Search results for: fixed live camera images

Authors: Carl van Walraven, Meltem Tuna

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Background: Network meta-analysis (NMA) quantifies the relative efficacy of 3 or more interventions from studies containing a subgroup of interventions. This study applied the analytical approach of NMA to quantify the relative accuracy of prediction models with distinct inclusion criteria that are evaluated on a common population (‘concurrent external validation’). Methods: We simulated binary events in 5000 patients using a known risk function. We biased the risk function and modified its precision by pre-specified amounts to create 15 prediction models with varying accuracy and distinct patient applicability. Prediction model accuracy was measured using the Scaled Brier Score (SBS). Overall prediction model accuracy was measured using fixed-effects methods that accounted for model applicability patterns. Prediction model accuracy was summarized as the Network Relative Model Accuracy (NeRMA) Score which ranges from -∞ through 0 (accuracy of random guessing) to 1 (accuracy of most accurate model in concurrent external validation). Results: The unbiased prediction model had the highest SBS. The NeRMA score correctly ranked all simulated prediction models by the extent of bias from the known risk function. A SAS macro and R-function was created to implement the NeRMA Score. Conclusions: The NeRMA Score makes it possible to quantify the accuracy of binomial prediction models having distinct inclusion criteria in a concurrent external validation.

Keywords: prediction model accuracy, scaled brier score, fixed effects methods, concurrent external validation

Procedia PDF Downloads 236

Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots

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Authors: Aynur Bütün Ayhan, Utku Beyazıt

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Adolescents can be heavily influenced by social media content as they develop their identities and body images. Therefore, the intensive use of social media platforms may have important effects on their body image beliefs. In this context, the objective of the present study was to assess the relationship between adolescents' social media use and their body image concerns. The study included 265 adolescents (133 girls and 132 boys) between the ages of 15 and 17 who were attending a high school in Ankara, Türkiye. In the study, the adolescents were administered the Social Media Addiction Scale to assess their level of social media use and the Social Appearance Anxiety Scale to assess their social appearance anxiety. Prior to analysis, a normality test was applied, and it was determined that the data displayed a non-parametric distribution. As a result, a significant positive relationship (r=.322, p<.01) was found between adolescents' level of social use and social appearance anxiety. It was also determined that social media addiction and social appearance anxiety significantly differed (p<.05) according to adolescents' opinions about their own bodies, being influenced by body images they see on social media and weight perceptions. The findings suggest that social media use should be managed carefully for adolescents to develop a healthy body image.

Keywords: social media, adolescent, social appearence, anxiety

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Authors: Temenuzhka Spasova, Nadya Yanakieva

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Snow modulates the hydrological cycle and influences the functioning of ecosystems and is a significant resource for many populations whose water is harvested from cold regions. Snow observations are important for validating climate models. The accumulation and rapid melt of snow are two of the most dynamical seasonal environmental changes on the Earth’s surface. The actuality of this research is related to the modern tendencies of the remote sensing application in the solution of problems of different nature in the ecological monitoring of the environment. The subject of the study is the dynamic during the different seasons on Livingstone Island, South Shetland Islands in Antarctica and on Svalbard in Arctic. The objects were analyzed and mapped according to the Еuropean Space Agency data (ESA), acquired by sensors Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel 2 MSI and GIS. Results have been obtained for changes in snow coverage during the summer-winter transition and its dynamics in the two hemispheres. The data used is of high time-spatial resolution, which is an advantage when looking at the snow cover. The MSI images are with different spatial resolution at the Earth surface range. The changes of the environmental objects are shown with the SAR images and different processing approaches. The results clearly show that snow and snow melting can be best registered by using SAR data via hh- horizontal polarization. The effect of the researcher on aerospace data and technology enables us to obtain different digital models, structuring and analyzing results excluding the subjective factor. Because of the large extent of terrestrial snow coverage and the difficulties in obtaining ground measurements over cold regions, remote sensing and GIS represent an important tool for studying snow areas and properties from regional to global scales.

Keywords: climate changes, GIS, remote sensing, SAR images, snow coverage

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Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

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Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

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Authors: Masashi Kanazawa, Takaaki Nakano, Masaaki Takemoto, Tomonori Imamura, Mamiko Sugimura, Toshitaka Ito

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Introduction: We experienced a massive disaster due to inhalation of water-soluble paint. Sixteen patients were brought to our emergency room, and pulmonary edema was revealed on the CT images of 12 cases. Purpose: Transition of chest CT-scan findings in cases with pulmonary edema was examined. Method: CT-scans were performed on the 1st, 2nd, 5th, and 19th days after the inhalation event. Patients whose pulmonary edema showed amelioration or exacerbation were classified into the improvement or the exacerbation group, respectively. Those with lung edema findings appearing at different sites after the second day were classified into the changing group. Results: Eight, one and three patients were in the improvement, exacerbation and changing groups, respectively. In all cases, the pulmonary edema had disappeared from CT images on the 19th day after the inhalation event. Conclusion: Inhalation of water-soluble paints is considered to be relatively safe. However, our observations in these emergency cases suggest that, even if pulmonary edema is not severe immediately after the exposure, new lesions may appear later and existing lesions may worsen. Follow-up imaging is thus necessary for about two weeks.

Keywords: CT scan, intoxication, pulmonary edema, water-soluble paint

Procedia PDF Downloads 173

Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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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: Bashir Ahmad Amiri, Nsenda Lukumwena

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The global trend indicates that more and more people live and will continue to live in urban areas. Today cities are expanding both in physical size and number due to the rapid population growth along with sprawl development, which caused the cities to expand beyond the growth boundary and exerting intense pressure on environmental resources specially farmlands to accommodate new housing and urban facilities. Also noticeable is the increase in urban decay along with the increase of slum dwellers present another challenge that most cities in developed and developing countries have to deal with. Today urban practitioners, researchers, planners, and decision-makers are seeking for alternative development and growth management policies to house the rising urban population and also cure the urban decay and slum issues turn to Smart Growth to achieve their goals. Many cities across the globe have adopted smart growth as an alternative growth management tool to deal with patterns and forms of development and to cure the rising urban and environmental problems. The method used in this study is a literature analysis method through reviewing various resources to highlight the potential benefits of Smart Growth in both developed and developing countries and analyze, to what extent it can be a strategic alternative for Afghanistan’s cities, especially the capital city. Hence a comparative analysis is carried on three countries, namely the USA, China, and India to identify the potential benefits of smart growth likely to serve as an achievable broad base for recommendations in different urban contexts.

Keywords: growth management, housing, Kabul city, smart growth, urban-expansion

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Authors: Harsh Vikram Singh, Ankur Rai, Anand Mohan

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In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image.

Keywords: data hiding, watermarking, DCT, chaotic sequence, arnold transforms

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Authors: Riikka Elina Kallio

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“The walls have ears” phrase is defining the era of dictatorship in Portugal (1926–1974) and political unrest decades in Finland (1917–1948). The phrase is referring to the policing of the political, secret police, PIDE (Policia Internacional e de Defesa do Estado 1933–1969) in Portugal and VALPO (Valtiollinen Poliisi 1939–1948) in Finland. Free speech at any public space and even in private events could be fatal. The members of the PIDE/VALPO or informers/collaborators could be listening. Strict censorship under the Salazar´s regime was controlling media for example newspapers, music, and the film industry. Similarly, the politically affected censorship influenced the media in Finland in those unrest decades. This article examines the similarities and the differences in the images of the political police in Finland and Portugal, by analyzing Finnish and Portuguese films from the nineteen-thirties to nineteensixties. The text addresses two main research questions: what are the common and different features in the representations of the Finnish and Portuguese political police in films between the 1930s and 1960s, and how did the national censorship affect these representations? This study approach is interdisciplinary, and it combines film studies and criminology. Close reading is a practical qualitative method for analyzing films and in this study, close reading emphasizes the features of the police officer. Criminology provides the methodological tools for analysis of the police universal features and European common policies. The characterization of the police in this study is based on Robert Reiner´s 1980s and Timo Korander´s 2010s definitions of the police officer. The research material consisted of the Portuguese films from online film archives and Finnish films from Movie Making Finland -project´s metadata which offered suitable material by data mining the keywords such as poliisi, poliisipäällikkö and konstaapeli (police, police chief, police constable). The findings of this study suggest that even though there are common features of the images of the political police in Finland and Portugal, there are still national and cultural differences in the representations of the political police and policing.

Keywords: censorship, film studies, images, PIDE, political police, VALPO

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Authors: Mona Elhelbawy, Mac Gray

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Traditional wired endoscopy is an intrusive process that requires a long flexible tube to be inserted through the patient’s mouth while intravenously sedated. Only images of the upper 4 feet of stomach, colon, and rectum can be captured, leaving the remaining 20 feet of small intestines. Wireless capsule endoscopy offers a painless, non-intrusive, efficient and effective alternative to traditional endoscopy. In wireless capsule endoscopy (WCE), ingestible vitamin-pill-shaped capsules with imaging capabilities, sensors, batteries, and antennas are designed to send images of the gastrointestinal (GI) tract in real time. In this paper, we investigate the radiation performance and specific absorption rate (SAR) of a miniature conformal capsule antenna operating at the Medical Implant Communication Service (MICS) frequency band in the human body. We perform numerical simulations using the finite element method based commercial software, high-frequency structure simulator (HFSS) and the ANSYS human body model (HBM). We also investigate the in-body channel characteristics between the implantable capsule and an external antenna placed on the surface of the human body.

Keywords: IEEE 802.15.6, MICS, SAR, WCE

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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: Arun C. O., Shrijith M. B., Thakur Rajesh Singh

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The study aims to analyze and understand the biomechanical stability of the atlantoaxial complex under different posterior fixation techniques using the finite element method in the Indian context. The conventional cadaveric studies performed show heterogeneity in biomechanical properties. The finite element method being a versatile numerical tool, is being wisely used for biomechanics analysis of atlantoaxial complex. However, the biomechanics of posterior fixation techniques for an Indian subject is missing in the literature. It is essential to study in this context as the bone density and geometry of vertebrae vary from region to region, thereby requiring different screw lengths and it can affect the range of motion(ROM), stresses generated. The current study uses CT images for developing a 3D finite element model with C1-C2 geometry without ligaments. Instrumentation is added to this geometry to develop four models for four fixation techniques, namely C1-C2 TA, C1LM-C2PS, C1LM-C2Pars, C1LM-C2TL. To simulate Flexion, extension, lateral bending, axial rotation, 1.5 Nm is applied to C1 while the bottom nodes of C2 are fixed. Then Range of Motion (ROM) is compared with the unstable model(without ligaments). All the fixation techniques showed more than 97 percent reduction in the Range of Motion. The von-mises stresses developed in the screw constructs are obtained. From the studies, it is observed that Transarticular technique is most stable in Lateral Bending, C1LM-C2 Translaminar is found most stable in Flexion/extension. The Von-Mises stresses developed minimum in Trasarticular technique in lateral bending and axial rotation, whereas stress developed in C2 pars construct minimum in Flexion/ Extension. On average, the TA technique is stable in all motions and also stresses in constructs are less in TA. Tarnsarticular technique is found to be the best fixation technique for Indian subjects among the 4 methods.

Keywords: biomechanics, cervical spine, finite element model, posterior fixation

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Authors: Luan Trong Nguyen, M. Azizur Rahman, Yusuke Tamenori, Toshihiro Yoshimura, Nozomu Iwasaki, Hiroshi Hasegawa

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This study investigated the distribution of magnesium (Mg), phosphorus (P), sulfur (S) and strontium (Sr) using micro X-ray fluorescence (µ-XRF) along the annual growth rings in the skeleton of Japanese red coral Paracorallium japonicum. The Mg, P and S distribution in µ-XRF mapping images correspond to the dark and light bands along the annual growth rings observed in microscopic images of the coral skeleton. The µ-XRF mapping data showed a positive correlation (r = 0.6) between P and S distribution in the coral skeleton. A contrasting distribution pattern of S and Mg along the axial skeleton of P. japonicum indicates a weak negative correlation (r = -0.2) between these two trace elements. The distribution pattern of S, P and Mg reveals linkage between their distributions and the formation of dark/light bands along the annual growth rings in the axial skeleton of P. japonicum. Sulfur and P were distributed in the organic matrix rich dark bands, while Mg was distributed in the light bands of the annual growth rings.

Keywords: µ-XRF, trace element, precious coral, Paracorallium japonicum

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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Authors: Ali Ben Abbes, Imed Riadh Farah

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Due to the considerable advances in Multi-Temporal Satellite Images (MTSI), remote sensing application became more accurate. Recently, many advances in modeling MTSI are developed using various models. The purpose of this article is to present an overview of studies using Hidden Markov Model (HMM). First of all, we provide a background of using HMM and their applications in this context. A comparison of the different works is discussed, and possible areas and challenges are highlighted. Secondly, we discussed the difference on vegetation monitoring as well as urban growth. Nevertheless, most research efforts have been used only stationary data. From another point of view, in this paper, we describe a new non-stationarity HMM, that is defined with a set of parts of the time series e.g. seasonal, trend and random. In addition, a new approach giving more accurate results and improve the applicability of the HMM in modeling a non-stationary data series. In order to assess the performance of the HMM, different experiments are carried out using Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI time series of the northwestern region of Tunisia and Landsat time series of tres Cantos-Madrid in Spain.

Keywords: multi-temporal satellite image, HMM , nonstationarity, vegetation, urban

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Authors: Özgür Öztürk, Cumhur Sipahi, Hande Yeşil

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Implant retained restorations commonly consist of a metal-framework veneered with ceramic or composite facings. The increasing and expanding use of indirect resin composites in dentistry is a result of innovations in materials and processing techniques. Of special interest to the implant restorative field is the possibility that composites present significantly lower peak vertical and transverse forces transmitted at the peri-implant level compared to metal-ceramic supra structures in implant-supported restorations. A 43-year-old male patient referred to the department of prosthodontics for an implant retained fixed prosthesis. The clinical and radiographic examination of the patient demonstrated the presence of an implant in the right mandibular first molar tooth region. A considerable amount of marginal bone loss around the implant was detected in radiographic examinations combined with a remarkable peri-implant soft tissue deficiency. To minimize the chewing loads transmitted to the implant-bone interface it was decided to fabricate an indirect composite resin veneered single metal crown over a screw-retained abutment. At the end of the treatment, the functional and aesthetic deficiencies were fully compensated. After a 6 months clinical and radiographic follow-up period the not any additional pathologic invasion was detected in the implant-bone interface and implant retained restoration did not reveal any vehement complication.

Keywords: dental implant, fixed partial dentures, indirect composite resin, peri-implant defects

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Authors: Daniel R. dos Santos, Mateus S. Maldonado, Estevão J. R. Batista

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The military commanders increasingly dependent on spatial awareness, as knowing where enemy are, understanding how war battle scenarios change over time, and visualizing these trends in ways that offer insights for decision-making. Thanks to advancements in geospatial technologies and artificial intelligence algorithms, the commanders are now able to modernize military operations on a universal scale. Thus, geovisualisation has become an essential asset in the defense sector. It has become indispensable for better decisionmaking in dynamic/temporal scenarios, operation planning and management for the war field, situational awareness, effective planning, monitoring, and others. For example, a 3D visualization of war field data contributes to intelligence analysis, evaluation of postmission outcomes, and creation of predictive models to enhance decision-making and strategic planning capabilities. However, old-school visualization methods are slow, expensive, and unscalable. Despite modern technologies in generating 3D point clouds, such as LIDAR and stereo sensors, monocular depth values based on deep learning can offer a faster and more detailed view of the environment, transforming single images into visual information for valuable insights. We propose a dedicated monocular depth reconstruction approach via deep learning techniques for 3D geovisualisation of satellite images. It introduces scalability in terrain reconstruction and data visualization. First, a dataset with more than 7,000 satellite images and associated digital elevation model (DEM) is created. It is based on high resolution optical and radar imageries collected from Planet and Copernicus, on which we fuse highresolution topographic data obtained using technologies such as LiDAR and the associated geographic coordinates. Second, we developed an imagery-DEM fusion strategy that combine feature maps from two encoder-decoder networks. One network is trained with radar and optical bands, while the other is trained with DEM features to compute dense 3D depth. Finally, we constructed a benchmark with sparse depth annotations to facilitate future research. To demonstrate the proposed method's versatility, we evaluated its performance on no annotated satellite images and implemented an enclosed environment useful for Geovisualisation applications. The algorithms were developed in Python 3.0, employing open-source computing libraries, i.e., Open3D, TensorFlow, and Pythorch3D. The proposed method provides fast and accurate decision-making with GIS for localization of troops, position of the enemy, terrain and climate conditions. This analysis enhances situational consciousness, enabling commanders to fine-tune the strategies and distribute the resources proficiently.

Keywords: depth, deep learning, geovisualisation, satellite images

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Authors: Ahmed Amin Mousa, Tamer M. Ismail, M. Abd El Salam

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This work presents a robot called Conceptual Robotic Cube, CR-Cube. The robot can be used as an educational tool for children from the age of three. It has a cube shape attached with a camera colours sensor. In addition, it contains four wheels to move smoothly. The researchers prepared a questionnaire to measure the efficiency of the robot. The design and the questionnaire was presented to 11 experts who agreed that the robot is appropriate for learning numbering and colours for preschool children.

Keywords: CR-Cube, robotic cube, conceptual robot, conceptual cube, colour concept, early childhood education

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Desta Brhanu Gebrehiwot

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The purpose of this review was to analyze the overall or combined effect of scholarly studies conducted on the impacts of Food for work (FFW) and Productive Safety Net Program (PSNP) on farm households’ livelihood (agricultural investment on the adoption of fertilizer, food security, livestock holding, nutrition and its’ disincentive effect) in Ethiopia. In addition, to make a critical assessment of the internal and external validity of the existing studies, the review also indicates the possibility to redesign the program. The method of selecting eligible studies for review was PICOS (Participants, Intervention, Comparison, Outcomes, and Settings) framework. The method of analysis was the fixed effects model under Meta-Analysis. The findings of this systematic review confirm the overall or combined positive significant impact of PSNP on fertilizer adoption (combined point estimate=0.015, standard error=0.005, variance=0.000, lower limit 0.004 up to the upper limit=0.026, z-value=2.726, and p-value=0.006). And the program had a significant positive impact on the child nutrition of rural households and had no significant disincentive effect. However, the program had no significant impact on livestock holdings. Thus, PSNP is important for households whose livelihood depends on rain-fed agriculture and are exposed to rainfall shocks. Thus, better to integrate the program into the national agricultural policy. In addition, most of the studies suggested that PSNP needs more attention to the design and targeting issued in order to be effective and efficient in social protection.

Keywords: meta-analysis, fixed effect model, PSNP, rural-livelihood, Ethiopia

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Authors: Sila K. Sari, Betty J.L. Laglbauer, Muhammad G. Salim, Irianies C. Gozali, Iqbal Herwata, Fahmi Fahmi, Selvia Oktaviyani, Isabel Ender, Sarah Lewis, Abraham Sianipar, Mark Erdmann

Abstract:

Taking strides towards the sustainable use of marine stocks requires science-based management of target fish populations and reduction of bycatch in non-selective fisheries. Among elasmobranchs, mobulid rays are faced with high extinction risk due to intrinsic vulnerability to fishing and their conservation has been recognized as a strong priority both in Indonesia and worldwide. Despite their common vulnerabilities to fishing pressure due to slow growth, late maturation and low fecundity, only manta rays, but not devil rays, are protected in Indonesian waters. However, both manta and devil rays are captured in non-selective fisheries, in particular drift gillnets, since their habitat overlaps with fishing grounds for primary target species (e.g. marlin, swordfish and bullet tuna off the coast of Muncar). For this reason, mobulid populations are being heavily impacted, and while national-level protections are crucial to help conservation, they may not suffice alone to insure populations sustainability. In order to assess the potential of applying live-release management measures to conserve mobulids captured as bycatch in drift gillnets, we deployed pop-up survival archival transmitters to assess post-release mortality in Indonesian mobulid rays. We also assessed which fishing practices, in particular, soak duration, affected post-release mortality in order to draw relevant conclusions for management.

Keywords: Mobulid, Devil ray, Manta ray, Bycatch

Procedia PDF Downloads 172

Authors: Saifalarab A. Mohmmed, Morgana E. Vianna, Jonathan C. Knowles

Abstract:

The issue of apical periodontitis has received considerable critical attention. Bacteria is integrated into communities, attached to surfaces and consequently form biofilm. The biofilm structure provides bacteria with a series protection skills against, antimicrobial agents and enhances pathogenicity (e.g. apical periodontitis). Sodium hypochlorite (NaOCl) has become the irrigant of choice for elimination of bacteria from the root canal system based on its antimicrobial findings. The aim of the study was to investigate the effect of different agitation techniques on the efficacy of 2.5% NaOCl to eliminate the biofilm from the surface of the lateral canal using the residual biofilm, and removal rate of biofilm as outcome measures. The effect of canal complexity (lateral canal) on the efficacy of the irrigation procedure was also assessed. Forty root canal models (n = 10 per group) were manufactured using 3D printing and resin materials. Each model consisted of two halves of an 18 mm length root canal with apical size 30 and taper 0.06, and a lateral canal of 3 mm length, 0.3 mm diameter located at 3 mm from the apical terminus. E. faecalis biofilms were grown on the apical 3 mm and lateral canal of the models for 10 days in Brain Heart Infusion broth. Biofilms were stained using crystal violet for visualisation. The model halves were reassembled, attached to an apparatus and tested under a fluorescence microscope. Syringe and needle irrigation protocol was performed using 9 mL of 2.5% NaOCl irrigant for 60 seconds. The irrigant was either left stagnant in the canal or activated for 30 seconds using manual (gutta-percha), sonic and ultrasonic methods. Images were then captured every second using an external camera. The percentages of residual biofilm were measured using image analysis software. The data were analysed using generalised linear mixed models. The greatest removal was associated with the ultrasonic group (66.76%) followed by sonic (45.49%), manual (43.97%), and passive irrigation group (control) (38.67%) respectively. No marked reduction in the efficiency of NaOCl to remove biofilm was found between the simple and complex anatomy models (p = 0.098). The removal efficacy of NaOCl on the biofilm was limited to the 1 mm level of the lateral canal. The agitation of NaOCl results in better penetration of the irrigant into the lateral canals. Ultrasonic agitation of NaOCl improved the removal of bacterial biofilm.

Keywords: 3D printing, biofilm, root canal irrigation, sodium hypochlorite

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Authors: Muhittin Karaman, Murat Budakoglu

Abstract:

In this study, derivation of lake bathymetry was evaluated using the high resolution Worldview-2 multispectral images in the very shallow hypersaline Lake Acıgöl which does not have a stable water table due to the wet-dry season changes and industrial usage. Every year, a great part of the lake water budget has been consumed for the industrial salt production in the evaporation ponds, which are generally located on the south and north shores of Lake Acıgöl. Therefore, determination of the water level changes from a perspective of remote sensing-based lake water by bathymetry studies has a great importance in the sustainability-control of the lake. While the water table interval is around 1 meter between dry and wet season, dissolved ion concentration, salinity and turbidity also show clear differences during these two distinct seasonal periods. At the same time, with the satellite data acquisition (June 9, 2013), a field study was conducted to collect the salinity values, Secchi disk depths and turbidity levels. Max depth, Secchi disk depth and salinity were determined as 1,7 m, 0,9 m and 43,11 ppt, respectively. Eight-band Worldview-2 image was corrected for atmospheric effects by ATCOR technique. For each sampling point in the image, mean reflectance values in 1*1, 3*3, 5*5, 7*7, 9*9, 11*11, 13*13, 15*15, 17*17, 19*19, 21*21, 51*51 pixel reflectance neighborhoods were calculated separately. A unique image has been derivated for each matrix resolution. Spectral values and depth relation were evaluated for these distinct resolution images. Correlation coefficients were determined for the 1x1 matrix: 0,98, 0,96, 0,95 and 0,90 for the 724 nm, 831 nm, 908 nm and 659 nm, respectively. While 15x5 matrix characteristics with 0,98, 0,97 and 0,97 correlation values for the 724 nm, 908 nm and 831 nm, respectively; 51x51 matrix shows 0,98, 0,97 and 0,96 correlation values for the 724 nm, 831 nm and 659 nm, respectively. Comparison of all matrix resolutions indicates that RedEdge band (724 nm) of the Worldview-2 satellite image has the best correlation with the saline shallow lake of Acıgöl in-situ depth.

Keywords: bathymetry, Worldview-2 satellite image, ATCOR technique, Lake Acıgöl, Denizli, Turkey

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Authors: Reine Suci Wulandari, Rosa Suryantini

Abstract:

Albizia (Paraserianthes falcataria) is a woody plant species that has a high economic value and multifunctional. Albizia is important timber, medicinal plants and can also be used as a plant to rehabilitate critical lands. The demand value of Albizia is increased so that the large quantities and high quality of seeds are required. In vitro propagation techniques are seed propagation that can produce more seeds and quality in a short time. In vitro cultures require growth regulators that can be obtained from biological agents such as endophytic fungi. Endophytic fungi are micro fungi that colonize live plant tissue without producing symptoms or other negative effects on host plants and increase plant growth. The purposes of this research were to isolate and identify endophytic fungi isolated from the root of Albizia and to study the effect of endophytic fungus on the growth of Albizia in vitro. The methods were root isolation, endophytic fungal identification, and inoculation of endophytic fungi to Albizia plants in vitro. Endophytic fungus isolates were grown on PDA media before being inoculated with Albizia sprouts. Incubation is done for 4 (four) weeks. The observed growth parameters were live explant percentage, percentage of explant shoot, and percentage of explant rooted. The results of the research showed that 6 (six) endophytic fungal isolates obtained from the root of Albizia, namely Aspergillus sp., Verticillium sp, Penicillium sp., Trichoderma sp., Fusarium sp., and Acremonium sp. Statistical analysis found that Trichoderma sp. and Fusarium sp. affect in vitro growth of Albizia. Endophytic fungi from the results of this research were potential as plant growth promoting. It can be applied to increase productivity either through increased plant growth and increased endurance of Albizia seedlings to pests and diseases.

Keywords: Albizia, endophytic fungi, propagation, in vitro

Procedia PDF Downloads 266

Authors: Milena Lakicevic

Abstract:

The paper deals with the problem of optimizing management options for urban parks within different scenarios of nature protection and tourism importance. The procedure is demonstrated on a case study example of urban parks in Novi Sad (Serbia). Six management strategies for the selected area have been processed by the decision support method PROMETHEE. Two criteria used for the evaluation were nature protection and tourism and each of them has been divided into a set of indicators: for nature protection those were biodiversity and preservation of original landscape, while for tourism those were recreation potential, aesthetic values, accessibility and culture features. It was pre-assumed that each indicator in a set is equally important to a corresponding criterion. This way, the research was focused on a sensitivity analysis of criteria weights. In other words, weights of indicators were fixed and weights of criteria altered along the entire scale (from the value of 0 to the value of 1), and the assessment has been performed in two-dimensional surrounding. As a result, one could conclude which management strategy would be the most appropriate along with changing of criteria importance. The final ranking of management alternatives was followed up by investigating the mean PROMETHEE Φ values for all options considered and when altering the importance of nature protection/tourism. This type of analysis enabled detecting an alternative with a solid performance along the entire scale, i.e., regardlessly of criteria importance. That management strategy can be seen as a compromise solution when the weight of criteria is not defined. As a conclusion, it can be said that, in some cases, instead of having criteria importance fixed it is important to test the outputs depending on the different schemes of criteria weighting. The research demonstrates the state of the final decision when the decision maker can estimate criteria importance, but also in cases when the importance of criteria is not established or known.

Keywords: criteria weights, PROMETHEE, sensitivity analysis, urban parks

Procedia PDF Downloads 188

Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

Abstract:

In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

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Authors: Princess Stephanie P. Llanos, Rinlee Butch M. Cervera

Abstract:

Lithium iron phosphate (LiFePO4) is a potential cathode material for lithium-ion batteries due to its promising characteristics. In this study, carbon-coated nanograined LiFePO4 is synthesized via wet chemistry method at a low temperature of 400 °C and investigated its performance as a cathode in Lithium battery. The X-ray diffraction pattern of the synthesized samples can be indexed to an orthorhombic LiFePO4 structure. Agglomerated particles that range from 200 nm to 300 nm are observed from scanning electron microscopy images. Transmission electron microscopy images confirm the crystalline structure of LiFePO4 and coating of amorphous carbon layer. Elemental mapping using Energy dispersive spectroscopy analysis revealed the homogeneous dispersion of Fe, P, O, and C elements. On the other hand, the electrochemical performances of the synthesized cathodes were investigated using cyclic voltammetry, galvanostatic charge/discharge tests with different C-rates, and cycling performances. Galvanostatic charge and discharge measurements revealed that the sample sintered at 400 °C for 3 hours with carbon coating demonstrated the highest capacity among the samples which reaches up to 160 mAhg⁻¹ at 0.1C rate.

Keywords: cathode, charge-discharge, electrochemical, lithium batteries

Procedia PDF Downloads 331