authors: Sher Muhammad, Mirza Muhammad Waqar

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It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79 to 24.85 degree in latitude and 66.91 to 66.97 degree in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image preprocessing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end-member extraction. Well-distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (white mangroves) and Avicennia Germinans (black mangroves) have been observed throughout the study area.

Keywords: mangrove, hyperspectral, hyperion, SAM, SFF, SID

Procedia PDF Downloads 362

Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

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Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

Procedia PDF Downloads 396

Authors: M. Owlia, M. H. Azarsa, M. Khabbazan, A. Mirbagheri

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Proprioceptive neuromuscular facilitation exercises are a series of stretching techniques that are commonly used in rehabilitation and exercise therapy. Assessment of these exercises for true maneuvering requires extensive experience in this field and could not be down with patients themselves. In this paper, we developed software that uses Microsoft Kinect sensor, a spherical color marker, and real-time image processing methods to evaluate patient’s performance in generating true patterns of movements. The software also provides the patient with a visual feedback by showing his/her avatar in a Virtual Reality environment along with the correct path of moving hand, wrist and marker. Primary results during PNF exercise therapy of a patient in a room environment shows the ability of the system to identify any deviation of maneuvering path and direction of the hand from the one that has been performed by an expert physician.

Keywords: image processing, Microsoft Kinect, proprioceptive neuromuscular facilitation, upper extremities assessment, virtual reality

Procedia PDF Downloads 273

Authors: Elhadi Nasr, Ibrahim Ramadan

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Biostratigraphical analyses of well sections from the Maragh Low in the Eastern Sirt Basin has allowed high resolution correlations to be undertaken. Full integration of this data with available palaeoenvironmental, lithological, gravity, seismic, aeromagnetic, igneous, radiometric and wireline log information and a geochemical analysis of source rock quality and distribution has led to a more detailed understanding of the geological and the structural history of this area. Pre Sirt Unconformity two superimposed rifting cycles have been identified. The oldest is represented by the Amal Group of sediments and is of Late Carboniferous, Kasimovian / Gzelian to Middle Triassic, Anisian age. Unconformably overlying is a younger rift cycle which is represented the Sarir Group of sediments and is of Early Cretaceous, late Neocomian to Aptian in age. Overlying the Sirt Unconformity is the marine Late Cretaceous section. An assessment of pyrolysis results and a palynofacies analysis has allowed hydrocarbon source facies and quality to be determined. There are a number of hydrocarbon source rock horizons in the Maragh Low, these are sometimes vertically stacked and they are of fair to excellent quality. The oldest identified source rock is the Triassic Shale, this unit is unconformably overlain by sandstones belonging to the Sarir Group and conformably overlies a Triassic Siltstone unit. Palynological dating of the Triassic Shale unit indicates a Middle Triassic, Anisian age. The Triassic Shale is interpreted to have been deposited in a lacustrine palaeoenvironment. This particularly is evidenced by the dark, fine grained, organic rich nature of the sediment and is supported by palynofacies analysis and by the recovery of fish fossils. Geochemical analysis of the Triassic Shale indicates total organic carbon varying between 1.37 and 3.53. S2 pyrolysate yields vary between 2.15 mg/g and 6.61 mg/g and hydrogen indices vary between 156.91 and 278.91. The source quality of the Triassic Shale varies from being of fair to very good / rich. Linked to thermal maturity it is now a very good source for light oil and gas. It was once a very good to rich oil source. The Early Barremian Shale was also deposited in a lacustrine palaeoenvironment. Recovered palynomorphs indicate an Early Cretaceous, late Neocomian to early Barremian age. The Early Barremian Shale is conformably underlain and overlain by sandstone units belonging to the Sarir Group of sediments which are also of Early Cretaceous age. Geochemical analysis of the Early Barremian Shale indicates that it is a good oil source and was originally very good. Total organic carbon varies between 3.59% and 7%. S2 varies between 6.30 mg/g and 10.39 mg/g and the hydrogen indices vary between 148.4 and 175.5. A Late Barremian Shale unit of this age has also been identified in the central Maragh Low. Geochemical analyses indicate that total organic carbon varies between 1.05 and 2.38%, S2 pyrolysate between 1.6 and 5.34 mg/g and the hydrogen index between 152.4 and 224.4. It is a good oil source rock which is now mature. In addition to the non marine hydrocarbon source rocks pre Sirt Unconformity, three formations in the overlying Late Cretaceous section also provide hydrocarbon quality source rocks. Interbedded shales within the Rachmat Formation of Late Cretaceous, early Campanian age have total organic carbon ranging between, 0.7 and 1.47%, S2 pyrolysate varying between 1.37 and 4.00 mg/g and hydrogen indices varying between 195.7 and 272.1. The indication is that this unit would provide a fair gas source to a good oil source. Geochemical analyses of the overlying Tagrifet Limestone indicate that total organic carbon varies between 0.26% and 1.01%. S2 pyrolysate varies between 1.21 and 2.16 mg/g and hydrogen indices vary between 195.7 and 465.4. For the overlying Sirt Shale Formation of Late Cretaceous, late Campanian age, total organic carbon varies between 1.04% and 1.51%, S2 pyrolysate varies between 4.65 mg/g and 6.99 mg/g and the hydrogen indices vary between 151 and 462.9. The study has proven that both the Sirt Shale Formation and the Tagrifet Limestone are good to very good and rich sources for oil in the Maragh Low. High resolution biostratigraphical interpretations have been integrated and calibrated with thermal maturity determinations (Vitrinite Reflectance (%Ro), Spore Colour Index (SCI) and Tmax (ºC) and the determined present day geothermal gradient of 25ºC / Km for the Maragh Low. Interpretation of generated basin modelling profiles allows a detailed prediction of timing of maturation development of these source horizons and leads to a determination of amounts of missing section at major unconformities. From the results the top of the oil window (0.72% Ro) is picked as high as 10,700’ and the base of the oil window (1.35% Ro) assuming a linear trend and by projection is picked as low as 18,000’ in the Maragh Low. For the Triassic Shale the early phase of oil generation was in the Late Palaeocene / Early to Middle Eocene and the main phase of oil generation was in the Middle to Late Eocene. The Early Barremian Shale reached the main phase of oil generation in the Early Oligocene with late generation being reached in the Middle Miocene. For the Rakb Group section (Rachmat Formation, Tagrifet Limestone and Sirt Shale Formation) the early phase of oil generation started in the Late Eocene with the main phase of generation being between the Early Oligocene and the Early Miocene. From studying maturity profiles and from regional considerations it can be predicted that up to 500’ of sediment may have been deposited and eroded by the Sirt Unconformity in the central Maragh Low while up to 2000’ of sediment may have been deposited and then eroded to the south of the trough.

Keywords: Geochemical analysis of the source rocks from wells in Eastern Sirt Basin.

Procedia PDF Downloads 409

Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

Procedia PDF Downloads 378

Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

Procedia PDF Downloads 104

Authors: S. Slimani, B. Djellouli

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Novel materials and innovative device structures has become necessary for the future of CMOS. High mobility materials like Ge is a very promising material due to its high mobility and is being considered to replace Si in the channel to achieve higher drive currents and switching speeds .Various approaches to circumvent the scaling limits to benchmark the performance of nanoscale MOSFETS with different channel materials, the optimized structure is simulated within nextnano in order to highlight the quantum effects on DG MOSFETs when Si is replaced by Ge and SiO2 is replaced by ZrO2 and HfO2as the gate dielectric. The results have shown that Ge MOSFET have the highest mobility and high permittivity oxides serve to maintain high drive current. The simulations show significant improvements compared with DGMOSFET using SiO2 gate dielectric and Si channel.

Keywords: high mobility, high-k, quantum effects, SOI-DGMOSFET

Procedia PDF Downloads 367

Authors: Hsiao-Yung Wang

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This paper aims to elaborate methodology of visual rhetoric with constant reference to Mikhail Bakhtin’s concept of “chronotope”. First, it attempts to outline Ronald Barthes, the most representative scholar of visual rhetoric and structuralism, perspective on visual rhetoric and its time-space category by referring to the concurrent word-image, the symbolic systematicity, the outer dialogicity. Second, an alternative approach is explored for grasping the dynamics and functions of visual rhetoric by articulating Mikhail Bakhtin’s concept of “chronotope.” Furthermore, that visual rhetorical consciousness could be identified as “the meaning parabola which projects from word to image,” “the symbolic system which proceeds from sequence to disorder,” “the ideological environment which struggles from the local to the global.” Last but not least, primary vision of the 2014 Taipei LGBT parade would be analyzed preliminarily to evaluate the effectiveness and persuasiveness embodied by specific visual rhetorical strategies. How Bakhtin’s concept of “chronotope” to explain the potential or possible ideological struggle deployed by visual rhetoric might be interpreted empirically and extensively.

Keywords: barthes, chronotope, Mikhail Bakhtin, Taipei LGBT parade, visual rhetoric

Procedia PDF Downloads 478

Authors: Paulo Fernando Silva Filho, Elcio Hideiti Shiguemori

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The selection of specific landmarks for an Unmanned Aerial Vehicles’ Visual Navigation systems based on Automatic Landmark Recognition has significant influence on the precision of the system’s estimated position. At the same time, manual selection of the landmarks does not guarantee a high recognition rate, which would also result on a poor precision. This work aims to develop an automatic landmark selection that will take the image of the flight area and identify the best landmarks to be recognized by the Visual Navigation Landmark Recognition System. The criterion to select a landmark is based on features detected by ORB or AKAZE and edges information on each possible landmark. Results have shown that disposition of possible landmarks is quite different from the human perception.

Keywords: clustering, edges, feature points, landmark selection, X-means

Procedia PDF Downloads 281

Authors: Brahim Balizi, Ayoub Aziz, Abdelilah Bellil, Abdellali El Khadiri, Jamal Mabrouki

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Mio-polio-quaternary volcanism of the Tabular Middle Atlas, which corresponds to prospective levels of exploitable usable raw minerals, is a feature of Morocco's Middle Atlas, especially the Azrou-Timahdite region. Given their importance in national policy in terms of human development by supporting the sociological and economic component, this area has consequently been the focus of various research and prospecting of these levels in order to develop these reserves. The outcome of this labor is a massive amount of data that needs to be managed appropriately because it comes from multiple sources and formats, including side points, contour lines, geology, hydrogeology, hydrology, geological and topographical maps, satellite photos, and more. In this regard, putting in place a Geographic Information System (GIS) is essential to be able to offer a side plan that makes it possible to see the most recent topography of the area being exploited, to compute the volume of exploitation that occurs every day, and to make decisions with the fewest possible restrictions in order to use the reserves for the realization of ecological light mortars The three sites' mining will follow the contour lines in five steps that are six meters high and decline. It is anticipated that each quarry produces about 90,000 m3/year. For a single quarry, this translates to a daily production of about 450 m3 (200 days/year). About 3,540,240 m3 and 10,620,720 m3, respectively, represent the possible net exploitable volume in place for a single quarry and the three exploitable zones.

Keywords: GIS, topography, exploitation, quarrying, lightweight mortar

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Authors: Belay Mulat Fentie

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In today’s high decrement figure of the global economy, nations are facing many economic, social, and political challenges; universally, there is high distress of food and other survival insecurity. Further, as a result of conflict, natural disaster, and leadership influences, youths are existentially less empowered and unemployed, especially in developing countries. With this situation to handle well challenges, it’s important to search, investigate and deliberate about youth, unemployment, empowerment, and possible management fashions, as youths has a potential to carry and fight such battles. The method adopted is qualitative analysis of secondary data sources in youth empowerment, unemployment, and development as inclusive framework. Youth unemployment is a major development headache for most African countries. In Ethiopia, following weak youth empowerment, youth unemployment has been increased time to time; and quality education and organizations linkage matters as an important constraint. As a management challenge, although accessibility of quality education for Ethiopian youths is an important constraint; the country youths fortified deceptively and harassed in a vicious political challenge in their struggle to fetch social and economic changes in the country. Further, thousands of youths inactivated, criminalized, and lost their lives, and this makes youths to be hopeless, anger in their lives and pushes further to expose for addictions, prostitution, violence, and illegitimate migrations. This youth challenge didn’t only destinate in African countries, rather, indeed, the global burden and headed as a global agenda. As a resolution, the construction of a healthy education system can create independent youths that acquire success and accelerate development. Developing countries should ensue development in cultivation of empowerment tool through long and short-term education, implementing policy in action, diminishing wide ranged gaps of (religion, ethnicity & region), and take the high youth population as an opportunity and empower them. And further manage and empower youths to involve in decision making, in giving political weight and build a network on organizations to easily access jobs opportunities are important suggestion to alive youths in work, for both increasing their income and country food security balance.

Keywords: development, Ethiopia, management, unemployment, youth empowerment

Procedia PDF Downloads 141