Search results for: aerial part

Authors: Mohadeseh Shojaei Shahrokhabadi, Ding-Geng (Din) Chen

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Positive continuous outcomes with a substantial number of zero values and incomplete longitudinal follow-up are quite common in medical cost data. To jointly model semi-continuous longitudinal cost data and survival data and to provide marginalized covariate effect estimates, a marginalized two-part joint model (MTJM) has been developed for outcome variables with lognormal distributions. In this paper, we propose MTJM models for outcome variables from a generalized gamma (GG) family of distributions. The GG distribution constitutes a general family that includes approximately all of the most frequently used distributions like the Gamma, Exponential, Weibull, and Log Normal. In the proposed MTJM-GG model, the conditional mean from a conventional two-part model with a three-parameter GG distribution is parameterized to provide the marginal interpretation for regression coefficients. In addition, MTJM-gamma and MTJM-Weibull are developed as special cases of MTJM-GG. To illustrate the applicability of the MTJM-GG, we applied the model to a set of real electronic health record data recently collected in Iran, and we provided SAS code for application. The simulation results showed that when the outcome distribution is unknown or misspecified, which is usually the case in real data sets, the MTJM-GG consistently outperforms other models. The GG family of distribution facilitates estimating a model with improved fit over the MTJM-gamma, standard Weibull, or Log-Normal distributions.

Keywords: marginalized two-part model, zero-inflated, right-skewed, semi-continuous, generalized gamma

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Authors: Aderet M. Pantierer, Shmuel Pantierer, Raphael Cordina, Yougashwar Budhoo

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Stress concentration occurs when there is an abrupt change in geometry, a mechanical part under loading. These changes in geometry can include holes, notches, or cracks within the component. The modifications create larger stress within the part. This maximum stress is difficult to determine, as it is directly at the point of the minimum area. Strain gauges have yet to be developed to analyze stresses at such minute areas. Therefore, a stress concentration factor must be utilized. The stress concentration factor is a dimensionless parameter calculated solely on the geometry of a part. The factor is multiplied by the nominal, or average, stress of the component, which can be found analytically or experimentally. Stress concentration graphs exist for common loading conditions and geometrical configurations to aid in the determination of the maximum stress a part can withstand. These graphs were developed from historical data yielded from experimentation. This project seeks to verify a stress concentration graph for combined loading conditions. The aforementioned graph was developed using CATIA Finite Element Analysis software. The results of this analysis will be validated through further testing. The 3D modeled parts will be subjected to further finite element analysis using Patran-Nastran software. The finite element models will then be verified by testing physical specimen using a tensile testing machine. Once the data is validated, the unique stress concentration graph will be submitted for publication so it can aid engineers in future projects.

Keywords: stress concentration, finite element analysis, finite element models, combined loading

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Authors: J. Branstett, V. Gagneux, A. Leleu, B. Levadoux, J. Pascale

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This paper presents the interface CONDUCTHOME which controls home automation systems with a Leap Motion using ‘invariant gesture protocols’. The function of this interface is to simplify the interaction of the user with its environment. A hardware part allows the Leap Motion to be carried around the house. A software part interacts with the home automation box and displays the useful information for the user. An objective of this work is the development a natural/invariant/simple gesture control interface to help elder people/people with disabilities.

Keywords: automation, ergonomics, gesture recognition, interoperability

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Authors: D. Kabeya Nahum, L. Y. Kabeya Mukeba

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In this work, the design of surface defects some support of the anchor rod ball joint. The future adhesion contact was rocking in manufacture machining, for giving by the numerical analysis of a short simple solution of thermo-mechanical coupled problem in process engineering. The analysis of geometrical evaluation and the quasi-static and dynamic states are discussed in kinematic dimensional tolerances onto surfaces of part. Geometric modeling using the finite element method (FEM) in rough part of such phase provides an opportunity to solve the nonlinearity behavior observed by empirical data to improve the discrete functional surfaces. The open question here is to obtain spherical geometry of drain wear with the operation of rolling. The formulation with (1 ± 0.01) mm thickness near the drain wear semi-finishing tool for studying different angles, do not help the professional factor in design cutting metal related vibration, friction and interface solid-solid of part and tool during this physical complex process, with multi-parameters no-defined in Sobolev Spaces. The stochastic approach of cracking, wear and fretting due to the cutting forces face boundary layers small dimensions thickness of the workpiece and the tool in the machining position is predicted neighbor to ‘Yakam Matrix’.

Keywords: FEM, geometry, part, simulation, spherical surface engineering, tool, workpiece

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Authors: Michaela Chovancova, Pavel Niedoba

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For the treatment of acute and chronic lung diseases it is preferred to deliver medicaments by inhalation. The drug is delivered directly to tracheobronchial tree. This way allows the given medicament to get directly into the place of action and it makes rapid onset of action and maximum efficiency. The transport of aerosol particles in the particular part of the lung is influenced by their size, anatomy of the lungs, breathing pattern and airway resistance. This article deals with calculation of airway resistance in the lung model of Horsfield. It solves the problem of determination of the pressure losses in bifurcation and thus defines the pressure drop at a given location in the bronchial tree. The obtained data will be used as boundary conditions for transport of aerosol particles in a central part of bronchial tree realized by Computational Fluid Dynamics (CFD) approach. The results obtained from CFD simulation will allow us to provide information on the required particle size and optimal inhalation technique for particle transport into particular part of the lung.

Keywords: human lungs, bronchial tree, pressure losses, airways resistance, flow, breathing

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Authors: C. C. Kruger, P. Van Tonder

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Concrete deteriorates over time and the deterioration can be escalated due to multiple factors. When deteriorations are beneath the concrete’s surface, they could be unknown, even more so when they are located at high elevations. Establishing the severity of such defects could prove difficult and therefore the need to find efficient, safe and economical methods to find these defects becomes ever more important. Current methods using thermography to find defects require equipment such as scaffolding to reach these higher elevations. This could become time- consuming and costly. The risks involved with personnel scaffold or abseil to such heights are high. Accordingly, by combining the technologies of a thermal camera and a Remotely Piloted Aerial System it could be used to find better diagnostic methods. The data could then be constructed into a 3D thermal model to easy representation of the results

Keywords: concrete, infrared thermography, 3D thermal models, diagnostic

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Authors: Aayush Anant, Roshni Thendiyath

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Aridity impacts on agriculture, as well as ecological, human health, and economic activities. In the present study, the effect of climate change on aridity index has been analysed in South Bihar for the past 30 year period by five types of aridity indices as Lang AI, De-Martonne AI, Erinc AI, Pinna combinative AI and UNEP AI. For the study of aridity index, the analysis of rainfall and temperature is significant. Rainfall was analysed for 30 year period from data of 23 gridded stations in for the period 1991-2020. The results show that rainfall pattern was decreasing with respect to previous decades for majority of stations. Trend of maximum, minimum and mean annual temperature has been observed, which shows increasing trend. Structural breakpoint was observed for mean annual temperature data series in year 2004. In period 1991-2004 mean annual temperature was 25.25 ºC, and in period 2005-2020, mean annual temperature was 25.7 ºC. Average aridity index has been calculated by all the above mentioned methods for whole 30 period. Lang AI shows that eastern part of study area is Humid type, and rest all is semi arid. De-Martonne AI also reveals that east part is humid, but rest of the study area is moist sub humid. According to Erinc AI and Pinna, combinative AI shows that whole south Bihar is dry sub humid and semi dry, respectively. UNEP AI shows most of the part as sub humid, and very small part in west is semi arid, while small part of east is humid. Temporal distribution of all the aridity indices shows a decreasing trend. This indicates a decrease in the humid areas in south Bihar for the selected time period.

Keywords: drought, aridity index, climate change, rainfall, temperature

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Haluk Altay, Bilal Yücel, Berkcan Ulcay, Yücel Aydın

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In this study, the design, integration, and testing of measurement systems required for performance tests of jet engines used in small-scale unmanned aerial vehicles are described. Performance tests are carried out as thrust and fuel consumption. For thrust tests, measurements are made using a load cell. Amplifier and filter designs have been made for the load cell to measure accurately to meet the desired sensitivity. It was calibrated by making multiple measurements at different thrust levels. As a result of these processes, the cycle thrust graph was obtained. For fuel consumption tests, tests are carried out using a flow meter. Performance graphics were obtained by finding the fuel consumption for different RPM levels of the engine.

Keywords: jet engine, UAV, experimental test, loadcell, thrust, fuel consumption

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Authors: E. Yeşil, M. Özgök, M. Özdemir, B. Köse

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The aim of the present study was to compare nutritional status, tendency of depression and orthorexia nervosa in vegan, vegetarian and omnivorous. The sample consisted of 150 individuals (126 women, 24 men) who agreed to participate in the study between February and May of the year 2018. Fifty vegan, fifty vegetarian and fifty omnivore diet pattern were compared. In the first part, each participant was interviewed using a structured questionnaire to obtain demographic information about education, occupation and health conditions. In the second part Beck Depression Inventory (BDI) was used. In the third part ORTO-11 was used. In the fourth part, 24 Hours Dietary Record was used in order to determine the nutritional status of individuals. The vegans and vegetarians were interviewed about their diets. The mean body mass index of the vegan, vegetarian and omnivore were, 21,24 ± 3,25; 22,2 ± 4,1 and 22,8 ± 4,3 respectively (p > 0,05). The daily energy intakes of the vegan, vegetarian and omnivore diet were 1792,57 ± 784,8 kcal; 1691,9 ± 742,2 kcal and 1697,9 ± 695,6 kcal (p > 0.05). The mean BDI of the vegan, vegetarian and omnivore diet were 6,2 ± 6,2, 9,8 ± 10,1 and 8,8 ± 8,1, respectively (p > 0,05). The mean ORTO-11 of the vegan, vegetarian and omnivore diet were 25,9 ± 4,2, 27,2 ± 5,9 and 26,4 ± 5,3 (p > 0,05). There was a statistically significant correlation between BDI and ORTO-11 in vegan diet group (p: 0,01 r: 0,333). There was a positive correlation between BMI and BDI in the vegetarian group (p: 0,01 r: 0,363). Also in the vegetarian group; there was a negative correlation between age and ORTO-11 (p: 0,01 r: -0,316). A statistically significant negative correlation was found between waist circumference and ORTO-11 (p: 0,05 r: -0,316) in the omnivore diet group. Also there was a negative correlation between age and BDI (p: 0,05 r: -0,338) in this group. As a conclusion, positive correlation was found between BDI and ORTO-11 score of vegan participants. There were no differences between three groups in BDI or ORTO-11 score.

Keywords: depression, orthorexia nervosa, vegan, vegetarian

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Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Andrew J. Zacharias

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The forest garden approach (FGA) was established by Trees for the Future (TREES) over the organization’s 30 years of agroforestry projects in Sub-Saharan Africa. This method transforms traditional agricultural systems into highly managed gardens that produce food and marketable products year-round. The effects of the FGA on food security, dietary diversity, and economic resilience have been measured closely, and TREES has begun to closely monitor the environmental impacts through the use of sensors mounted on unmanned aerial vehicles, commonly known as 'drones'. These drones collect thousands of pictures to create 3-D models in both the visible and the near-infrared wavelengths. Analysis of these models provides TREES with quantitative and qualitative evidence of improvements to the annual above-ground biomass and leaf area indices, as measured in-situ using NDVI calculations.

Keywords: agroforestry, biomass, drones, NDVI

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Authors: Cedric Leong, Parth Desai, Parth Patel

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The purpose of this project was to develop a neural network based on qualitative team data to predict alliance scores to determine winners of matches in the FIRST Robotics Competition (FRC). The game for the competition changes every year with different objectives and game objects, however the idea was to create a prediction system which can be reused year by year using some of the statistics that are constant through different games, making our system adaptable to future games as well. Aerial Assist is the FRC game for 2014, and is played in alliances of 3 teams going against one another, namely the Red and Blue alliances. This application takes any 6 teams paired into 2 alliances of 3 teams and generates the prediction for the final score between them.

Keywords: artifical neural network, prediction system, qualitative team data, FIRST Robotics Competition (FRC)

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Authors: Maged El Osta, Milad Masoud

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Al Jabal Al Akhdar in the north-eastern part of Libya represents a region with promising ecological underpinning for grazing and other agricultural developments. The groundwater potential of both Upper Cretaceous and Eocene aquifers was studied based the available literature and a complete database for about 112 water wells drilled in the period 2003-2009. In this research, the hydrogeological methods will be integrated with the Geographic Information System (GIS) that played a main role in highlighting the spatial characteristics of the groundwater system. The results indicate that the depth to water for the Upper Cretaceous aquifer ranges from 150 to 458 m, and the piezometric surface decreases from over 500 m (m.s.l) in the northern parts to -20 m (m.s.l) in southeastern part. Salinity ranges between 303 and 1329 mg/l indicating that groundwater belongs to the slightly fresh water class. In the Eocene aquifer, the depth to groundwater ranges from 120 to 290.5 m and the potentiometric level decreases gradually southwards from 220 to -51 m (m.s.l) and characterized by steep slope in the southeastern part of the study area, where the aquifer characterized by relatively high productivity (specific capacity ranges between 10.08 and 332.3 m2/day). The groundwater salinity within this aquifer ranges between 198 and 2800 mg/l (fresh to brackish water class). The annual average rainfall (from 280 to 500 mm) plays a significant role in the recharge of the two aquifers. The priority of groundwater quality and potentiality increases towards the central and northern portions of the concerned area.

Keywords: Eocene and Upper Cretaceous aquifers, rainfall, potentiality, Geographic Information System (GIS)

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Authors: Shilpi Tripathi

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India has adopted the policy of economic reforms (Globalization, Liberalization, and Privatization) in 1991 which has reduced the trade barriers and investment restrictions and further increased the economy’s international trade, foreign direct investment (FDI) inflows and Gross Domestic Product (GDP) growth. The paper empirically studies the relationship between India’s international trades, GDP, FDI and environment during 1978-2012. The first part of the paper focuses on the background and trends of FDI, GDP, trade, and environment (CO2). The second part focuses on the literature regarding the relationship among all the variables. The last part of paper, we examine the results of empirical analysis like co integration and Granger causality between foreign trade, FDI inflows, GDP and CO2 since 1978. The findings of the paper revealed that there is only one uni- directional causality exists between GDP and trade. The direction of causality reveals that international trade is one of the major contributors to the economic growth (GDP). While, there is no causality found between GDP and FDI, FDI, and CO2 and International trade and CO2. The paper concludes with the policy recommendations that will ensure environmental friendly trade, investment and growth in India for future.

Keywords: international trade, foreign direct investment, GDP, CO2, co-integration, granger causality test

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Authors: Gi Ryung Song, Kyoung Seok Kim

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This study reviewed the literature that focused on similarity of various characteristics such as values, personality, or demographics between employee and other elements in its organization for example employee with leader, job, and organization. We divided a body of this study into two parts and organized and demonstrated recent studies in first part. Three issues appeared in this part, which are statistical ways of measuring similarity, supervisor-subordinate similarity, and person-organization fit with person-job fit. In the latter part, based on the three issues of recent studies, we suggested three propositions about points that the recent studies missed or the studies did not orient. First proposition argued about the direction of similarity, which could also be interpreted as there is causal relation between employee and its workplace environments. Second, we suggested a consideration of eliminating common variance buried in one’s characteristics or its profiles. Third proposition was about the similarity of extra role behavior between individual and organization, and we treated this organization’s level of extra role behavior as a kind of its culture. In doing so, similarity of individual’s extra role behavior and organization’s has the meaning that individual’s congruence against their organization culture.

Keywords: similarity, person-organization fit, supervisor-subordinate similarity, literature review

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Authors: T. Abdelkrim, K. Benamrane, B. Bezza, Aeh Benkhelifa, A. Borni

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This paper proposes a regulation method of back-to-back connected three-level converters in order to reduce the torque ripple in induction motor. First part is dedicated to the presentation of the feedback control of three-level PWM rectifier. In the second part, three-level NPC voltage source inverter balancing DC bus algorithm is presented. A theoretical analysis with a complete simulation of the system is presented to prove the excellent performance of the proposed technique.

Keywords: back-to-back connection, feedback control, neutral-point balance, three-level converter, torque ripple

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Mahmoud M. S. Albattah

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Urbanization results in the expansion of administrative boundaries, mainly at the periphery, ultimately leading to changes in landcover. Agricultural land, naturally vegetated land, and other land types are converted into residential areas with a high density of constructs, such as transportation systems and housing. In urban regions of rapid growth and change, urban planners need regular information on up to date ground change. Amman (the capital of Jordan) is growing at unprecedented rates, creating extensive urban landscapes. Planners interact with these changes without having a global view of their impact. The use of aerial photographs and satellite images data combined with topographic information and field survey could provide effective information to develop urban change and growth inventory which could be explored towards producing a very important signature for the built-up area changes.

Keywords: highway design, satellite technologies, remote sensing, GIS, image segmentation, classification

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Authors: M. Fayez Al Homsi, Reem Al Homsi

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Renal disease is a major cause of morbidity and mortality. Glomerular diseases make a small portion of the renal disease. Lupus glomerulonephritis (GN) is the commonest among the GN of systemic diseases. More than a hundred and eighty-eight consecutive renal biopsies are performed and evaluated for clinically suspected glomerular diseases over a period of two years. As in a standard practice after receiving the ultrasound-guided renal biopsies, the fresh biopsy is divided to three parts, one part is frozen for immunofluorescence evaluation, the second part is placed in 4% glutaraldehyde for electron microscopic evaluation, and the third part is placed in 10% buffered formalin for light microscopic evaluation. Primary glomerular diseases are detected in 83 biopsies; glomerulonephritis (GN) of systemic diseases are identified in 88, glomerular lesions in vascular diseases in 3, glomerular lesions in metabolic diseases in 7, hereditary nephropathies in 2, end-stage kidney in 2, and glomerular lesions in transplantation in 3 biopsies. Among the primary lesions, focal segmental glomerulosclerosis (28) and mesangial proliferative GN (26) were the most common. Lupus GN (67) and Ig A nephropathy (20) were the most common of the GN of systemic diseases. Lupus nephritis biopsies included one biopsy diagnosed as class 1 (normal), 17 biopsies class 2 (mesangial proliferation), 5 biopsies class 3 (focal proliferative GN), 39 biopsies class 4 diffuse proliferative GN), 3 biopsies class 5 (membranous GN), and 2 biopsies class 6 (crescentic GN). Lupus GN is the most common among GN of systemic diseases. While diabetes is very common here, diabetic GN (3 biopsies) is not as common as might one expects. Most likely this is due to sampling and reluctance on part of nephrologists and patients in sampling the kidney in diabetes mellitus.

Keywords: diabetes, glomerulonephritis, lupus, mesangial proliferation, nephropathy

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Authors: Pengchao Wei, Xiangzhong Fang

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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: Itay Harlap

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Over the past decade, LGBT figures have become increasingly visible on Israeli television in its various channels and genres. In recent years, however, the representation of gays on Israeli television has undergone an interesting shift, whereby many television texts feature gay people as fathers. These texts, mostly news items and documentaries, usually present gay parenthood as a positive phenomenon. The question in paper is whether LGBT parenting (in reality and as representation) fated to be part of the homonormativity that characterizes the LGBT community in Israel, or can it be an alternative to the hegemonic discourse? This paper embraces a dialectical position and explores the tension between mainstream and radical, or homonormativity and queer politics in the specific Israeli Jewish context through a textual and discursive reading of a selection of television programs that revolve principally around gay parenting in Israel. The first part of this lecture addresses the cultural and social context that generated these representations, dealing with three key Israeli areas: The fertility cult, the evolution of the LGBT community, and the evolution of local television. The second part offers a queer reading of these ‘positive’ representations (mainly in special reports on the news and programs labeled as ‘documentaries’ by broadcasters) and highlight the possible price of the ‘bear hug’ given by Israeli media to gay parents. The last part focuses on a single case study, the TV serial drama Ima Veabaz, and suggests that this drama exposes the performative aspect of parenting and the connection between ethnicity and fertility, and offers an alternative to normative displays of gay parenting.

Keywords: fatherhood, heteronormativity, Israel, queer theory, television

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Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Sandro Bartolini, Alessandro Mecocci, Alessio Medaglini

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The growing popularity of systems based on unmanned aerial vehicles (UAVs) is highlighting their vulnerability, particularly in relation to the positioning system used. Typically, UAV architectures use the civilian GPS, which is exposed to a number of different attacks, such as jamming or spoofing. This is why it is important to develop alternative methodologies to accurately estimate the actual UAV position without relying on GPS measurements only. In this paper, we propose a position estimate method for UAVs based on monocular visual odometry. We have developed a flight control system capable of keeping track of the entire trajectory travelled, with a reduced dependency on the availability of GPS signals. Moreover, the simplicity of the developed solution makes it applicable to a wide range of commercial drones. The final goal is to allow for safer flights in all conditions, even under cyber-attacks trying to deceive the drone.

Keywords: visual odometry, autonomous uav, position measurement, autonomous outdoor flight

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Authors: Ha T. Pham, Shuichi Miyagawa

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Ongoing landscape transformation is one of the major causes behind disappearance of traditional landscapes, and lead to species and resource loss. Tree in paddy fields in the northeast of Thailand is one of those traditional landscapes. Using three different historical time layers, we acknowledged the severe deforestation and rapid urbanization happened in the region. Despite the general thinking of decline in tree density as consequences, the heterogeneous trend of changes in total tree density in three studied landscapes denied the hypothesis that number of trees in paddy field depend on the length of land use practice. On the other hand, due to selection of planting new trees on levees, existence of trees in paddy field are now rely on their values for human use. Besides, changes in land use and landscape structure had a significant impact on decision of which tree density level is considered as suitable for the landscape.

Keywords: aerial photographs, land use change, traditional landscape, tree in paddy fields

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Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

Abstract:

Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

Procedia PDF Downloads 113

Authors: Yujin Jeong, Youkyung Son, Myounghwan Choi, Sanghyub Lee, Sangyeol Lee, Changho Hwang, Kyo-in Koo

Abstract:

Dysphasia is difficulty in swallowing food because of oral cavity impairments induced by stroke, muscle damage, tumor. Intermittent oro-esophageal (IOE) tube feeding is one of the well-known feeding methods for the dysphasia patients. However, it is hard to insert at the proper position in esophagus. In this study, we design and fabricate the IOE tube guide using 3-dimensional (3D) printer. The printed IOE tube is tested in a mannequin (Airway Management Trainer, Co., Ltd., Copenhagen, Denmark) mimicking human’s esophagus. The gag reflex point is measured as the design point in the mannequin. To avoid the gag reflex, we design various shapes of IOE tube guide. One structure is separated into three parts; biting part, part through oral cavity, connecting part to oro-esophageal. We designed 6 types of IOE tube guide adjusting length and angle of these three parts. To evaluate the IOE tube guide, it is inserted in the mannequin, and through the inserted guide, an endoscopic camera successfully arrived at the oro-esophageal. We had planned to apply this mannequin-based design experience to patients in near future.

Keywords: dysphagia, feeding method, IOE tube guide, 3-D printer

Procedia PDF Downloads 404

Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

Abstract:

This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

Procedia PDF Downloads 145

Authors: Walid Hassairi, Moncef Bousselmi, Mohamed Abid

Abstract:

Functional verification is a major part of today’s system design task. Several approaches are available for verification on a high abstraction level, where designs are often modeled using MATLAB/Simulink. However, different approaches are a barrier to a unified verification flow. In this paper, we propose a co-simulation interface between SystemC and MATLAB and Simulink to enable functional verification of multi-abstraction levels designs. The resulting verification flow is tested on JPEG compression algorithm. The required synchronization of both simulation environments, as well as data type conversion is solved using the proposed co-simulation flow. We divided into two encoder jpeg parts. First implemented in SystemC which is the DCT is representing the HW part. Second, consisted of quantization and entropy encoding which is implemented in Matlab is the SW part. For communication and synchronization between these two parts we use S-Function and engine in Simulink matlab. With this research premise, this study introduces a new implementation of a Hardware SystemC of DCT. We compare the result of our simulation compared to SW / SW. We observe a reduction in simulation time you have 88.15% in JPEG and the design efficiency of the supply design is 90% in SDR.

Keywords: hardware/software, co-design, co-simulation, systemc, matlab, s-function, communication, synchronization

Procedia PDF Downloads 367