Search results for: vascular tree
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1278

Search results for: vascular tree

1068 Angular-Coordinate Driven Radial Tree Drawing

Authors: Farshad Ghassemi Toosi, Nikola S. Nikolov

Abstract:

We present a visualization technique for radial drawing of trees consisting of two slightly different algorithms. Both of them make use of node-link diagrams for visual encoding. This visualization creates clear drawings without edge crossing. One of the algorithms is suitable for real-time visualization of large trees, as it requires minimal recalculation of the layout if leaves are inserted or removed from the tree; while the other algorithm makes better utilization of the drawing space. The algorithms are very similar and follow almost the same procedure but with different parameters. Both algorithms assign angular coordinates for all nodes which are then converted into 2D Cartesian coordinates for visualization. We present both algorithms and discuss how they compare to each other.

Keywords: Radial drawing, Visualization, Algorithm, Use of node-link diagrams

Procedia PDF Downloads 341
1067 Traumatic Brachiocephalic Artery Pseudoaneurysm

Authors: Sally Shepherd, Jessica Wong, David Read

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Traumatic brachiocephalic artery aneurysm is a rare injury that typically occurs as a result of a blunt chest injury. A 19-year-old female sustained a head-on, high speed motor vehicle crash into a tree. Upon release after 45 minutes of entrapment, she was tachycardic but normotensive, with a significant seatbelt sign across her chest and open deformed right thigh with weak pulses in bilateral lower limbs. A chest XR showed mild upper mediastinal widening. A CT trauma series plus gated CT chest revealed a grade 3a aortic arch transection with brachiocephalic pseudoaneurysm. Endovascular repair of the brachiocephalic artery was attempted post-presentation but was unsuccessful as the first stent migrated to the infrarenal abdominal aorta and the second stent across the brachiocephalic artery origin had a persistent leak at the base. She was transferred to Intensive Care for strict blood pressure control. She returned to theatre 5 hours later for a median sternotomy, aortic arch repair with an 8mm graft extraction, and excision of the innominate artery pseudoaneurysm. She had an uncomplicated post-operative recovery. This case highlights that brachiocephalic artery injury is a rare but potentially lethal injury as a result of blunt chest trauma. Safe management requires a combined Vascular and Cardiothoracic team approach, as stenting alone may be insufficient.

Keywords: blunt chest injury, Brachiocephalic aneurysm, innominate artery, trauma

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1066 Developing Structured Sizing Systems for Manufacturing Ready-Made Garments of Indian Females Using Decision Tree-Based Data Mining

Authors: Hina Kausher, Sangita Srivastava

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In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which covers the variety of figure proportions in both height and girth. 3,000 data has been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from some states of India to produce the sizing system suitable for clothing manufacture and retailing. This data is used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from a large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: anthropometric data, data mining, decision tree, garments manufacturing, sizing systems, ready-made garments

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1065 A Comparative Analysis of Machine Learning Techniques for PM10 Forecasting in Vilnius

Authors: Mina Adel Shokry Fahim, Jūratė Sužiedelytė Visockienė

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With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realisation often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter

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1064 Evaluation of Collect Tree Protocol for Structural Health Monitoring System Using Wireless Sensor Networks

Authors: Amira Zrelli, Tahar Ezzedine

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Routing protocol may enhance the lifetime of sensor network, it has a highly importance, especially in wireless sensor network (WSN). Therefore, routing protocol has a big effect in these networks, thus the choice of routing protocol must be studied before setting up our network. In this work, we implement the routing protocol collect tree protocol (CTP) which is one of the hierarchic protocols used in structural health monitoring (SHM). Therefore, to evaluate the performance of this protocol, we choice to work with Contiki system and Cooja simulator. By throughput and RSSI evaluation of each node, we will deduce about the utility of CTP in structural monitoring system.

Keywords: CTP, WSN, SHM, routing protocol

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1063 The Use of Boosted Multivariate Trees in Medical Decision-Making for Repeated Measurements

Authors: Ebru Turgal, Beyza Doganay Erdogan

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Machine learning aims to model the relationship between the response and features. Medical decision-making researchers would like to make decisions about patients’ course and treatment, by examining the repeated measurements over time. Boosting approach is now being used in machine learning area for these aims as an influential tool. The aim of this study is to show the usage of multivariate tree boosting in this field. The main reason for utilizing this approach in the field of decision-making is the ease solutions of complex relationships. To show how multivariate tree boosting method can be used to identify important features and feature-time interaction, we used the data, which was collected retrospectively from Ankara University Chest Diseases Department records. Dataset includes repeated PF ratio measurements. The follow-up time is planned for 120 hours. A set of different models is tested. In conclusion, main idea of classification with weighed combination of classifiers is a reliable method which was shown with simulations several times. Furthermore, time varying variables will be taken into consideration within this concept and it could be possible to make accurate decisions about regression and survival problems.

Keywords: boosted multivariate trees, longitudinal data, multivariate regression tree, panel data

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1062 Model Development for Real-Time Human Sitting Posture Detection Using a Camera

Authors: Jheanel E. Estrada, Larry A. Vea

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This study developed model to detect proper/improper sitting posture using the built in web camera which detects the upper body points’ location and distances (chin, manubrium and acromion process). It also established relationships of human body frames and proper sitting posture. The models were developed by training some well-known classifiers such as KNN, SVM, MLP, and Decision Tree using the data collected from 60 students of different body frames. Decision Tree classifier demonstrated the most promising model performance with an accuracy of 95.35% and a kappa of 0.907 for head and shoulder posture. Results also showed that there were relationships between body frame and posture through Body Mass Index.

Keywords: posture, spinal points, gyroscope, image processing, ergonomics

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1061 Augmented Reality to Support the Design of Innovative Agroforestry Systems

Authors: Laetitia Lemiere, Marie Gosme, Gerard Subsol, Marc Jaeger

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Agroforestry is recognized as a way of developing sustainable and resilient agriculture that can fight against climate change. However, the number of species combinations, spatial configurations, and management options for trees and crops is vast. These choices must be adapted to the pedoclimatic and socio-economic contexts and to the objectives of the farmer, who therefore needs support in designing his system. Participative design workshops are a good way to integrate the knowledge of several experts in order to design such complex systems. The design of agroforestry systems should take into account both spatial aspects (e.g., spacing of trees within the lines and between lines, tree line orientation, tree-crop distance, species spatial patterns) and temporal aspects (e.g., crop rotations, tree thinning and pruning, tree planting in the case of successional agroforestry). Furthermore, the interactions between trees and crops evolve as the trees grow. However, agroforestry design workshops generally emphasize the spatial aspect only through the use of static tokens to represent the different species when designing the spatial configuration of the system. Augmented reality (AR) may overcome this limitation, allowing to visualize dynamic representations of trees and crops, and also their interactions, while at the same time retaining the possibility to physically interact with the system being designed (i.e., move trees, add or remove species, etc.). We propose an ergonomic digital solution capable of assisting a group of agroforestry experts to design an agroforestry system and to represent it. We investigated the use of web-based marker-based AR that does not require specific hardware and does not require specific installation so that all users could use their own smartphones right out of the pocket. We developed a prototype mobilizing the AR.js, ArToolKit.js, and Three.js open source libraries. In our implementation, we gradually build a virtual agroforestry system pattern scene from the users' interactions. A specific set of markers initialize the scene properties, and the various plant species are added and located during the workshop design session. The full virtual scene, including the trees positions with their neighborhood, are saved for further uses, such as virtual, augmented instantiation in the farmer fields. The number of tree species available in the application is gradually increasing; we mobilize 3D digital models for walnut, poplar, wild cherry, and other popular species used in agroforestry systems. The prototype allows shadow computations and the representation of trees at various growth stages, as well as different tree generations, and is thus able to visualize the dynamics of the system over time. Future work will focus on i) the design of complex patterns mobilizing several tree/shrub organizations, not restricted to lines; ii) the design of interfaces related to cultural practices, such as clearing or pruning; iii) the representation of tree-crop interactions. Beside tree shade (light competition), our objective is to represent also below-ground competitions (water, nitrogen) or other variables of interest for the design of agroforestry systems (e.g., predicted crop yield).

Keywords: agroforestry system design, augmented reality, marker-based AR, participative design, web-based AR

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1060 Case Report: Massive Deep Venous Thrombosis in a Young Female: A Rare and Fatal Presentation of May-Thurner Syndrome

Authors: Mahmoud Eldeeb, Yousri Mohamed

Abstract:

Background: May-Thurner Syndrome (MTS) is a rare vascular condition caused by the compression of the left common iliac vein by the overlying right common iliac artery, leading to venous stasis and an increased risk of deep vein thrombosis (DVT). While MTS typically presents in young adults, its diagnosis is often delayed due to its nonspecific presentation, which can lead to catastrophic complications like massive pulmonary embolism (PE). Early recognition and intervention are paramount to prevent fatal outcomes. Objectives: Highlight the importance of early recognition and management of critically ill patients presenting with life- and limb-threatening conditions. Raise awareness of May-Thurner Syndrome as a rare but significant cause of extensive DVT in young adults. Emphasize the necessity of a multidisciplinary approach to managing complex vascular emergencies. Methodology: A 21-year-old female presented with a 7-day history of progressive left leg swelling, pain, and skin discoloration following immobilization due to gastroenteritis. Clinical suspicion for massive DVT and compartment syndrome prompted immediate initiation of a heparin bolus and referrals to vascular and orthopedic surgery teams. Bedside Doppler ultrasound confirmed extensive DVT, and subsequent CT venography revealed thrombi extending to the inferior vena cava, consistent with MTS. Despite anticoagulation therapy, angioplasty and stenting were required to restore venous patency. Tragically, the patient experienced a massive PE during the procedure, requiring cardiopulmonary resuscitation (CPR) and transfer to a tertiary center for cardiothoracic intervention. Results: The case highlights the aggressive and life-threatening progression of MTS. The patient’s presentation was characterized by massive DVT with severe pain and discoloration, rapidly culminating in a PE during intervention. The combination of bedside imaging and CT venography facilitated an accurate diagnosis. Despite timely management, the patient’s course underscores the high mortality risk associated with MTS-related thromboembolism. Conclusion: May-Thurner Syndrome, though rare, can lead to devastating complications in young adults if not promptly recognized and treated. This case emphasizes the need for a high index of suspicion in patients presenting with unexplained extensive DVT, especially in the context of limited mobility or other precipitating factors. Multidisciplinary collaboration, including vascular imaging, anticoagulation, and interventional procedures, is critical to optimize outcomes. Urgent recognition and treatment of MTS are vital to prevent progression to massive PE and death.

Keywords: may-thurner syndrome, deep venous thrombosis, pulmonary embolism, vascular emergency, iliac vein compression syndrome

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1059 Data Mining Algorithms Analysis: Case Study of Price Predictions of Lands

Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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1058 Antioxidant Extraction from Indonesian Crude Palm Oil and Its Antioxidation Activity

Authors: Supriyono, Sumardiyono, Puti Pertiwi

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Crude palm oil (CPO) is a vegetable oil that came from a palm tree bunch. Palm oil tree was known as highest vegetable oil yield. It was grown across Equatorial County, especially in Malaysia and Indonesia. The greenish red color on CPO was came from carotenoid antioxidant, which could be extracted and use separately as functional food and other purposes as antioxidant source. Another antioxidant that also found in CPO is tocopherol. The aim of the research work is to find antioxidant activity on CPO comparing to the synthetic antioxidant that available in a market. On this research work, antioxidant was extracted by using a mixture of acetone and n. hexane, while activity of the antioxidant extract was determine by DPPH method. The extracted matter was shown that their antioxidant activity was about 45% compare to pure tocopherol and beta carotene.

Keywords: antioxidant, , beta carotene, , crude palm oil, , DPPH, , tocopherol

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1057 Monitoring Soil Moisture Dynamic in Root Zone System of Argania spinosa Using Electrical Resistivity Imaging

Authors: F. Ainlhout, S. Boutaleb, M. C. Diaz-Barradas, M. Zunzunegui

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Argania spinosa is an endemic tree of the southwest of Morocco, occupying 828,000 Ha, distributed mainly between Mediterranean vegetation and the desert. This tree can grow in extremely arid regions in Morocco, where annual rainfall ranges between 100-300 mm where no other tree species can live. It has been designated as a UNESCO Biosphere reserve since 1998. Argania tree is of great importance in human and animal feeding of rural population as well as for oil production, it is considered as a multi-usage tree. Admine forest located in the suburbs of Agadir city, 5 km inland, was selected to conduct this work. The aim of the study was to investigate the temporal variation in root-zone moisture dynamic in response to variation in climatic conditions and vegetation water uptake, using a geophysical technique called Electrical resistivity imaging (ERI). This technique discriminates resistive woody roots, dry and moisture soil. Time-dependent measurements (from April till July) of resistivity sections were performed along the surface transect (94 m Length) at 2 m fixed electrode spacing. Transect included eight Argan trees. The interactions between the tree and soil moisture were estimated by following the tree water status variations accompanying the soil moisture deficit. For that purpose we measured midday leaf water potential and relative water content during each sampling day, and for the eight trees. The first results showed that ERI can be used to accurately quantify the spatiotemporal distribution of root-zone moisture content and woody root. The section obtained shows three different layers: middle conductive one (moistured); a moderately resistive layer corresponding to relatively dry soil (calcareous formation with intercalation of marly strata) on top, this layer is interspersed by very resistant layer corresponding to woody roots. Below the conductive layer, we find the moderately resistive layer. We note that throughout the experiment, there was a continuous decrease in soil moisture at the different layers. With the ERI, we can clearly estimate the depth of the woody roots, which does not exceed 4 meters. In previous work on the same species, analyzing the δ18O in water of xylem and in the range of possible water sources, we argued that rain is the main water source in winter and spring, but not in summer, trees are not exploiting deep water from the aquifer as the popular assessment, instead of this they are using soil water at few meter depth. The results of the present work confirm the idea that the roots of Argania spinosa are not growing very deep.

Keywords: Argania spinosa, electrical resistivity imaging, root system, soil moisture

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1056 Effect of Scattered Vachellia Tortilis (Umbrella Torn) and Vachellia nilotica (Gum Arabic) Trees on Selected Physio-Chemical Properties of the Soil and Yield of Sorghum (Sorghum bicolor (L.) Moench) in Ethiopia

Authors: Sisay Negash, Zebene Asfaw, Kibreselassie Daniel, Michael Zech

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A significant portion of the Ethiopian landscape features scattered trees that are deliberately managed in crop fields to enhance soil fertility and crop yield in which the compatibility of crops with these trees varies depending on location, tree species, and annual crop type. This study aimed to examine the effects of scattered Vachellia tortilis and Vachellia nilotica trees on selected physico-chemical properties of the soil, as well as the yield and yield components of sorghum in Ethiopia. Vachellia tortilis and Vachellia nilotica were selected on abundance occurrence and managed in crop fields. A randomized complete block design was used, with a distance from the tree canopy (middle, edge, and outside) as a treatment, and five trees of each species served as replications. Sorghum was planted up to 15 meters in the east, west, south, and north directions from the tree trunk to assess growth and yield. Soil samples were collected from the two tree species, three distance factors, three soil depths(0-20cm, 20-40cm, and 40-60cm), and five replications, totaling 45 samples for each tree species. These samples were analyzed for physical and chemical properties. The results indicated that both V. tortilis and V. nilotica significantly affected soil physico-chemical properties and sorghum yield. Specifically, soil moisture content, EC, total nitrogen, organic carbon, available phosphorus and potassium, CEC, sorghum plant height, panicle length, biomass, and yield decreased with increasing distance from the canopy. Conversely, bulk density and pH increased. Under the canopy, sorghum yield increased by 66.4% and 53.5% for V. tortilis and V. nilotica, respectively, due to higher soil moisture and nutrient availability. The study recommends promoting trees in crop fields, management options for new saplings, and further research on root decomposition and nutrient supply.

Keywords: canopy, crop yield, soil nutrient, soil organic matter, yield components

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1055 The 'Cornaro Family Tree' as a Tool for Identifying Cornaro Family Portraits

Authors: Rachel Healy

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This paper builds on the speaker’s recent identification of an early sixteenth-century painting in the National Gallery of Ireland as containing rare portraits of Giorgio Cornaro (brother of Caterina, Queen of Cyprus) and his son Cardinal Francesco. It resolves similar long-standing confusion regarding the identities of sitters in related works by Titian, Raphael and Bernini, in works such as the Cornaro Triple Portrait in the National Gallery of Art, Washington DC, Man with a Falcon in The Joslyn Art Museum, Omaha, Head of a Cardinal, Wilton House, Wiltshire and The Cornaro Chapel, Santa Maria della Vittoria, Rome, by using an overlooked seventeenth-century painted Cornaro family tree, from Palazzo Corner-Mocenigo, as a tool for identifying these and other sitters in disputed portraits of one of Renaissance Venice’s wealthiest and most influential patrician families. In so doing, it will cast new light on Titian’s development as a portraitist and the extent to which important paintings commissioned by the Cornaro survived fires at two family palaces in Venice in the 1530s. It will also showcase the associations Raphael had with the Cornaro cardinal and will present new evidence relating to the likenesses Bernini fashioned for the Cornaro Chapel in 1647-52.

Keywords: Venice, portraits, titian, genealogy, Bernini, family tree, Raphael, venetian family, cornaro, sixteenth century Venice, portraiture

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1054 Investigation of Changes of Physical Properties of the Poplar Wood in Radial and Longitudinal Axis at Chaaloos Zone

Authors: Afshin Veisi

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In this study, the physical properties of wood in poplar wood (Populous sp.) were analyzed in longitudinal and radial directions of the stem. Three Populous Alba tree were cut in chaloos zone and from each tree, 3 discs were selected at 130cm, half of tree and under of crown. The test samples from pith to bark (heartwood to sapwood) were prepared from these discs for measuring the involved properties such as, wet, dry and critical specific gravity, porosity, volume shrinkage and swelling based on the ASTM standard, and data in two radial and longitudinal directions in the trank were statistically analyzed. Such as, variations of wet, dry and critical specific gravity had in radial direction respectively: irregular increase, increase and increase, and in longitudinal direction respectively: irregular decrease, irregular increase and increase. Results of variations to moisture content and porosity show that in radial direction respectively: irregular increasing and decreasing, and in longitudinal direction from down to up respectively: irregular decreasing and stability. Volume shrinkage and swelling variations show in radial direction irregular and in longitudinal axial regular decreasing.

Keywords: poplar wood, physical properties, shrinkage, swelling, critical specific gravity, wet specific gravity, dry specific gravity

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1053 Bridging Urban Planning and Environmental Conservation: A Regional Analysis of Northern and Central Kolkata

Authors: Tanmay Bisen, Aastha Shayla

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This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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1052 A Comparative Study on Automatic Feature Classification Methods of Remote Sensing Images

Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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1051 Effect of Ramp Rate on the Preparation of Activated Carbon from Saudi Date Tree Fronds (Agro Waste) by Physical Activation Method

Authors: Muhammad Shoaib, Hassan M Al-Swaidan

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Saudi Arabia is the major date producer in the world. In order to maximize the production from date tree, pruning of the date trees is required annually. Large amount of this agriculture waste material (palm tree fronds) is available in Saudi Arabia and considered as an ideal source as a precursor for production of activated carbon (AC). The single step procedure for the preparation of micro porous activated carbon (AC) from Saudi date tree fronds using mixture of gases (N2 and CO2) is carried out at carbonization/activation temperature at 850°C and at different ramp rates of 10, 20 and 30 degree per minute. Alloy 330 horizontal reactor is used for tube furnace. Flow rate of nitrogen and carbon dioxide gases are kept at 150 ml/min and 50 ml/min respectively during the preparation. Characterization results reveal that the BET surface area, pore volume, and average pore diameter of the resulting activated carbon generally decreases with the increase in ramp rate. The activated carbon prepared at a ramp rate of 10 degrees/minute attains larger surface area and can offer higher potential to produce activated carbon of greater adsorption capacity from agriculture wastes such as date fronds. The BET surface areas of the activated carbons prepared at a ramp rate of 10, 20 and 30 degree/minute after 30 minutes activation time are 1094, 1020 and 515 m2/g, respectively. Scanning electron microscopy (SEM) for surface morphology, and FTIR for functional groups was carried out that also verified the same trend. Moreover, by increasing the ramp rate from 10 and 20 degrees/min the yield remains same, i.e. 18%, whereas at a ramp rate of 30 degrees/min the yield increases from 18 to 20%. Thus, it is feasible to produce high-quality micro porous activated carbon from date frond agro waste using N2 carbonization followed by physical activation with CO2 and N2 mixture. This micro porous activated carbon can be used as adsorbent of heavy metals from wastewater, NOx SOx emission adsorption from ambient air and electricity generation plants, purification of gases, sewage treatment and many other applications.

Keywords: activated carbon, date tree fronds, agricultural waste, applied chemistry

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1050 Effectiveness of ISSR Technique in Revealing Genetic Diversity of Phaseolus vulgaris L. Representing Various Parts of the World

Authors: Mohamed El-Shikh

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Phaseolus vulgaris L. is the world’s second most important bean after soybeans; used for human food and animal feed. It has generally been linked to reduced risk of cardiovascular disease, diabetes mellitus, obesity, cancer and diseases of digestive tract. The effectiveness of ISSR in achievement of the genetic diversity among 60 common bean accessions; represent various germplasms around the world was investigated. In general, the studied Phaseolus vulgaris accessions were divided into 2 major groups. All of the South-American accessions were separated into the second major group. These accessions may have different genetic features that are distinct from the rest of the accessions clustered in the major group. Asia and Europe accessions (1-20) seem to be more genetically similar (99%) to each other as they clustered in the same sub-group. The American and African varieties showed similarities as well and clustered in the same sub-tree group. In contrast, Asian and American accessions No. 22 and 23 showed a high level of genetic similarities, although these were isolated from different regions. The phylogenetic tree showed that all the Asian accessions (along with Australian No. 59 and 60) were similar except Indian and Yemen accessions No. 9 and 20. Only Netherlands accession No. 3 was different from the rest of European accessions. Morocco accession No. 52 was genetically different from the rest of the African accessions. Canadian accession No. 44 seems to be different from the other North American accessions including Guatemala, Mexico and USA.

Keywords: phylogenetic tree, Phaseolus vulgaris, ISSR technique, genetics

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1049 Normalized Laplacian Eigenvalues of Graphs

Authors: Shaowei Sun

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Let G be a graph with vertex set V(G)={v_1,v_2,...,v_n} and edge set E(G). For any vertex v belong to V(G), let d_v denote the degree of v. The normalized Laplacian matrix of the graph G is the matrix where the non-diagonal (i,j)-th entry is -1/(d_id_j) when vertex i is adjacent to vertex j and 0 when they are not adjacent, and the diagonal (i,i)-th entry is the di. In this paper, we discuss some bounds on the largest and the second smallest normalized Laplacian eigenvalue of trees and graphs. As following, we found some new bounds on the second smallest normalized Laplacian eigenvalue of tree T in terms of graph parameters. Moreover, we use Sage to give some conjectures on the second largest and the third smallest normalized eigenvalues of graph.

Keywords: graph, normalized Laplacian eigenvalues, normalized Laplacian matrix, tree

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1048 Efficacy of Deep Learning for Below-Canopy Reconstruction of Satellite and Aerial Sensing Point Clouds through Fractal Tree Symmetry

Authors: Dhanuj M. Gandikota

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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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1047 Comparative Study od Three Artificial Intelligence Techniques for Rain Domain in Precipitation Forecast

Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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1046 Cytotoxic Effect of Neem Seed Extract (Azadirachta indica) in Comparison with Artificial Insecticide Novastar on Haemocytes (THC and DHC) of Musca domestica

Authors: Muhammad Zaheer Awan, Adnan Qadir, Zeeshan Anjum

Abstract:

Housefly, Musca domestica Linnaeus is ubiquitous and hazardous for Homo sapiens and livestock in sundry venerations. Musca domestica cart 100 different pathogens, such as typhoid, salmonella, bacillary dysentery, tuberculosis, anthrax and parasitic worms. The flies in rural areas usually carry more pathogens. Houseflies feed on liquid or semi-liquid substances besides solid materials which are softened by saliva. Neem botanically known as Azadirachta indica belongs to the family Meliaceae and is an indigenous tree to Pakistan. The neem tree is also one such tree which has been revered by the Pakistanis and Kashmiris for its medicinal properties. Present study showed neem seed extract has potentially toxic ability that affect Total Haemocyte Count (THC) and Differential Haemocytes Count (DHC) in insect’s blood cells, of the housefly. A significant variation in haemolymph density was observed just after application, 30 minutes and 60 minutes post treatment in term of THC and DHC in comparison with novastar. The study strappingly acclaim use of neem seed extract as insecticide as compare to artificial insecticides.

Keywords: neem, Azadirachta indica, Musca domestica, differential haemocyte count (DHC), total haemocytes count (DHC), novastar

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1045 Advanced Eales’ Disease with Neovascular Glaucoma at First Presentation: Case Report

Authors: Mohammed A. Alfayyadh, Halla A. AlAbdulhadi, Mahdi H. Almubarak

Abstract:

Purpose: Eales’ disease is an idiopathic vasculitis that affects the peripheral retina. It is characterized by recurrent vitreous hemorrhage as a complication of retinal neovascularization. It is more prevalent in India and affects young males. Here we present a patient with neovascular glaucoma as a rare first presentation of Eales’ disease. Observations: This is a 24-year-old Indian gentleman, who complained of a sudden decrease in vision in the left eye over less than 24 hours, along with frontal headache and eye pain for the last three weeks. Ocular examination revealed peripheral retinal ischemia in the right eye, very high intraocular pressure, rubeosis iridis, vitreous hemorrhage and extensive retinal ischemia in the left eye, vascular sheathing and neovascularization in both eyes. Purified protein derivative skin test was positive. The patient was managed with anti-glaucoma, intravitreal anti-vascular endothelial growth factor and laser photocoagulation. Systemic steroids and anti-tuberculous therapy were also initiated. Conclusions: Neovascular glaucoma is an infrequent complication of Eales’ disease. However, the lack of early detection of the disease in the early stages might lead to such serious complication.

Keywords: case report, Eales’ disease, mycobacterium tuberculosis, neovascular glaucoma

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1044 The Origin Variability of the Iliolumbar Artery

Authors: Raid Hommady, Waseem Al-Talalwah, Shorok Al Dorazi, Roger Soames

Abstract:

The iliolumbar artery is a regular branch of posterior division of the internal iliac artery. The present study investigate 82 specimens to identify the origin of iliolumbar artery. The present study targets the sciatic nerve root supply from iliolumbar artery based on its origin and course. In present study, the ililumbar artery arose from the posterior division of internal iliac artery in 52.2%. In few cases, it arose from dorsomedial aspect of the internal iliac artery in 28.8%. In few cases, the iliolumbar artery arose from the dorsal aspects of the internal iliac artery as well as from the common and external iliac artery 1.7%. Also, the iliolumbar artery arose from the sciatic artery as well as from superior and inferior gluteal arteries in 5.1%. Conversely, it found to be congenital absent in 8.5%. Therefore, the posterior trunk of the internal iliac artery is the most common origin of the iliolumbar artery. With the origin variability of the iliolumbar artery, there is a vascular supply variability of the lumbosacral trunk and sacral root of sciatic nerve. The iliolumbar artery provides vascular supply for lumbosacral trunk 57.3% in whereas the sacral root in 5.1%. As a result, surgeons should pay attention to these variations to decrease iatrogenic fault.

Keywords: iliolumbar, sciatic artery, internal iliac, external iliac, posterior division

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1043 Ecotourism Development in Ikogosi Warmspring, Nigeria: Implications on Its Floristic Composition and Structure

Authors: Oluwatobi Emmanuel Olaniyi, Babafemi George Ogunjemite

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The high rate of infrastructural development in Ikogosi warm spring towards harnessing her great ecotourism potentials calls for a serious concern, as more forest areas are been opened up for public access and the landscape is modified. On this note, we investigated the implication of ecotourism development on the floristic composition and forest structure in Ikogosi. The study aimed at identifying the past and present status of infrastructural development, assessing and comparing the floristic composition and structure of the built- up/ recreational areas and undisturbed forested areas, to infer on the impact of ecotourism development on the study site. We conducted stakeholder interview and field observation to identify the past and present status of infrastructural development respectively. A total of ten quadrants were employed in the vegetation assessment to characterize the woody tree species composition, diameter at breast height and height, to obtain mean indices characterizing each part of the site. These indices were compared using T – test analysis. A total of 49 different woody tree species distributed in 21 families were identified in the built-in/ recreational areas while 67 different woody tree species belonging to 25 families were recorded in the undeveloped forested areas. Although, the latter has a higher mean diameter at breast height of woody trees, it was not significantly different from the former (T-test = -0.74, p = 0.46). On the contrary, the built-up area had a higher mean trees height than the undeveloped areas, but the difference was not statistically significant (T-test= 1.04, p = 0.30). Despite these, the slight reduction in richness and diversity of the woody tree species in the built- up/ recreational areas implies mitigating the negative effects of infrastructural development on the warm spring's vegetation.

Keywords: ecosystem services, forest structure, vegetation assessment, warm-spring

Procedia PDF Downloads 511
1042 Determinant Factor of Farm Household Fruit Tree Planting: The Case of Habru Woreda, North Wollo

Authors: Getamesay Kassaye Dimru

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The cultivation of fruit tree in degraded areas has two-fold importance. Firstly, it improves food availability and income, and secondly, it promotes the conservation of soil and water improving, in turn, the productivity of the land. The main objectives of this study are to identify the determinant of farmer's fruit trees plantation decision and to major fruit production challenges and opportunities of the study area. The analysis was made using primary data collected from 60 sample household selected randomly from the study area in 2016. The primary data was supplemented by data collected from a key informant. In addition to the descriptive statistics and statistical tests (Chi-square test and t-test), a logit model was employed to identify the determinant of fruit tree plantation decision. Drought, pest incidence, land degradation, lack of input, lack of capital and irrigation schemes maintenance, lack of misuse of irrigation water and limited agricultural personnel are the major production constraints identified. The opportunities that need to further exploited are better access to irrigation, main road access, endowment of preferred guava variety, experience of farmers, and proximity of the study area to research center. The result of logit model shows that from different factors hypothesized to determine fruit tree plantation decision, age of the household head accesses to market and perception of farmers about fruits' disease and pest resistance are found to be significant. The result has revealed important implications for the promotion of fruit production for both land degradation control and rehabilitation and increasing the livelihood of farming households.

Keywords: degradation, fruit, irrigation, pest

Procedia PDF Downloads 238
1041 Using Deep Learning Real-Time Object Detection Convolution Neural Networks for Fast Fruit Recognition in the Tree

Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

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Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

Procedia PDF Downloads 422
1040 Non-Invasive Characterization of the Mechanical Properties of Arterial Walls

Authors: Bruno RamaëL, GwenaëL Page, Catherine Knopf-Lenoir, Olivier Baledent, Anne-Virginie Salsac

Abstract:

No routine technique currently exists for clinicians to measure the mechanical properties of vascular walls non-invasively. Most of the data available in the literature come from traction or dilatation tests conducted ex vivo on native blood vessels. The objective of the study is to develop a non-invasive characterization technique based on Magnetic Resonance Imaging (MRI) measurements of the deformation of vascular walls under pulsating blood flow conditions. The goal is to determine the mechanical properties of the vessels by inverse analysis, coupling imaging measurements and numerical simulations of the fluid-structure interactions. The hyperelastic properties are identified using Solidworks and Ansys workbench (ANSYS Inc.) solving an optimization technique. The vessel of interest targeted in the study is the common carotid artery. In vivo MRI measurements of the vessel anatomy and inlet velocity profiles was acquired along the facial vascular network on a cohort of 30 healthy volunteers: - The time-evolution of the blood vessel contours and, thus, of the cross-section surface area was measured by 3D imaging angiography sequences of phase-contrast MRI. - The blood flow velocity was measured using a 2D CINE MRI phase contrast (PC-MRI) method. Reference arterial pressure waveforms were simultaneously measured in the brachial artery using a sphygmomanometer. The three-dimensional (3D) geometry of the arterial network was reconstructed by first creating an STL file from the raw MRI data using the open source imaging software ITK-SNAP. The resulting geometry was then transformed with Solidworks into volumes that are compatible with Ansys softwares. Tetrahedral meshes of the wall and fluid domains were built using the ANSYS Meshing software, with a near-wall mesh refinement method in the case of the fluid domain to improve the accuracy of the fluid flow calculations. Ansys Structural was used for the numerical simulation of the vessel deformation and Ansys CFX for the simulation of the blood flow. The fluid structure interaction simulations showed that the systolic and diastolic blood pressures of the common carotid artery could be taken as reference pressures to identify the mechanical properties of the different arteries of the network. The coefficients of the hyperelastic law were identified using Ansys Design model for the common carotid. Under large deformations, a stiffness of 800 kPa is measured, which is of the same order of magnitude as the Young modulus of collagen fibers. Areas of maximum deformations were highlighted near bifurcations. This study is a first step towards patient-specific characterization of the mechanical properties of the facial vessels. The method is currently applied on patients suffering from facial vascular malformations and on patients scheduled for facial reconstruction. Information on the blood flow velocity as well as on the vessel anatomy and deformability will be key to improve surgical planning in the case of such vascular pathologies.

Keywords: identification, mechanical properties, arterial walls, MRI measurements, numerical simulations

Procedia PDF Downloads 319
1039 Effect of Peg-6000-induced Drought Stress on the Germination of Moringa Stenopetala Seeds

Authors: Khater Nadia, Garah Kenza

Abstract:

Moringa stenopetala is a rapidly growing, unappreciated tree regarded as the "miracle tree" for its food, feed, and medicinal benefits. It appears to be a versatile and promising species for use under changing conditions. To evaluate the effect of water stress on germination seeds of M. stenopetala, three different concentrations PEG- 6000 (4, 8, and 12 per cent) along with a control in a factorial experiment based on a completely randomized design with five replications. The results revealed that water potential significantly reduced germination rate (82.5%) and average germination time. Germination speed in T3 by 93%, kinetics germination in T2 (39), germination index in T2 (102) and germination vigor index in T2 (91.25) were increased in the osmotic potential of PEG solution. By following these steps, we can improve the chances of successful germination of M. stenopetala seeds under water stress conditions

Keywords: moringa stenopetala, PEG, water stress, rate

Procedia PDF Downloads 13