Search results for: fixed live camera images

Authors: Shamsundar Kulkarni

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Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion, image blurring etc. Hence, many researchers study such drawbacks to enhance the quality of videos. In this paper, an algorithm is proposed to stabilize jittery videos .A stable output video will be attained without the effect of jitter which is caused due to shaking of handheld camera during video recording. Firstly, salient points from each frame from the input video are identified and processed followed by optimizing and stabilize the video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.

Keywords: video stabilization, point feature matching, salient points, image quality measurement

Procedia PDF Downloads 291

Authors: Wei Zhang, Yan He, Yan Wang, Yufeng Li, Chuanpeng Hao

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Surface roughness is an important index for evaluating surface quality, needs to be accurately measured to ensure the performance of the workpiece. The roughness measurement based on machine vision involves various image features, some of which are redundant. These redundant features affect the accuracy and speed of the visual approach. Previous research used correlation analysis methods to select the appropriate features. However, this feature analysis is independent and cannot fully utilize the information of data. Besides, blindly reducing features lose a lot of useful information, resulting in unreliable results. Therefore, the focus of this paper is on providing a redundant feature removal approach for visual roughness measurement. In this paper, the statistical methods and gray-level co-occurrence matrix(GLCM) are employed to extract the texture features of machined images effectively. Then, the principal component analysis(PCA) is used to fuse all extracted features into a new one, which reduces the feature dimension and maintains the integrity of the original information. Finally, the relationship between new features and roughness is established by the support vector machine(SVM). The experimental results show that the approach can effectively solve multi-feature information redundancy of machined surface images and provides a new idea for the visual evaluation of surface roughness.

Keywords: feature analysis, machine vision, PCA, surface roughness, SVM

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Authors: Tabassum Yasmin, Hamid Pahlevan

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HIV/Hepatitis C co-infection treatments have evolved substantially and they have similar sustained virologic response rates as those of Hepatitis C monoinfected population. There are a few studies on therapy of patients with dual genotypes, especially in HIV/Hepatic C coinfected group. Most studies portrayed case reports of dual genotype chronic Hepatitis C coinfection treatment with Sofosbuvir/Ledipasvir and Ribavirin. A 79-year-old male with a history of HIV on Truvada and Isentress had chronic Hepatitis C with 1a and 2 genotypes. The patient has a history of alcohol intake for 40 years but recently stopped drinking alcohol. He has a history of intravenous drug use in the past and currently is not using any recreational drugs. Patient has Fibro score of 0.7 with Metavir score F2 to F4. AFP is 3.2. The HCV RNA is 493,034 IU/ML. The HBV viral DNA is < 1.30 (not detected). The CD4 is 687CU/MM. The FIB 4 is 3.34 with APRI index 0.717. The HIV viral load is 101 copies/ML. MRI abdomen did not show any liver abnormality. Fixed dose Sofosbuvir/Ledipasvir was used for therapy without Ribavirin. He tolerated medication except for some minor gastrointestinal side effects like abdominal bloating. He demonstrated 100% adherence rate. Patient completed 12 weeks of therapy. HCV RNA was undetectable at 4 and 12 weeks. He achieved SVR at week 12 and subsequently had undetectable RNA for 2 years. Dual genotype prevalence in chronic hepatitis C population is rare, especially in HIV/hepatic coinfection. Our case demonstrates that dual genotypic cases can still be successfully treated with Direct Acting Antiviral agents. The newer agents for therapy for pan genotypes were not available at the time the patient was being treated. We demonstrated that dual agent therapy was still able to maintain SVR in our patient.

Keywords: HIV/Hepatitis C, SVR (sustained virologic response), DAA (direct active antiviral agents, dual genotype

Procedia PDF Downloads 179

Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

Procedia PDF Downloads 107

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 115

Authors: Alireza Abbasi Moshaii, Farshid Najafi

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In this paper a new model for centre of motion creating is proposed. This new method uses cables. So, it is very useful in robots because it is light and has easy assembling process. In the robots which need to be in touch with some things this method is very good. It will be described in the following. The accuracy of the idea is proved by an experiment. This system could be used in the robots which need a fixed point in the contact with some things and make a circular motion. Such as dancer, physician or repair robots.

Keywords: centre of motion, robotic cables, permanent touching, mechatronics engineering

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Authors: Talal Alharigi, Kawther Alshlash, Mariska Weijerman

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The government of Saudi Arabia has developed an ambitious “Vision 2030”, which includes a Green Initiative (i.e., the planting of 10 billion trees) and the establishment of seven Royal Reserves as protected areas that comprise 13% of the total land area. The main objective of the reserves is to restore ecosystem balance and reconnect people with nature. Two royal reserves are managed by The Imam Abdulaziz bin Mohammed Royal Reserve Development Authority, including Imam Abdulaziz bin Mohammed Royal Reserve and King Khalid Royal Reserve. The authority has developed a management plan to enhance the habitat through seed dispersal and the planting of 10 million trees, and to restock wildlife that was once abundant in these arid ecosystems (e.g., oryx, Nubian ibex, gazelles, red-necked ostrich). Expectations are that with the restoration of the native vegetation, soil condition and natural hydrologic processes will improve and lead to further enhancement of vegetation and, over time, an increase in biodiversity of flora and fauna. To evaluate the management strategies in reaching these expectations, a comprehensive monitoring and evaluation program was developed. The main objectives of this program are to (1) monitor the status and trends of indicator species, (2) improve desert ecosystem understanding, (3) assess the effects of human activities, and (4) provide science-based management recommendations. Using a random stratified survey design, a diverse suite of survey methods will be implemented, including belt and quadrant transects, camera traps, GPS tracking devices, and drones. Data will be gathered on biotic parameters (plant and animal diversity, density, and distribution) and abiotic parameters (humidity, temperature, precipitation, wind, air, soil quality, vibrations, and noise levels) to meet the goals of the monitoring program. This case study intends to provide a detailed overview of the management plan and monitoring program of two royal reserves and outlines the types of data gathered which can be made available for future research projects.

Keywords: camera traps, desert ecosystem, enhancement, GPS tracking, management evaluation, monitoring, planting, restocking, restoration

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Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger

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Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.

Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration

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Authors: Ozgun Oktar, Sevilay Can, Cengiz V. Ekici

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The oil spill is a form of pollution caused by releasing of a liquid petroleum hydrocarbon into the marine environment. Considering the growth of ship traffic, increasing of off-shore oil drilling and seaside refineries affect the risk of oil spill upward. The oil spill is easy to spread to large areas when occurs especially on the sea surface. Remote sensing technology offers the easiest way to control/monitor the area of the oil spill in a large region. It’s usually easy to detect pollution when occurs by the ship accidents, however monitoring non-accidental pollution could be possible by remote sensing. It is also needed to observe specific regions daily and continuously by satellite solutions. Remote sensing satellites mostly and effectively used for monitoring oil pollution are RADARSAT, ENVISAT and MODIS. Spectral coverage and transition period of these satellites are not proper to monitor Marmara Sea and Istanbul Strait continuously. In this study, RASAT and GOKTURK-2 are suggested to use for monitoring Marmara Sea and Istanbul Strait. RASAT, with spectral resolution 420 – 730 nm, is the first Turkish-built satellite. GOKTURK-2’s resolution can reach up to 2,5 meters. This study aims to analyze the images from both satellites and produce maps to show the regions which have potentially affected by spills from shipping traffic.

Keywords: Marmara Sea, monitoring, oil spill, satellite remote sensing

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Authors: Brighton Chamunorwa

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The current remote sensing of water quality procedures does not provide a step representing physical visualisation of the monitored dam. The application of the remote sensing of water quality techniques may benefit from use of mathematical morphology operators for shape identification. Given an input of dam outline, morphological operators such as the hit or miss transform identifies if the water body is present on input remotely sensed images. This study seeks to determine the accuracy of the hit or miss transform to identify dams monitored by the water resources authorities in South Africa on satellite images. To achieve this objective the study download a Landsat image acquired in winter and tested the capability of the hit or miss transform using shapefile boundaries of dams in the crocodile marico catchment. The results of the experiment show that it is possible to detect most dams on the Landsat image after the adjusting the erosion operator to detect pixel matching a percentage similarity of 80% and above. Successfully implementation of the current study contributes towards optimisation of mathematical morphology image operators. Additionally, the effort helps develop remote sensing of water quality monitoring with improved simulation of the conventional procedures.

Keywords: hit or miss transform, mathematical morphology, remote sensing, water quality monitoring

Procedia PDF Downloads 131

Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Tassili, occupying a large area of Algeria, is characterized by a rich vegetative biodiversity to be preserved and managed both in time and space. The management of a large area (case of Tassili), by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information etc.), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Multispectral imaging sensors have been very useful in the last decade in very interesting applications of remote sensing. They can aid in several domains such as the de¬tection and identification of diverse surface targets, topographical details, and geological features. In this work, we try to extract vegetative areas using fusion techniques between data acquired from sensor on-board the Earth Observing 1 (EO-1) satellite and Landsat ETM+ and TM sensors. We have used images acquired over the Oasis of Djanet in the National Park of Tassili in the south of Algeria. Fusion technqiues were applied on the obtained image to extract the vegetative fraction of the different classes of land use. We compare the obtained results in vegetation end member extraction with vegetation indices calculated from both Hyperion and other multispectral sensors.

Keywords: Landsat ETM+, EO1, data fusion, vegetation, Tassili, Algeria

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Authors: Maysam Shahsavari, Seyed Jamalaldin Haddadi

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There are several methods to localize a mobile robot such as relative, absolute and probabilistic. In this paper, particle filter due to its simple implementation and the fact that it does not need to know to the starting position will be used. This method estimates the position of the mobile robot using a probabilistic distribution, relying on a known map of the environment instead of predicting it. Afterwards, it updates this estimation by reading input sensors and control commands. To receive information from the surrounding world, distance to obstacles, for example, a Kinect is used which is much cheaper than a laser range finder. Finally, after explaining the Adaptive Particle Filter method and its implementation in detail, we will compare this method with the dead reckoning method and show that this method is much more suitable for situations in which we have a map of the environment.

Keywords: particle filter, localization, methods, odometry, kinect

Procedia PDF Downloads 247

Authors: Juan C. Gutierrez-Estrada, Inmaculada Pulido-Calvo, Ignacio De La Rosa, Antonio Peregrin, Fernando Gomez-Bravo, Samuel Lopez-Dominguez, Alejandro Garrocho-Cruz, Jairo Castro-Gutierrez

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The semi-intensive aquaculture in traditional earth ponds is the main rearing system in Southern Spain. These fish rearing systems are approximately two thirds of aquatic production in this area which has made a significant contribution to the regional economy in recent years. In this type of rearing system, a crucial aspect is the correct quantification and control of the fish abundance in the ponds because the fish farmer knows how many fishes he puts in the ponds but doesn’t know how many fishes will harvest at the end of the rear period. This is a consequence of the mortality induced by different causes as pathogen agents as parasites, viruses and bacteria and other factors as predation of fish-eating birds and poaching. Track the fish abundance in these installations is very difficult because usually the ponds take up a large area of land and the management of the water flow is not automatized. Therefore, there is a very high degree of uncertainty on the abundance fishes which strongly hinders the management and planning of the sales. A novel and non-invasive procedure to count fishes in the ponds is by the means of imaging sonars, particularly fixed systems and/or linked to aquatic vehicles as Remotely Operated Vehicles (ROVs). In this work, a method based on census stations procedures is proposed to evaluate the fish abundance estimation accuracy using images obtained of multibeam sonars. The results indicate that it is possible to obtain a realistic approach about the number of fishes, sizes and therefore the biomass contained in the ponds. This research is included in the framework of the KTTSeaDrones Project (‘Conocimiento y transferencia de tecnología sobre vehículos aéreos y acuáticos para el desarrollo transfronterizo de ciencias marinas y pesqueras 0622-KTTSEADRONES-5-E’) financed by the European Regional Development Fund (ERDF) through the Interreg V-A Spain-Portugal Programme (POCTEP) 2014-2020.

Keywords: census station procedure, fish biomass, semi-intensive aquaculture, multibeam sonars

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

Procedia PDF Downloads 102

Authors: Sergio A. Navarro Tuch, Martin Rogelio Bustamante Bello, Leopoldo Julian Lechuga Lopez

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In recent years, Mexico’s population has seen a rise of different physiological and mental negative states. Two main consequences of this problematic are deficient work performance and high levels of stress generating and important impact on a person’s physical, mental and emotional health. Several approaches, such as the use of audiovisual stimulus to induce emotions and modify a person’s emotional state, can be applied in an effort to decreases these negative effects. With the use of different non-invasive physiological sensors such as EEG, luminosity and face recognition we gather information of the subject’s current emotional state. In a controlled environment, a subject is shown a series of selected images from the International Affective Picture System (IAPS) in order to induce a specific set of emotions and obtain information from the sensors. The raw data obtained is statistically analyzed in order to filter only the specific groups of information that relate to a subject’s emotions and current values of the physical variables in the controlled environment such as, luminosity, RGB light color, temperature, oxygen level and noise. Finally, a neural network based control algorithm is given the data obtained in order to feedback the system and automate the modification of the environment variables and audiovisual content shown in an effort that these changes can positively alter the subject’s emotional state. During the research, it was found that the light color was directly related to the type of impact generated by the audiovisual content on the subject’s emotional state. Red illumination increased the impact of violent images and green illumination along with relaxing images decreased the subject’s levels of anxiety. Specific differences between men and women were found as to which type of images generated a greater impact in either gender. The population sample was mainly constituted by college students whose data analysis showed a decreased sensibility to violence towards humans. Despite the early stage of the control algorithm, the results obtained from the population sample give us a better insight into the possibilities of emotional domotics and the applications that can be created towards the improvement of performance in people’s lives. The objective of this research is to create a positive impact with the application of technology to everyday activities; nonetheless, an ethical problem arises since this can also be applied to control a person’s emotions and shift their decision making.

Keywords: data analysis, emotional domotics, performance improvement, neural network

Procedia PDF Downloads 122

Authors: Farhad Ahmadi, Vafa Pahlavani, Pejman Bidar

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This study was conducted to investigate the effect of zinc oxide nanoparticles (Nano-ZnO) on carcass quality, blood parameters, and gut morphology in broiler chickens feeding wet diets. This research was conducted by total of 300 one-day-old broiler chicks (Ross-308) were distributed into a completely randomized design inclusion of 5 treatments in 4 replicated and 15 birds in each from 1 to 42 d. The experimental diets contain: 1) diet-based on corn-soybean dry (without Nano-ZnO), 2) dry diet whit 25 mg Nano-ZnO, 3) wet diet whit 25 mg Nano-ZnO, 4) dry diet whit 50 mg Nano-ZnO, 5) wet diet whit 50 mg Nano-ZnO to wet diet. The results indicated that trail diets had no significant effect on carcass and fraction cuts in 21 age (P > 0.05). Wet feeding increased (P < 0.05) live, carcass, pancreas, gizzard, proventriculus, breast, wing and SI weight index so that the birds fed wet diet contain 50mg/kg of Nano-ZnO had the highest (P < 0.05) live, carcass, pancreas, proventriculus, gizzard, breast, wing, and gut weights at 42d compared other treatments. The birds fed diet contain 25mg/kg Nano-ZnO had the higher (P < 0.05) leg weight and lowest gizzard and gut weight than others treatment. Wet diet inclusion of 50mg Nano-ZnO increased (P < 0.05) liver weight on d 42. Experimental treatments had no significant effect on blood hematology on 21 and 42. The lymphocyte count had increased (P < 0.05) in dry than wet diet, however, monocyte Percent had significantly (P < 0.05) decreased in dry and increased in wet diets. The birds of height and height: crypts villi ratio had significantly (P < 0.05) increased on d 42, so that the highest and lowest villus height observed in 50 mg Nano-ZnO to form dry and control, respectively. In conclusion, the results of indicated that used of Nano-ZnO and wet feeding had no effect on performance parameters. Wet diet caused increased monocyte percent and 50 mg level Nano-ZnO to form dry caused increased height of villi.

Keywords: broiler, blood, gut, performance, nanoparticles

Procedia PDF Downloads 512

Authors: I. Yilmaz, O. Taga, F. Kosar, O. Keles

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In this study, friction and damping coefficients of folded cover mechanism were obtained in accordance with experimental studies and data. Friction and damping coefficients are the most important inputs to accomplish a mechanism analysis. Friction and damping are two objects that change the time of deployment of mechanisms and their dynamic behaviors. Though recommended friction coefficient values exist in literature, damping is differentiating feature according to mechanic systems. So the damping coefficient should be obtained from mechanism test outputs. In this study, the folded cover mechanism use torsion springs for deploying covers that are formerly close folded position. Torsion springs provide folded covers with desirable deploying time according to variable environmental conditions. To verify all design revisions with system tests will be so costly so that some decisions are taken in accordance with numerical methods. In this study, there are two folded covers required to deploy simultaneously. Scotch-yoke and crank-rod mechanisms were combined to deploy folded covers simultaneously. The mechanism was unlocked with a pyrotechnic bolt onto scotch-yoke disc. When pyrotechnic bolt was exploded, torsion springs provided rotational movement for mechanism. Quick motion camera was recording dynamic behaviors of system during deployment case. Dynamic model of mechanism was modeled as rigid body with Adams MBD (multi body dynamics) then torque values provided by torsion springs were used as an input. A well-advised range of friction and damping coefficients were defined in Adams DOE (design of experiment) then a large number of analyses were performed until deployment time of folded covers run in with test data observed in record of quick motion camera, thus the deployment time of mechanism and dynamic behaviors were obtained. Same mechanism was tested with different torsion springs and torque values then outputs were compared with numerical models. According to comparison, it was understood that friction and damping coefficients obtained in this study can be used safely when studying on folded objects required to deploy simultaneously. In addition to model generated with Adams as rigid body the finite element model of folded mechanism was generated with Abaqus then the outputs of rigid body model and finite element model was compared. Finally, the reasonable solutions were suggested about different outputs of these solution methods.

Keywords: damping, friction, pyro-technic, scotch-yoke

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Authors: Ellen Nhedzi Gozo

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Unavailability of adequate hydro-meteorological data has always limited the analysis and understanding of hydrological behaviour of several dam catchments including Mazowe Dam in Zimbabwe. The problem of insufficient data for Mazowe Dam catchment analysis was solved by extracting catchment characteristics and aerial hydro-meteorological data from ASTER, LANDSAT, Shuttle Radar Topographic Mission SRTM remote sensing (RS) images using ILWIS, ArcGIS and ERDAS Imagine geographic information systems (GIS) software. Available observed hydrological as well as meteorological data complemented the use of the remotely sensed information. Ground truth land cover was mapped using a Garmin Etrex global positioning system (GPS) system. This information was then used to validate land cover classification detail that was obtained from remote sensing images. A bathymetry survey was conducted using a SONAR system connected to GPS. Hydrological modelling using the HBV model was then performed to simulate the hydrological process of the catchment in an effort to verify the reliability of the derived parameters. The model output shows a high Nash-Sutcliffe Coefficient that is close to 1 indicating that the parameters derived from remote sensing and GIS can be applied with confidence in the analysis of Mazowe Dam catchment.

Keywords: geographic information systems, hydrological modelling, remote sensing, water resources management

Procedia PDF Downloads 313

Authors: Johan Buermans, Kristel Crombé, Niek Desmet, Laura Dittrich, Andrei Goriaev, Yurii Kovtun, Daniel López-Rodriguez, Sören Möller, Per Petersson, Maja Verstraeten

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The International Thermonuclear Experimental Reactor (ITER) will rely on three sources of external heating to produce and sustain a plasma; Neutral Beam Injection (NBI), Ion Cyclotron Resonance Heating (ICRH), and Electron Cyclotron Resonance Heating (ECRH). ECRH is a way to heat the electrons in a plasma by resonant absorption of electromagnetic waves. The energy of the electrons is transferred indirectly to the ions by collisions. The electron cyclotron heating system can be directed to deposit heat in particular regions in the plasma (https://www.iter.org/mach/Heating). Electron Cyclotron Resonance Heating (ECRH) at the fundamental resonance in X-mode is limited by a low cut-off density. Electromagnetic waves cannot propagate in the region between this cut-off and the Upper Hybrid Resonance (UHR) and cannot reach the Electron Cyclotron Resonance (ECR) position. Higher harmonic heating is hence preferred in heating scenarios nowadays to overcome this problem. Additional power deposition mechanisms can occur above this threshold to increase the plasma density. This includes collisional losses in the evanescent region, resonant power coupling at the UHR, tunneling of the X-wave with resonant coupling at the ECR, and conversion to the Electron Bernstein Wave (EBW) with resonant coupling at the ECR. A more profound knowledge of these deposition mechanisms can help determine the optimal plasma production scenarios. Several ECRH experiments are performed on the TOroidally MAgnetized System (TOMAS) to identify the conditions for Electron Bernstein Wave (EBW) heating. Density and temperature profiles are measured with movable Triple Langmuir Probes in the horizontal and vertical directions. Measurements of the forwarded and reflected power allow evaluation of the coupling efficiency. Optical emission spectroscopy and camera images also contribute to plasma characterization. The influence of the injected power, magnetic field, gas pressure, and wave polarization on the different deposition mechanisms is studied, and the contribution of the Electron Bernstein Wave is evaluated. The TOMATOR 1D hydrogen-helium plasma simulator numerically describes the evolution of current less magnetized Radio Frequency plasmas in a tokamak based on Braginskii’s legal continuity and heat balance equations. This code was initially benchmarked with experimental data from TCV to determine the transport coefficients. The code is used to model the plasma parameters and the power deposition profiles. The modeling is compared with the data from the experiments.

Keywords: electron Bernstein wave, Langmuir probe, plasma characterization, TOMAS

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Authors: Selifontova Darya Yurievna

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The study of the process of the emergence and evolution of socio-cultural ideas about the "Asian states" in the context of the development of US cinema in 1941-1945 will contribute both to the approbation of a new approach to the classical subject and will allow using the methodological tools of history, political science, philology, sociology for understanding modern military-political, historical, ideological, socio-cultural processes on a concrete example. This is especially important for understanding the process of constructing the image of the Japanese Empire in the USA. Assessments and images of China and Japan in World War II, created in American cinema, had an immediate impact on the media, public sentiment, and opinions. During the war, the US cinema created new myths and actively exploited old ones, combining them with traditional Hollywood cliches - all this served as a basis for creating the image of China and the Japanese Empire on the screen, which were necessary to solve many foreign policy and domestic political tasks related to the construction of two completely different, but at the same time, similar images of Asia (China and the Japanese Empire). In modern studies devoted to the history of wars, the study of the specifics of the information confrontation of the parties is in demand. A special role in this confrontation is played by propaganda through cinema, which uses images, historical symbols, and stable metaphors, the appeal to which can form a certain public reaction. Soviet documentaries of the war years are proof of this. The relevance of the topic is due to the fact that cinema as a means of propaganda was very popular and in demand during the Second World War. This period was the time of creation of real masterpieces in the field of propaganda films, in the documentary space of the cinema of 1941 – 1945. The traditions of depicting the Second World War were laid down. The study of the peculiarities of visualization and mythologization of the Second World War in Soviet cinema is the most important stage for studying the development of the specifics of propaganda methods since the methods and techniques of depicting the war formed in 1941-1945 are also significant at the present stage of the study of society.

Keywords: asian countries, politics, sociology, domestic politics, USA, cinema

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Authors: Mateusz Szul, Tomasz Iluk, Aleksander Sobolewski

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Small-scale, distributed energy systems enabling cogeneration of heat and power based on gasification of sewage sludge, are considered as the most efficient and environmentally friendly ways of their treatment. However, economic aspects of such an investment are very demanding; therefore, for such a small scale sewage sludge gasification installation to be profitable, it needs to be efficient and simple at the same time. The article presents results of research on air gasification of sewage sludge in fixed bed GazEla reactor. Two of the most important aspects of the research considered the influence of the composition of sewage sludge blends with other feedstocks on properties of generated syngas and ash sintering problems occurring at the fixed bed. Different means of the fuel pretreatment and blending were proposed as a way of dealing with the above mentioned undesired characteristics. Influence of RDF (Refuse Derived Fuel) and biomasses in the fuel blends were evaluated. Ash properties were assessed based on proximate, ultimate, and ash composition analysis of the feedstock. The blends were specified based on complementary characteristics of such criteria as C content, moisture, volatile matter, Si, Al, Mg, and content of basic metals in the ash were analyzed, Obtained results were assessed with use of experimental gasification tests and laboratory ISO-procedure for analysis of ash characteristic melting temperatures. Optimal gasification process conditions were determined by energetic parameters of the generated syngas, its content of tars and lack of ash sinters within the reactor bed. Optimal results were obtained for co-gasification of herbaceous biomasses with sewage sludge where LHV (Lower Heating Value) of the obtained syngas reached a stable value of 4.0 MJ/Nm3 for air/steam gasification.

Keywords: ash fusibility, gasification, piston engine, sewage sludge

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Authors: Constance Kirker

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While there is general agreement that food itself can be beautiful, thousands of still-life masterpieces over the years attest to this, depicting the act of eating, actually placing food in one’s mouth and chewing is seemingly taboo. The environment created around consumption -dining rooms, linens, china, flowers- is consciously choreographed to provide a pleasing aesthetic experience. Yet artists, from Roman frescoes painters to contemporary photographers, create images from feasts to solitary subjects that rarely show food or drink touching lips, chewing, or swallowing. Of the countless paintings of the Last Supper, the food remains on the table. Rarely is Adam or Eve shown taking a bite of the apple, initiating Original Sin. In the few examples that do depict food-in-mouth, Goya’s Saturn Devouring His Son, or the ubiquitous photos of the “wedding smash” with brides and grooms pushing wedding cake into each other’s mouths, the images are seemingly intended to be particularly ugly or humorous in a distasteful way. This paper will explore theories that include the rules of etiquette, some determined hundreds of years ago and still followed today, that imply eating is a metaphor for gluttony, implicit sexuality of eating, the distortion of the face while eating and the simple practicality of the difficulty of an artist’s model maintaining a chewing position. If art is a reflection of society, what drives the universal impulse to hide this very human function?

Keywords: aesthetics, senses, taboo, consumption

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Authors: Catherine Wheatley, Emma L. Davies, Helen Dawes

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The health benefits of exercise are widely recognised, but numerous interventions have failed to halt a sharp decline in physical activity during early adolescence. Many such projects are underpinned by the Theory of Planned Behaviour, yet this model of rational decision-making leaves variance in behavior unexplained. This study investigated whether the Prototype Willingness Model, which proposes a second, reactive decision-making path to account for spontaneous responses to the social environment, has potential to improve understanding of adolescent exercise behaviour in school by exploring constructs in the model with young people. PE teachers in 4 Oxfordshire schools each nominated 6 pupils who were active in school, and 6 who were inactive, to participate in the study. Of these, 45 (22 male) aged 12-13 took part in 8 focus group discussions. These were transcribed and subjected to deductive thematic analysis to search for themes relating to the prototype willingness model. Participants appeared to make rational decisions about commuting to school or attending sports clubs, but spontaneous choices to be inactive during both break and PE. These reactive decisions seemed influenced by a social context described as more ‘judgmental’ than primary school, characterised by anxiety about physical competence, negative peer evaluation and inactive playground norms. Participants described their images of typical active and inactive adolescents: active images included negative social characteristics including ‘show-off’. There was little concern about the long-term risks of inactivity, although participants seemed to recognise that physical activity is healthy. The Prototype Willingness Model might more fully explain young adolescents’ physical activity in school than rational behavioural models, indicating potential for physical activity interventions that target social anxieties in response to the changing playground environment. Images of active types could be more complex than earlier research has suggested, and their negative characteristics might influence willingness to be active.

Keywords: adolescence, physical activity, prototype willingness model, school

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Authors: Alena Radina

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On the global stage, national image is shaped by historical memory of wars and alliances, government ideology and particularly media stereotypes which represent countries in positive or negative ways. News magazine covers are a key site for national representation. The object of analysis in this paper is the portrayals of the US, Germany, China, and Russia in the front pages and cover stories of “Time”, “Der Spiegel”, “Beijing Review”, and “Expert”. Political comedy helps people learn about current affairs even if politics is not their area of interest, and thus satire indirectly sets the public agenda. Coupled with satirical messages, cover images and the linguistic messages embedded in the covers become persuasive visual and verbal factors, known to drive about 80% of magazine sales. Preliminary analysis identified satirical elements in magazine covers, which are known to influence and frame understandings and attract younger audiences. Multimodal and transnational comparative framing analyses lay the groundwork to investigate why journalists, editors and designers deploy certain frames rather than others. This research investigates to what degree frames used in covers correlate with frames within the cover stories and what these framings can tell us about media professionals’ representations of their own and other nations. The study sample includes 32 covers consisting of two covers representing each of the four chosen countries from the four magazines. The sampling framework considers two time periods to compare countries’ representation with two different presidents, and between men and women when present. The countries selected for analysis represent each category of the international news flows model: the core nations are the US and Germany; China is a semi-peripheral country; and Russia is peripheral. Examining textual and visual design elements on the covers and images in the cover stories reveals not only what editors believe visually attracts the reader’s attention to the magazine but also how the magazines frame and construct national images and national leaders. The cover is the most powerful editorial and design page in a magazine because images incorporate less intrusive framing tools. Thus, covers require less cognitive effort of audiences who may therefore be more likely to accept the visual frame without question. Analysis of design and linguistic elements in magazine covers helps to understand how media outlets shape their audience’s perceptions and how magazines frame global issues. While previous multimodal research of covers has focused mostly on lifestyle magazines or newspapers, this paper examines the power of current affairs magazines’ covers to shape audience perception of national image.

Keywords: framing analysis, magazine covers, multimodality, national image, satire

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Authors: Piotr Tylec, Julia Wierzbicka, Natalia Gajewska, Krzysztof Przeczek, Grzegorz Torbicz, Alicja Dudek, Magdalena Pisarska-Adamczyk, Mateusz Wierdak, Michal Pedziwiatr

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Introduction: Many patients have described changes in taste perception after weight loss surgery. However, little data is available about short term changes in taste after surgery. Aim: We aimed to evaluate short-term changes in taste preference after bariatric surgeries in comparison to colorectal surgeries. Material and Methods: Between April 2018 and April 2019, a total of 121 bariatric patients and 63 controls participated. Bariatric patients underwent laparoscopic sleeve gastrectomy or Roux-en-Y gastric by-pass. Controls underwent oncological colorectal surgeries. Patients who developed clinical complications requiring restriction of oral intake after surgery or withdraw their consent were excluded from the study. In the end, 85 bariatric patients and 44 controls were included. In all of them, the 16-item ERAS Protocol was applied. Using 10-points Numeric Rating Scale (1-10) patients completed questionnaire and rated their appetite and thirst (1 - no appetite/not thirsty, 10 – normal appetite/very thirsty) and flavoured standardized liquids' taste (1- horrible, 10-very tasty) and food images for the 6 group of taste (sweet, umami, sour, spicy, bitter and salty) (1 - not appetizing, 10 - very appetizing) preoperatively and on the first postoperative day. Data were analysed with Statistica 13.0 PL. Results: Analysed group consist of 129 patients (85 bariatric, 44 controls). Mean age and BMI in a research group was 44.91 years old, 46.22 kg/m² and in control group 62.09 years old, 25.87 kg/m², respectively. Our analysis revealed significant differences in changes of appetite between both groups (research: -4.55 ± 3.76 vs. control: -0.85 ± 4.37; p < 0.05), ratings bitter (research: 0.60 ± 2.98 vs. control: -0.88 ± 2.58; p < 0.05) and salty (research: 1.20 ± 3.50 vs. control: -0.52 ± 2.90; p < 0.05) flavoured liquids and ratings for sweet (research: 1.62 ± 3.31 vs. control: 0.01 ± 2.63; p < 0.05) and bitter (research: 1.21 ± 3.15 vs. control: -0.09 ± 2.25; p < 0.05) food images. There were statistically significant results in the ratings of other images, but in comparison to the control group, they were not statistically significant. Conclusion: The study showed that bariatric surgeries quickly decreases appetite and desire to eat certain types of food, such as salty. Moreover, the bitter taste was more desirable in the research group in comparison to control group. Nevertheless, the sweet taste was more appetible in the bariatric group than in control.

Keywords: bariatric surgery, general surgery, obesity, taste preference

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Authors: Nan Deng, Zhenqiu Liu

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Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

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Authors: Kristina Sakalauskiene, Renaldas Raisutis, Gintare Linkeviciute, Skaidra Valiukeviciene

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Cutaneous melanoma is a melanocytic skin tumour, which has a very poor prognosis while is highly resistant to treatment and tends to metastasize. Thickness of melanoma is one of the most important biomarker for stage of disease, prognosis and surgery planning. In this study, we hypothesized that the automatic analysis of spectrophotometric images and high-frequency ultrasonic 2D data can improve differential diagnosis of cutaneous melanoma and provide additional information about tumour penetration depth. This paper presents the novel complex automatic system for non-invasive melanocytic skin tumour differential diagnosis and penetration depth evaluation. The system is composed of region of interest segmentation in spectrophotometric images and high-frequency ultrasound data, quantitative parameter evaluation, informative feature extraction and classification with linear regression classifier. The segmentation of melanocytic skin tumour region in ultrasound image is based on parametric integrated backscattering coefficient calculation. The segmentation of optical image is based on Otsu thresholding. In total 29 quantitative tissue characterization parameters were evaluated by using ultrasound data (11 acoustical, 4 shape and 15 textural parameters) and 55 quantitative features of dermatoscopic and spectrophotometric images (using total melanin, dermal melanin, blood and collagen SIAgraphs acquired using spectrophotometric imaging device SIAscope). In total 102 melanocytic skin lesions (including 43 cutaneous melanomas) were examined by using SIAscope and ultrasound system with 22 MHz center frequency single element transducer. The diagnosis and Breslow thickness (pT) of each MST were evaluated during routine histological examination after excision and used as a reference. The results of this study have shown that automatic analysis of spectrophotometric and high frequency ultrasound data can improve non-invasive classification accuracy of early-stage cutaneous melanoma and provide supplementary information about tumour penetration depth.

Keywords: cutaneous melanoma, differential diagnosis, high-frequency ultrasound, melanocytic skin tumours, spectrophotometric imaging

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Hesti Ghassani, Tessa Septiadi

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In the world we live on today, young generation highly influences the future of a nation. We have to concern that the condition of the country in 20 years later depending by the character of young adults these days. Therefore, it is important that we have to support and control the teenagers especially in one of developing countries in which I live in: Indonesia. Indonesia is a home to 240 million people. It diverse in languages, cultures, as well as attitudes. The differences among each individual lead us to think that there is something we have to take care of. It is necessary to pay attention to the nutrition consumed by the nation. We initiate to control the food consumed by young generation as early as a primary students. Nutrition affects the immune of the body, neuron system, and, most importantly brain. One of the nutrition that has to be fulfilled is milk. However, most of the population in Indonesia isn’t aware of the importance of consuming milk as their daily basis. We’ve formed an innovation called the Brilliant Candy which is affordable and rich in nutrition. So that is why the paper made by literature study to solve the problem with effective ways using available resources, practice and cheap. Brilliant Candy consists of Centella asiatica extract mixed with Soy milk. Centella asiatica contains of alkaloid which give the energy to brain and circulate oxygen. Based on the research of Sathya and Ganga, Centella asiatica can increase the intelligence. Indeed, Centella asiatica can relieve stress, and help us in staying focus. Soy milk is a kind of milk which come from extracted soybean. Soybean is rich in flafonoid. It has various advantages for our body. Which can also support child nutrition consumed. Soybean boosts immune system, helps digestive system, and in terms of food, soy bean exists as a source of nutrition. A method to get extraction of Centella asiatica is namely maserasi using ethanol. While making soybean milk with got the pollen of soybean. Both materials get mixed processed into hard candy with congelation of.

Keywords: Indonesia, Centella asiatica, Soy milk, alkaloid, flafonoid

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Authors: Geraldine Ambe

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Cameroon is a country in a country in Central Africa. Before the first World War, Germany colonized Cameroon, including some parts of Gabon, Chad, Nigeria, and the Central African Republic. After the war, the United Nations divided most of the colony into Britain and France. In 1960, Eastern Cameroon (‘La Republique du Cameroon’) gained its independence from France while British Southern Cameroons obtained its independence from Britain. The two entities agreed to live together as a federal state officially called the Federal Republic of Cameroon. In 1962, the name of the name of the country was changed from the Federal Republic of Cameroon to the United Republic of Cameroon, while the Prime Minister of Western Cameroon was moved to Yaounde. In 1984, President Paul Biya singlehandedly changed the name to the Republic of Cameroon, implying that Southern Cameroon is not recognized in the union again. From the words of Am Cohen, the two territories came together to form a federal government with one currency, one army, and one foreign policy like states in the United States of America. However, the name Republic of Cameroon (‘La Republique du Cameroun’) does not recognize BSC, and this is exactly what has been practiced: politics of exclusion and excessive centralization in Yaounde. In 2016, teachers and Lawyers started strikes to call the attention of the government on the inhalation of the English culture/people. They were greeted with guns, causing the radicalization of the youths. The civil society came together to form a union to address the issues facing the people, and the government took their leaders and sentenced them to live imprisonment. The consequence was a civil war with nobody to dialogue with. Out of Cameroon, more than half a million people from BSC have been taking dangerous trips through the air, land, and sea. In the jungles and the deserts, the snow of Europe, these people have been seen for the last 4 years. This paper will present some personalities, political fractions, and their stands of decentralization, federalism, and independence as the war continues. The paper will further look at the consequence of this crisis on migration in Central and Eastern Europe.

Keywords: British Southern Cameroons, decolonization, Second World War, dialogue, civil war, immigration

Procedia PDF Downloads 188