Search results for: distance constraints

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

Abstract:

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

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

Procedia PDF Downloads 27

Authors: Mary Hanhoun, Jilla Bamarni, Anne-Sophie Bougard

Abstract:

INSPIR’ECO is a 18-month research and innovation project that aims to specify and develop a tool to offer new services for industrials and territorial planners/managers based on Industrial Ecology Principles. This project is carried out on the territory of Salaise Sablons and the services are designed to be deployed on other territories. Salaise-Sablons area is located in the limit of 5 departments on a major European economic axis multimodal traffic (river, rail and road). The perimeter of 330 ha includes 90 hectares occupied by 20 companies, with a total of 900 jobs, and represents a significant potential basin of development. The project involves five multi-disciplinary partners (Syndicat Mixte INSPIRA, ENGIE, IDEEL, IDEAs Laboratory and TREDI). INSPIR’ECO project is based on the principles that local stakeholders need services to pool, share their activities/equipment/purchases/materials. These services aims to : 1. initiate and promote exchanges between existing companies and 2. identify synergies between pre-existing industries and future companies that could be implemented in INSPIRA. These eco-industrial synergies can be related to: the recovery / exchange of industrial flows (industrial wastewater, waste, by-products, etc.); the pooling of business services (collective waste management, stormwater collection and reuse, transport, etc.); the sharing of equipments (boiler, steam production, wastewater treatment unit, etc.) or resources (splitting jobs cost, etc.); and the creation of new activities (interface activities necessary for by-product recovery, development of products or services from a newly identified resource, etc.). These services are based on IT tool used by the interested local stakeholders that intends to allow local stakeholders to take decisions. Thus, this IT tool: - include an economic and environmental assessment of each implantation or pooling/sharing scenarios for existing or further industries; - is meant for industrial and territorial manager/planners - is designed to be used for each new industrial project. - The specification of the IT tool is made through an agile process all along INSPIR’ECO project fed with: - Users expectations thanks to workshop sessions where mock-up interfaces are displayed; - Data availability based on local and industrial data inventory. These input allow to specify the tool not only with technical and methodological constraints (notably the ones from economic and environmental assessments) but also with data availability and users expectations. A feedback on innovative resource management initiatives in port areas has been realized in the beginning of the project to feed the designing services step.

Keywords: development opportunities, INSPIR’ECO, INSPIRA, industrial ecology, planification, synergy identification

Procedia PDF Downloads 145

Authors: Constantin Z. Leshan

Abstract:

Hole Vacuum theory is based on discontinuous spacetime that contains vacuum holes. Vacuum holes can explain gravitation, some laws of quantum mechanics and allow teleportation of matter. All massive bodies emit a flux of holes which curve the spacetime; if we increase the concentration of holes, it leads to length contraction and time dilation because the holes do not have the properties of extension and duration. In the limited case when space consists of holes only, the distance between every two points is equal to zero and time stops - outside of the Universe, the extension and duration properties do not exist. For this reason, the vacuum hole is the only particle in physics capable of describing gravitation using its own properties only. All microscopic particles must 'jump' continually and 'vibrate' due to the appearance of holes (impassable microscopic 'walls' in space), and it is the cause of the quantum behavior. Vacuum holes can explain the entanglement, non-locality, wave properties of matter, tunneling, uncertainty principle and so on. Particles do not have trajectories because spacetime is discontinuous and has impassable microscopic 'walls' due to the simple mechanical motion is impossible at small scale distances; it is impossible to 'trace' a straight line in the discontinuous spacetime because it contains the impassable holes. Spacetime 'boils' continually due to the appearance of the vacuum holes. For teleportation to be possible, we must send a body outside of the Universe by enveloping it with a closed surface consisting of vacuum holes. Since a material body cannot exist outside of the Universe, it reappears instantaneously in a random point of the Universe. Since a body disappears in one volume and reappears in another random volume without traversing the physical space between them, such a transportation method can be called teleportation (or Hole Teleportation). It is shown that Hole Teleportation does not violate causality and special relativity due to its random nature and other properties. Although Hole Teleportation has a random nature, it can be used for colonization of extrasolar planets by the help of the method called 'random jumps': after a large number of random teleportation jumps, there is a probability that the spaceship may appear near a habitable planet. We can create vacuum holes experimentally using the method proposed by Descartes: we must remove a body from the vessel without permitting another body to occupy this volume.

Keywords: border of the Universe, causality violation, perfect isolation, quantum jumps

Procedia PDF Downloads 404

Authors: Evan Lowhorn, Rocio Alba-Flores

Abstract:

The purpose of this work is to develop a method for classifying hand signals and using the output in a drone control algorithm. To achieve this, methods based on Convolutional Neural Networks (CNN) were applied. CNN's are a subset of deep learning, which allows grid-like inputs to be processed and passed through a neural network to be trained for classification. This type of neural network allows for classification via imaging, which is less intrusive than previous methods using biosensors, such as EMG sensors. Classification CNN's operate purely from the pixel values in an image; therefore they can be used without additional exteroceptive sensors. A development bench was constructed using a desktop computer connected to a high-definition webcam mounted on a scissor arm. This allowed the camera to be pointed downwards at the desk to provide a constant solid background for the dataset and a clear detection area for the user. A MATLAB script was created to automate dataset image capture at the development bench and save the images to the desktop. This allowed the user to create their own dataset of 12,000 images within three hours. These images were evenly distributed among seven classes. The defined classes include forward, backward, left, right, idle, and land. The drone has a popular flip function which was also included as an additional class. To simplify control, the corresponding hand signals chosen were the numerical hand signs for one through five for movements, a fist for land, and the universal “ok” sign for the flip command. Transfer learning with PyTorch (Python) was performed using a pre-trained 18-layer residual learning network (ResNet-18) to retrain the network for custom classification. An algorithm was created to interpret the classification and send encoded messages to a Ryze Tello drone over its 2.4 GHz Wi-Fi connection. The drone’s movements were performed in half-meter distance increments at a constant speed. When combined with the drone control algorithm, the classification performed as desired with negligible latency when compared to the delay in the drone’s movement commands.

Keywords: classification, computer vision, convolutional neural networks, drone control

Procedia PDF Downloads 190

Authors: Ola Elfmark, Lars M. Bardal, Luca Oggiano, H˚avard Myklebust

Abstract:

Team pursuit is a relatively new event in international long track speed skating. For a single speed skater the aerodynamic drag will account for up to 80% of the braking force, thus reducing the drag can greatly improve the performance. In a team pursuit the interactions between athletes in near proximity will also be essential, but is not well studied. In this study, systematic measurements of the aerodynamic drag, body posture and relative positioning of speed skaters have been performed in the low speed wind tunnel at the Norwegian University of Science and Technology, in order to investigate the aerodynamic interaction between two speed skaters. Drag measurements of static speed skaters drafting, leading, side-by-side, and dynamic drag measurements in a synchronized and unsynchronized movement at different distances, were performed. The projected frontal area was measured for all postures and movements and a blockage correction was performed, as the blockage ratio ranged from 5-15% in the different setups. The static drag measurements where performed on two test subjects in two different postures, a low posture and a high posture, and two different distances between the test subjects 1.5T and 3T where T being the length of the torso (T=0.63m). A drag reduction was observed for all distances and configurations, from 39% to 11.4%, for the drafting test subject. The drag of the leading test subject was only influenced at -1.5T, with the biggest drag reduction of 5.6%. An increase in drag was seen for all side-by-side measurements, the biggest increase was observed to be 25.7%, at the closest distance between the test subjects, and the lowest at 2.7% with ∼ 0.7 m between the test subjects. A clear aerodynamic interaction between the test subjects and their postures was observed for most measurements during static measurements, with results corresponding well to recent studies. For the dynamic measurements, the leading test subject had a drag reduction of 3% even at -3T. The drafting showed a drag reduction of 15% when being in a synchronized (sync) motion with the leading test subject at 4.5T. The maximal drag reduction for both the leading and the drafting test subject were observed when being as close as possible in sync, with a drag reduction of 8.5% and 25.7% respectively. This study emphasize the importance of keeping a synchronized movement by showing that the maximal gain for the leading and drafting dropped to 3.2% and 3.3% respectively when the skaters are in opposite phase. Individual differences in technique also appear to influence the drag of the other test subject.

Keywords: aerodynamic interaction, drag force, frontal area, speed skating

Procedia PDF Downloads 118

Authors: Mariam Shalaby, Kayla Krause, Raisha Ismail, Daniel George

Abstract:

Introduction: The Pennsylvania State College of Medicine Refugee Initiative is a student-run organization that works with eleven Syrian and Congolese refugee families. Since 2016, it has used grant funding to make weekly produce purchases at a local market, provide tutoring services, and develop trusting relationships. This case study explains how the Refugee Initiative shifted focus to face new challenges due to the COVID-19 pandemic in 2020. Methodology: When refugees who had previously attained stability found themselves unable to pay the bills, the organization shifted focus from food security to direct assistance such as applying for unemployment compensation since many had recently lost jobs. When refugee families additionally struggled to access hygiene supplies, funding was redirected to purchase them. Funds were also raised from the community to provide financial relief from unpaid rent and bills. Findings: Systemic challenges were encountered in navigating federal/state unemployment and social welfare systems, and there was a conspicuous absence of affordable, language-accessible assistance that could help refugees. Finally, as struggling public schools failed to maintain adequate English as a Second Language (ESL) education, the group’s tutoring services were hindered by social distancing and inconsistent access to distance-learning platforms. Conclusion: Ultimately, the pandemic highlighted that a charity-based arrangement is helpful but not sustainable, and challenges persist for refugee families. Based on the Refugee Initiative's experiences over the past year of the COVID-19 pandemic, several needs must be addressed to aid refugee families at this time, including: increased access to affordable and language-accessible social services, educational resources, and simpler options for grant-based financial assistance. Interventions to increase these resources will aid refugee families in need in Central Pennsylvania and internationally

Keywords: COVID-19, health, pandemic, refugees

Procedia PDF Downloads 107

Authors: Chi-Wai Kan, Kam-Hong Chau, Ho-Shing Law

Abstract:

Wicking property is important for textile finishing and wears comfort. Good wicking properties can ensure uniformity and efficiency of the textiles treatment. In view of wear comfort, quick wicking fabrics facilitate the evaporation of sweat. Therefore, the wetness sensation of the skin is minimised to prevent discomfort. The testing method for vertical wicking was standardised by the American Association of Textile Chemists and Colorists (AATCC) in 2011. The traditional vertical wicking test involves human error to observe fast changing and/or unclear wicking height. This study introduces optoelectronic devices to achieve an automatic Vertical Wicking Tester (VWT) and reduce human error. The VWT can record the wicking time and wicking height of samples. By reducing the difficulties of manual judgment, the reliability of the vertical wicking experiment is highly increased. Furthermore, labour is greatly decreased by using the VWT. The automatic measurement of the VWT has optoelectronic devices to trace the liquid wicking with a simple operation procedure. The optoelectronic devices detect the colour difference between dry and wet samples. This allows high sensitivity to a difference in irradiance down to 10 μW/cm². Therefore, the VWT is capable of testing dark fabric. The VWT gives a wicking distance (wicking height) of 1 mm resolution and a wicking time of one-second resolution. Acknowledgment: This is a research project of HKRITA funded by Innovation and Technology Fund (ITF) with title “Development of an Automatic Measuring System for Vertical Wicking” (ITP/055/20TP). Author would like to thank the financial support by ITF. Any opinions, findings, conclusions or recommendations expressed in this material/event (or by members of the project team) do not reflect the views of the Government of the Hong Kong Special Administrative Region, the Innovation and Technology Commission or the Panel of Assessors for the Innovation and Technology Support Programme of the Innovation and Technology Fund and the Hong Kong Research Institute of Textiles and Apparel. Also, we would like to thank the support and sponsorship from Lai Tak Enterprises Limited, Kingis Development Limited and Wing Yue Textile Company Limited.

Keywords: AATCC method, comfort, textile measurement, wetness sensation

Procedia PDF Downloads 81

Authors: Hiripurage Mallika Sandamali Dissanayaka

Abstract:

Butterflies are found everywhere on Earth, helping flowering plants reproduce through pollination. Wetlands perform many valuable functions such as providing wildlife habitat. Diyasaru Wetland Park was chosen as the study site. It is located in a highly urbanized area of Sri Jayawardenepura Kotte, Sri Lanka. A distribution map was prepared to increase butterfly habitat in the urbanized area, and research was conducted to determine the most suitable sections for using it. As this wetland has footpaths for walking, line transect surveys were used to mark species within the sampling area, and directly observed species were recorded. All data collection was done from 0900 to 1200 hours and 1300 to 1600 hours and fieldwork was done from 11 February 2020 to 20 January 2021. ED binoculars (10.5x45), DSLR cameras (Canon EOS/EFS5 mm 3.5-5.6), and Garmin GPS (Etrex 10) were used to observe butterfly species, identify locations, and take photographs as evidence. Analyzing their habitats using GIS (ArcGIS Pro) to identify their distribution within the park premises, the distribution density of the known size of the population was calculated for each point by kernel density, and local similarity values were calculated for each pair of corresponding features through hotspot analysis, and cell values were determined by inverse distance weighting (IDW) using a linearly weighted combination of a set of sample points. According to the maps prepared to predict the distribution of butterflies in this park, the high level of distribution or favorable areas were near flower gardens and meadows, but some individual species prefer habitats that are more suitable for their life activities, so they live in other areas. Sixty-six (66) species belonging to six (6) families have been recorded in the premises. Sixty (60) species of least concern (LC), two (2) near threatened (NT), and four (4) vulnerable (VU) species have been recorded, and several new species, such as Plum Judy (Abisara echerius), were reported. The outcome of the study will form the basis for decision-making by the Sri Lanka Land Development (SLLD) Corporation for the future development and maintenance of the park.

Keywords: wetland, Lepidoptera, habitat, urban, west

Procedia PDF Downloads 31

Authors: Tasnuba Binte Jamal, Khan Mahmud Amanat

Abstract:

Carbon Fiber-Reinforced Polymer (CFRP) composite materials have proven to have valuable properties and suitability to be used in the construction of new buildings and in upgrading the existing ones due to its effectiveness, ease of implementation and many more. In the present study, a numerical finite element investigation has been conducted using ANSYS 18.1 to study the behavior of square HSS AISC sections under eccentric compressive loading strengthened with CFRP materials. A three-dimensional finite element model for square HSS section using shell element was developed. Application of CFRP strengthening was incorporated in the finite element model by adding an additional layer of shell elements. Both material and geometric nonlinearities were incorporated in the model. The developed finite element model was applied to simulate experimental studies done by past researchers and it was found that good agreement exists between the current analysis and past experimental results, which established the acceptability and validity of the developed finite element model to carry out further investigation. Study was then focused on some selected non-compact AISC square HSS columns and the effects of number of CFRP layers, amount of eccentricities and cross-sectional geometry on the strength gain of those columns were observed. Load was applied at a distance equal to the column dimension and twice that of column dimension. It was observed that CFRP strengthening is comparatively effective for smaller eccentricities. For medium sized sections, strengthening tends to be effective at smaller eccentricities as well. For relatively large AISC square HSS columns, with increasing number of CFRP layers (from 1 to 3 layers) the gain in strength is approximately 1 to 38% to that of unstrengthened section for smaller eccentricities and slenderness ratio ranging from 27 to 54. For medium sized square HSS sections, effectiveness of CFRP strengthening increases approximately by about 12 to 162%. The findings of the present study provide a better understanding of the behavior of HSS sections strengthened with CFRP subjected to eccentric compressive load.

Keywords: CFRP strengthening, eccentricity, finite element model, square hollow section

Procedia PDF Downloads 122

Authors: Christian Lauter, Corin Reuter, Shuang Wu, Thomas Troester

Abstract:

Lightweight construction became more and more important over the last decades in several applications, e.g. in the automotive or aircraft sector. This is the result of economic and ecological constraints on the one hand and increasing safety and comfort requirements on the other hand. In the field of lightweight design, different approaches are used due to specific requirements towards the technical systems. The use of endless carbon fiber reinforced plastics (CFRP) offers the largest weight saving potential of sometimes more than 50% compared to conventional metal-constructions. However, there are very limited industrial applications because of the cost-intensive manufacturing of the fibers and production technologies. Other disadvantages of pure CFRP-structures affect the quality control or the damage resistance. One approach to meet these challenges is hybrid materials. This means CFRP and sheet metal are combined on a material level. Therefore, new opportunities for innovative process routes are realizable. Hybrid lightweight design results in lower costs due to an optimized material utilization and the possibility to integrate the structures in already existing production processes of automobile manufacturers. In recent and current research, the advantages of two-layered hybrid materials have been pointed out, i.e. the possibility to realize structures with tailored mechanical properties or to divide the curing cycle of the epoxy resin into two steps. Current research work at the Chair for Automotive Lightweight Design (LiA) at the Paderborn University focusses on production processes for fiber-metal-laminates. The aim of this work is the development and qualification of a large-scale production process for high-performance fiber-metal-laminates (FML) for industrial applications in the automotive or aircraft sector. Therefore, the prepreg-press-technology is used, in which pre-impregnated carbon fibers and sheet metals are formed and cured in a closed, heated mold. The investigations focus e.g. on the realization of short process chains and cycle times, on the reduction of time-consuming manual process steps, and the reduction of material costs. This paper gives an overview over the considerable steps of the production process in the beginning. Afterwards experimental results are discussed. This part concentrates on the influence of different process parameters on the mechanical properties, the laminate quality and the identification of process limits. Concluding the advantages of this technology compared to conventional FML-production-processes and other lightweight design approaches are carried out.

Keywords: composite material, fiber-metal-laminate, lightweight construction, prepreg-press-technology, large-series production

Procedia PDF Downloads 224

Authors: Zuyong Chen, Jianghao Wu, Yanlai Zhang

Abstract:

Flapping-wing micro aerial vehicle (FMAV) is a new type of aircraft by mimicking the flying behavior to that of small birds or insects. Comparing to the traditional fixed wing or rotor-type aircraft, FMAV only needs to control the motion of flapping wings, by changing the size and direction of lift to control the flight attitude. Therefore, its transmission system should be designed very compact. Lightweight design can effectively extend its endurance time, while engineering experience alone is difficult to simultaneously meet the requirements of FMAV for structural strength and quality. Current researches still lack the guidance of considering nonlinear factors of 3D printing material when carrying out topology optimization, especially for the tiny FMAV transmission system. The coupling of non-linear material properties and non-linear contact behaviors of FMAV transmission system is a great challenge to the reliability of the topology optimization result. In this paper, topology optimization design based on FEA solver package Altair Optistruct for the transmission system of FMAV manufactured by 3D Printing was carried out. Firstly, the isotropic constitutive behavior of the Ultraviolet (UV) Cureable Resin used to fabricate the structure of FMAV was evaluated and confirmed through tensile test. Secondly, a numerical computation model describing the mechanical behavior of FMAV transmission structure was established and verified by experiments. Then topology optimization modeling method considering non-linear factors were presented, and optimization results were verified by dynamic simulation and experiments. Finally, detail discussions of different load status and constraints were carried out to explore the leading factors affecting the optimization results. The contributions drawn from this article helpful for guiding the lightweight design of FMAV are summarizing as follow; first, a dynamic simulation modeling method used to obtain the load status is presented. Second, verification method of optimized results considering non-linear factors is introduced. Third, based on or can achieve a better weight reduction effect and improve the computational efficiency rather than taking multi-states into account. Fourth, basing on makes for improving the ability to resist bending deformation. Fifth, constraint of displacement helps to improve the structural stiffness of optimized result. Results and engineering guidance in this paper may shed lights on the structural optimization and light-weight design for future advanced FMAV.

Keywords: flapping-wing micro aerial vehicle, 3d printing, topology optimization, finite element analysis, experiment

Procedia PDF Downloads 155

Authors: Ariel Vilchez, Francisca Acevedo, Rodrigo Navia

Abstract:

The wound healing process can be accelerated and improved by the action of antioxidants such as curcumin (Cur) over the tissues; however, the efficacy of curcumin used through the digestive system is not enough to exploit its benefits. Electrospinning presents an alternative to carry curcumin directly to the wounds, and polyhydroxybutyrate (PHB) is proposed as the matrix to load curcumin owing to its biodegradable and biocompatible properties. PHB is among 150 types of Polyhydroxyalkanoates (PHAs) identified, it is a natural thermoplastic polyester produced by microbial fermentation obtained from microorganisms. The proposed objective is to develop electrospun bacterial PHB-based microfibers containing curcumin for possible biomedical applications. Commercial PHB was solved in Chloroform: Dimethylformamide (4:1) to a final concentration of 7% m/V. Curcumin was added to the polymeric solution at 1%, and 7% m/m regarding PHB. The electrospinning equipment (NEU-BM, China) with a rotary collector was used to obtain Cur-PHB fibers at different voltages and flow rate of the polymeric solution considering a distance of 20 cm from the needle to the collector. Scanning electron microscopy (SEM) was used to determine the diameter and morphology of the obtained fibers. Thermal stability was obtained from Thermogravimetric (TGA) analysis, and Fourier Transform Infrared Spectroscopy (FT-IR) was carried out in order to study the chemical bonds and interactions. A preliminary curcumin release to Phosphate Buffer Saline (PBS) pH = 7.4 was obtained in vitro and measured by spectrophotometry. PHB fibers presented an intact chemical composition regarding the original condition (dust) according to FTIR spectra, the diameter fluctuates between 0.761 ± 0.123 and 2.157 ± 0.882 μm, with different qualities according to their morphology. The best fibers in terms of quality and diameter resulted in sample 2 and sample 6, obtained at 0-10kV and 0.5 mL/hr, and 0-10kV and 1.5 mL/hr, respectively. The melting temperature resulted near 178 °C, according to the bibliography. The crystallinity of fibers decreases while curcumin concentration increases for the studied interval. The curcumin release reaches near 14% at 37 °C at 54h in PBS adjusted to a quasi-Fickian Diffusion. We conclude that it is possible to load curcumin in PHB to obtain continuous, homogeneous, and solvent-free microfibers by electrospinning. Between 0% and 7% of curcumin, the crystallinity of fibers decreases as the concentration of curcumin increases. Thus, curcumin enhances the flexibility of the obtained material. HPLC should be used in further analysis of curcumin release.

Keywords: antioxidant, curcumin, polyhydroxybutyrate, wound healing

Procedia PDF Downloads 112

Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

Abstract:

Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

Procedia PDF Downloads 68

Authors: Athanasia Petropoulou

Abstract:

While there is a common understanding that a person’s sex, gender, gender identity, and sexual orientation shape every stage of the migration experience, theories of international migration had until recently not been focused on exploring and incorporating a gender perspective in their analysis. In a similar vein, refugee law has long been the object of criticisms for failing to recognize and respond appropriately to women’s and sexual minorities’ experiences of persecution. The present analysis attempts to depict the challenges faced by the European Court of Human Rights (ECtHR) and U.S. courts when adjudicating in cases involving asylum claims with a gendered perspective. By providing a comparison between adjudicating strategies of international and national jurisdictions, the article aims to identify common or distinctive approaches in addressing gendered based claims. The paper argues that, despite the different nature of the judicial bodies and the different legal instruments applied respectively, judges face similar challenges in this context and often fail to qualify and address the gendered dimensions of asylum claims properly. The ECtHR plays a fundamental role in safeguarding human rights protection in Europe not only for European citizens but also for people fleeing violence, war, and dire living conditions. However, this role becomes more difficult to fulfill, not only because of the obvious institutional constraints but also because cases related to claims of asylum seekers concern a domain closely linked to State sovereignty. Amid the current “refugee crisis,” risk assessment performed by national authorities, like in the process of asylum determination, is shaped by wider geopolitical and economic considerations. The failure to recognize and duly address the gendered dimension of non - refoulement claims, one of the many shortcomings of these processes, is reflected in the decisions of the ECtHR. As regards U.S. case law, the study argues that U.S. courts either fail to apply any connection between asylum claims and their gendered dimension or tend to approach gendered based claims through the lens of the “political opinion” or “membership of a particular social group” reasons of fear of persecution. This exercise becomes even more difficult, taking into account that the U.S. asylum law inappropriately qualifies gendered-based claims. The paper calls for more sociologically informed decision-making practices and for a more contextualized and relational approach in the assessment of the risk of ill-treatment and persecution. Such an approach is essential for unearthing the gendered patterns of persecution and addressing effectively related claims, thus securing the human rights of asylum seekers.

Keywords: asylum, European court of human rights, gender, human rights, U.S. courts

Procedia PDF Downloads 94

Authors: Carmen Nechita

Abstract:

This research explores the world of Syrian refugee women living in Dresden and their efforts to reconstruct their lives in the state of Saxony in Germany. The focus is on the initial period of adjustment and understanding how refugee women use culture, family ties, and tradition to contest and rebuild new relationships with the host country. Faced with a new status as “the refugee”, women have to re-imagine their ethno-cultural identity in order to cope with life in Diaspora. In order to understand the coping mechanism and the displacement effects on Syrian women, interviews with twelve refugee women were conducted. Traumatic experiences of loss and oppression are at the core of their confessions. While gender violence, abuse and patriarchal framework shape their narratives, this research argues that there is a need to look at this from a cultural perspective and try to distance ourselves from the western paradigm. The way Syrian women refute and rebuild their national and ethno-cultural identity in order to negotiate for themselves new space within German borders is explored. Two discourses are bridged: one of multiculturalism and one of tradition in order to explain how Syrian women experience western notions of family, womanhood and spousal dynamics. The process is painful, traumatic and marked by feelings of low self-worth, but in the end, new codes emerge and these women come out more empowered. The paper includes the migration experience and explores the ways in which Syrian refugee women tend to tell their complex stories, and how they reconstruct their identity in a new territory while faced with a different culture that discriminates against them. During the research, four distinct phases in the acculturation period were identified: “the survival”, “the honeymoon period”, “the isolation period” and “the anger period”. Each phase is analyzed in order to understand what triggers them, how women migrate from one phase to another and what can be done to make the process easier. This paper contributes to the field of refugee studies by offering a thorough understanding of the initial phases of the acculturation process in the case of Syrian refugee women. The study examines the fleeing and settlement experience in order to understand the complex ways that refugee women cope with the traumatic experience of settlement in another country and in a different culture. *Almanya: The Arabic word for Germany.

Keywords: displacement, migration, refugee women, Syria

Procedia PDF Downloads 239

Authors: Nkechi V. Osuji

Abstract:

The use of blockchain to address the issue of climate change is increasingly a discourse among countries, industries, and stakeholders. For a long time, the European Union (EU) has been combating the issue of climate action in industries through sustainability programs. One of such programs is the EU monitoring reporting and verification (MRV) program of the EU ETS. However, the system has some key challenges and areas for improvement, which makes it inefficient. The main objective of the research is to look at how blockchain can be used to improve the inefficiency of the EU ETS program for the Danish energy industry with a focus on its monitoring and reporting framework. Applying empirical data from 13 semi-structured expert interviews, three case studies, and literature reviews, three outcomes are presented in the study. The first is on the current conditions and challenges of monitoring and reporting CO₂ emission trading. The second is putting into consideration if blockchain is the right fit to solve these challenges and how. The third stage looks at the factors that might affect the implementation of such a system and provides recommendations to mitigate these challenges. The first stage of the findings reveals that the monitoring and reporting of CO₂ emissions is a mandatory requirement by law for all energy operators under the EU ETS program. However, most energy operators are non-compliant with the program in reality, which creates a gap and causes challenges in the monitoring and reporting of CO₂ emission trading. Other challenges the study found out are the lack of transparency, lack of standardization in CO₂ accounting, and the issue of double-counting in the current system. The second stage of the research was guided by three case studies and requirement engineering (RE) to explore these identified challenges and if blockchain is the right fit to address them. This stage of the research addressed the main research question: how can blockchain be used for monitoring and reporting CO₂ emission trading in the energy industry. Through analysis of the study data, the researcher developed a conceptual private permissioned Hyperledger blockchain and elucidated on how it can address the identified challenges. Particularly, the smart contract of blockchain was highlighted as a key feature. This is because of its ability to automate, be immutable, and digitally enforce negotiations without a middleman. These characteristics are unique in solving the issue of compliance, transparency, standardization, and double counting identified. The third stage of the research presents technological constraints and a high level of stakeholder collaboration as major factors that might affect the implementation of the proposed system. The proposed conceptual model requires high-level integration with other technologies such as the Internet of Things (IoT) and machine learning. Therefore, the study encourages future research in these areas. This is because blockchain is continually evolving its technology capabilities. As such, it remains a topic of interest in research and development for addressing climate change. Such a study is a good contribution to creating sustainable practices to solve the global climate issue.

Keywords: blockchain, carbon emission trading, European Union emission trading system, monitoring and reporting

Procedia PDF Downloads 111

Authors: Faith Eweluegim Enahoro-Ofagbe, Alika Eke Joseph

Abstract:

Information on genetic variation within a population is crucial for utilizing heterozygosity for breeding programs that aim to improve crop species. The study was conducted to ascertain the genotypic similarities among twelve sugarcane (Saccharum officinarum) varieties to group them for purposes of hybridizations for cane yield improvement. The experiment was conducted at the University of Benin, Faculty of Agriculture Teaching and Research Farm, Benin City. Twelve sugarcane varieties obtained from National Cereals Research Institute, Badeggi, Niger State, Nigeria, were planted in three replications in a randomized complete block design. Each variety was planted on a five-row plot of 5.0 m in length. Data were collected on 12 agronomic traits, including; the number of millable cane, cane girth, internode length, number of male and female flowers (fuss), days to flag leaf, days to flowering, brix%, cane yield, and others. There were significant differences, according to the findings among the twelve genotypes for the number of days to flag leaf, number of male and female flowers (fuss), and cane yield. The relationship between the twelve sugarcane varieties was expressed using hierarchical cluster analysis. The twelve genotypes were grouped into three major clusters based on hierarchical classification. Cluster I had five genotypes, cluster II had four, and cluster III had three. Cluster III was dominated by varieties characterized by higher cane yield, number of leaves, internode length, brix%, number of millable stalks, stalk/stool, cane girth, and cane length. Cluster II contained genotypes with early maturity characteristics, such as early flowering, early flag leaf development, growth rate, and the number of female and male flowers (fuss). The maximum inter-cluster distance between clusters III and I indicated higher genetic diversity between the two groups. Hybridization between the two groups could result in transgressive recombinants for agronomically important traits.

Keywords: sugarcane, Saccharum officinarum, genotype, cluster analysis, principal components analysis

Procedia PDF Downloads 64

Authors: Jian Wu

Abstract:

Since a few years, some French companies have integrated CRS (corporate social responsibility) criteria in their variable remuneration plans to ‘restore a good working atmosphere’ and ‘preserve the natural environment’. These CSR criteria are based on concerns on environment protection, social aspects, and corporate governance. In June 2012, a report on this practice has been made jointly by ORSE (which means Observatory on CSR in French) and PricewaterhouseCoopers. Facing this initiative from the business world, we need to examine whether it has a real economic utility. We adopt a theoretical approach for our study. First, we examine the debate between the ‘orthodox’ point of view in economics and the CSR school of thought. The classical economic model asserts that in a capitalist economy, exists a certain ‘invisible hand’ which helps to resolve all problems. When companies seek to maximize their profits, they are also fulfilling, de facto, their duties towards society. As a result, the only social responsibility that firms should have is profit-searching while respecting the minimum legal requirement. However, the CSR school considers that, as long as the economy system is not perfect, there is no ‘invisible hand’ which can arrange all in a good order. This means that we cannot count on any ‘divine force’ which makes corporations responsible regarding to society. Something more needs to be done in addition to firms’ economic and legal obligations. Then, we reply on some financial theories and empirical evident to examine the sound foundation of CSR. Three theories developed in corporate governance can be used. Stakeholder theory tells us that corporations owe a duty to all of their stakeholders including stockholders, employees, clients, suppliers, government, environment, and society. Social contract theory tells us that there are some tacit ‘social contracts’ between a company and society itself. A firm has to respect these contracts if it does not want to be punished in the form of fine, resource constraints, or bad reputation. Legitime theory tells us that corporations have to ‘legitimize’ their actions toward society if they want to continue to operate in good conditions. As regards empirical results, we present a literature review on the relationship between the CSR performance and the financial performance of a firm. We note that, due to difficulties in defining these performances, this relationship remains still ambiguous despite numerous research works realized in the field. Finally, we are curious to know whether the integration of CSR criteria in variable remuneration plans – which is practiced so far in big companies – should be extended to other ones. After investigation, we note that two groups of firms have the greatest need. The first one involves industrial sectors whose activities have a direct impact on the environment, such as petroleum and transport companies. The second one involves companies which are under pressures in terms of return to deal with international competition.

Keywords: corporate social responsibility, corporate governance, variable remuneration, stakeholder theory

Procedia PDF Downloads 167

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder

Procedia PDF Downloads 278

Authors: Kibret Berhanu Getinet

Abstract:

Off-farm income diversification by farm rural households has gained the attention of researchers and policymakers due to the fact that agriculture failed to meet the needs of people in developing countries like Ethiopia. The objective of this study was to investigate income diversification strategies into off-farm activities among rural households in Hawassa Zuria Woreda, Sidama National Regional State, Ethiopia. The study used primary and secondary data sources for the primary data collection questionnaire employed as a data collection instrument. A multistage sampling technique was used to collect data from a total of 197 sample households from four kebeles of the study area. Descriptive statistics, as well as econometrics methods of data analysis, were employed. The descriptive statistics result indicates that the majority of sample rural households (68.53 %) have engaged in off-farm income diversification activities while the remaining 31.47% of households did not participate in the diversification in the study area. The choice of participants among the strategies indicates that 6.60% of respondents participated in off-farm wage employment, 30.46% participated in off-farm self-employment, and about 31.47% of them participated in both off-farm wage employment. The study revealed that the share of off-farm income in total annual earnings of households was about 48.457%, and thus, the off-farm diversification significantly contributes to the rural household income. Moreover, binary and multinomial logistic regression models were employed to identify factors that affect the participation and the choices of the off-farm income diversification strategies, respectively. The binary logit model result indicated that agro-ecological zone, education status of the households, available technical skills of the household, household saving, total livestock owned by the households, access to electricity, road access and being married of household head were significant and positively affected the chance of diversification in off-farm activities while the on-farm income of households is negatively affected the chance of diversification. Similarly, the multinomial logistic regression model estimate revealed that agroecological zone, on-farm income, available technical skills, household savings, and access to electricity are positively related and significantly influenced the household’s choice of employment into off-farm wage employment. The off-farm self-employment diversification choice is significantly influenced by on-farm income, available technical skills, household savings, total livestock owned, and access to electricity. Moreover, the result showed that the factors that affect the choice of farm households to engage in both off-farm wage and self-employment are ecological zone, education status, on-farm income, available technical skills, household own saving, market access, total livestock owned, access to electricity and road access. Thus, due attention should be given to addressing the demographic, socio-economic, and institutional constraints to strengthen off-farm income diversification strategies to improve the income of rural households.

Keywords: off-farm, incoem, diversification, logit model

Procedia PDF Downloads 37

Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

Abstract:

The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

Procedia PDF Downloads 113

Authors: Ahmad Lutfi, Nikolas Dhega

Abstract:

The Malala deposit in northwest Sulawesi is the only known porphyry molybdenum and the only source for rhenium, occurrence in Indonesia. The neural network method produces results that correspond very closely to those of the knowledge-based fuzzy logic method and weights of evidence method. This method required data of solid geology, regional faults, airborne magnetic, gamma-ray survey data and GIS data. This interpretation of the network output fits with the intuitive notion that a prospective area has characteristics that closely resemble areas known to contain mineral deposits. Contrasts with the weights of evidence and fuzzy logic methods, where, for a given grid location, each input-parameter value automatically results in an increase in the prospective estimated. Malala District indicated molybdenum anomalies in stream sediments from in excess of 15 km2 were obtained, including the Takudan Fault as most prominent structure with striking 40̊ to 60̊ over a distance of about 30 km and in most places weakly at anomaly B, developed over an area of 4 km2, with a ‘shell’ up to 50 m thick at the intrusive contact with minor mineralization occurring in the Tinombo Formation. Series of NW trending, steeply dipping fracture zones, named the East Zone has an estimated resource of 100 Mt at 0.14% MoS2 and minimum target of 150 Mt 0.25%. The Malala porphyries occur as stocks and dykes with predominantly granitic, with fluorine-poor class of molybdenum deposits and belongs to the plutonic sub-type. Unidirectional solidification textures consisting of subparallel, crenulated layers of quartz that area separated by layers of intrusive material textures. The deuteric nature of the molybdenum mineralization and the dominance of carbonate alteration.The nature of the Stage I with alteration barren quartz K‐feldspar; and Stage II with alteration quartz‐K‐feldspar‐apatite-molybdenite veins combined with the presence of disseminated molybdenite with primary biotite in the host intrusive.

Keywords: molybdenite, Malala, porphyries, anomaly B

Procedia PDF Downloads 138

Authors: Maria Angela Bedini, Fabio Bronzini

Abstract:

The Italian experiences, positive and negative, of the post-earthquake are conditioned by long times and structural bureaucratic constraints, also motivated by the attempt to contain mafia infiltration and corruption. The transition from the operational phase of the emergency to the planning phase of the reconstruction project is thus hampered by a series of inefficiencies and delays, incompatible with the need for rapid recovery of the territories in crisis. In fact, intervening in areas affected by seismic events means at the same time associating the reconstruction plan with an urban and territorial rehabilitation project based on strategies and tools in which prevention and safety play a leading role in the regeneration of territories in crisis and the return of the population. On the contrary, the earthquakes that took place in Italy have instead further deprived the territories affected of the minimum requirements for habitability, in terms of accessibility and services, accentuating the depopulation process, already underway before the earthquake. The objective of this work is to address with implementing and programmatic tools the procedures and strategies to be put in place, today and in the future, in Italy and abroad, to face the challenge of the reconstruction of activities, sociality, services, risk mitigation: a protocol of operational intentions and firm points, open to a continuous updating and implementation. The methodology followed is that of the comparison in a synthetic form between the different Italian experiences of the post-earthquake, based on facts and not on intentions, to highlight elements of excellence or, on the contrary, damage. The main results obtained can be summarized in technical comparison cards on good and bad practices. With this comparison, we intend to make a concrete contribution to the reconstruction process, certainly not only related to the reconstruction of buildings but privileging the primary social and economic needs. In this context, the recent instrument applied in Italy of the strategic urban and territorial SUM (Minimal Urban Structure) and the strategic monitoring process become dynamic tools for supporting reconstruction. The conclusions establish, by points, a protocol of interventions, the priorities for integrated socio-economic strategies, multisectoral and multicultural, and highlight the innovative aspects of 'inversion' of priorities in the reconstruction process, favoring the take-off of 'accelerator' interventions social and economic and a more updated system of coexistence with risks. In this perspective, reconstruction as a necessary response to the calamitous event can and must become a unique opportunity to raise the level of protection from risks and rehabilitation and development of the most fragile places in Italy and abroad.

Keywords: an operational protocol for reconstruction, operational priorities for coexistence with seismic risk, social and economic interventions accelerators of building reconstruction, the difficult post-earthquake reconstruction in Italy

Procedia PDF Downloads 108

Authors: Niyti, Aman Deep, Rajesh Kharab, Sahila Chopra, Raj. K. Gupta

Abstract:

Relatively long-lived transactinide elements (i.e., elements with atomic number Z≥104) up to Z = 108 have been produced in nuclear reactions between low Z projectiles (C to Al) and actinide targets. Cross sections have been observed to decrease steeply with increasing Z. Recently, production cross sections of several picobarns have been reported for comparatively neutron-rich nuclides of 112 through 118 produced via hot fusion reactions with 48Ca and actinide targets. Some of those heavy nuclides are reported to have lifetimes on the order of seconds or longer. The relatively high cross sections in these hot fusion reactions are not fully understood and this has renewed interest in systematic studies of heavy-ion reactions with actinide targets. The main aim of this work is to understand the dynamics hot fusion reactions 18O+ 248Cm and 22Ne+244Pu (carried out at RIKEN and TASCA respectively) using the collective clusterization technique, carried out by undertaking the decay of the compound nucleus 266Rf∗ into 4n, 5n and 6n neutron evaporation channels. Here we extend our earlier study of the excitation functions (EFs) of 266Rf∗, formed in fusion reaction 18O+248Cm, based on Dynamical Cluster-decay Model (DCM) using the pocket formula for nuclear proximity potential, to the use of other nuclear interaction potentials derived from Skyrme energy density formalism (SEDF) based on semiclassical extended Thomas Fermi (ETF) approach and also study entrance channel effects by considering the synthesis of 266Rf* in 22Ne+244Pu reaction. The Skyrme forces used are the old force SIII, and new forces GSkI and KDE0(v1). Here, the EFs for the production of 260Rf, 261Rf and 262Rf isotope via 6n, 5n and 4n decay channel from the 266Rf∗ compound nucleus are studied at Elab = 88.2 to 125 MeV, including quadrupole deformations β2i and ‘hot-optimum’ orientations θi. The calculations are made within the DCM where the neck-length ∆R is the only parameter representing the relative separation distance between two fragments and/or clusters Ai which assimilates the neck formation effects.

Keywords: entrance channel effects, fusion reactions, skyrme force, superheavy nucleus

Procedia PDF Downloads 235

Authors: Martial Amou

Abstract:

This study was carried out to assess the situation of households’ livelihood under a changing climate pattern in the Zio district of Togo, West Africa. The study examined three important aspects: (i) assessment of households’ livelihood situation under a changing climate pattern, (ii) farmers’ perception and understanding of local climate change, (iii) determinants of adaptation strategies undertaken in cropping pattern to climate change. To this end, secondary sources of data, and survey data collected from 235 farmers in four villages in the study area were used. Adapted conceptual framework from Sustainable Livelihood Framework of DFID, two steps Binary Logistic Regression Model and descriptive statistics were used in this study as methodological approaches. Based on Sustainable Livelihood Approach (SLA), various factors revolving around the livelihoods of the rural community were grouped into social, natural, physical, human, and financial capital. Thus, the study came up that households’ livelihood situation represented by the overall livelihood index in the study area (34%) is below the standard average households’ livelihood security index (50%). The natural capital was found as the poorest asset (13%) and this will severely affect the sustainability of livelihood in the long run. The result from descriptive statistics and the first step regression (selection model) indicated that most of the farmers in the study area have clear understanding of climate change even though they do not have any idea about greenhouse gases as the main cause behind the issue. From the second step regression (output model) result, education, farming experience, access to credit, access to extension services, cropland size, membership of a social group, distance to the nearest input market, were found to be the significant determinants of adaptation measures undertaken in cropping pattern by farmers in the study area. Based on the result of this study, recommendations are made to farmers, policy makers, institutions, and development service providers in order to better target interventions which build, promote or facilitate the adoption of adaptation measures with potential to build resilience to climate change and then improve rural livelihood.

Keywords: climate change, rural livelihood, cropping pattern, adaptation, Zio District

Procedia PDF Downloads 306

Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar

Abstract:

Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.

Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers

Procedia PDF Downloads 76

Authors: Mochamad Nuruz Zaman, Mangatur Rudolf Nababan, M. A. Djatmika

Abstract:

Both society and education areas teach to have good communication for building the interpersonal skills up. Everyone has the capacity to understand something new, either well comprehension or worst understanding. Worst understanding makes the language errors when the interactions are done by someone in the first meeting, and they do not know before it because of distance area. “The Space between Us” movie delivers the love-adventure story between Mars Boy and Earth Girl. They are so many missing conversations because of the different climate and environment. As the moviegoer also must be focused on the subtitle in order to enjoy well the movie. Furthermore, Indonesia subtitle and English conversation on the movie still have overlapping understanding in the translation. Translation hereby consists of source language -SL- (English conversation) and target language -TL- (Indonesia subtitle). These research gap above is formulated in research question by how the language errors happened in that movie and their effects on translation quality which is deepest analyzed by translation study toward discourse analysis approach. The research goal is to expand the language errors and their translation qualities in order to create a good atmosphere in movie media. The research is studied by embedded research in qualitative design. The research locations consist of setting, participant, and event as focused determined boundary. Sources of datum are “The Space between Us” movie and informant (translation quality rater). The sampling is criterion-based sampling (purposive sampling). Data collection techniques use content analysis and questioner. Data validation applies data source and method triangulation. Data analysis delivers domain, taxonomy, componential, and cultural theme analysis. Data findings on the language errors happened in the movie are referential, register, society, textual, receptive, expressive, individual, group, analogical, transfer, local, and global errors. Data discussions on their effects to translation quality are concentrated by translation techniques on their data findings; they are amplification, borrowing, description, discursive creation, established equivalent, generalization, literal, modulation, particularization, reduction, substitution, and transposition.

Keywords: discourse analysis, language errors, The Space between Us movie, translation techniques, translation quality instruments

Procedia PDF Downloads 201

Authors: Shahnam Behnam Malekzadeh, Ian Kerr, Tyson Kaempffer, Teague Harper, Andrew Watson

Abstract:

The Site C Hydroelectric dam is currently being constructed in north-eastern British Columbia on sub-horizontal sedimentary strata that dip approximately 15 meters from one bank of the Peace River to the other. More than 615 pressure sensors (Vibrating Wire Piezometers) have been installed on bedding planes (BPs) since construction began, with over 80 more planned before project completion. These pressure measurements are essential to monitor the stability of the rock foundation during and after construction and for dam safety purposes. BPs are identified by their clay gouge infilling, which varies in thickness from less than 1 to 20 mm and can be challenging to identify as the core drilling process often disturbs or washes away the gouge material. Without the use of depth predictions from nearby boreholes, stratigraphic markers, and downhole geophysical data, it is difficult to confidently identify BP targets for the sensors. In this paper, a Case-Based Reasoning (CBR) method was used to develop an empirical model called the Bedding Plane Elevation Prediction (BPEP) to help geologists and geotechnical engineers to predict geological features and bedding planes at new locations in a fast and accurate manner. To develop CBR, a database was developed based on 64 pressure sensors already installed on key bedding planes BP25, BP28, and BP31 on the Right Bank, including bedding plane elevations and coordinates. Thirteen (20%) of the most recent cases were selected to validate and evaluate the accuracy of the developed model, while the similarity was defined as the distance between previous cases and recent cases to predict the depth of significant BPs. The average difference between actual BP elevations and predicted elevations for above BPs was ±55cm, while the actual results showed that 69% of predicted elevations were within ±79 cm of actual BP elevations while 100% of predicted elevations for new cases were within ±99cm range. Eventually, the actual results will be used to develop the database and improve BPEP to perform as a learning machine to predict more accurate BP elevations for future sensor installations.

Keywords: case-based reasoning, geological feature, geology, piezometer, pressure sensor, core logging, dam construction

Procedia PDF Downloads 62

Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

Procedia PDF Downloads 110

Authors: Hemendra Singh Rathod

Abstract:

Frequency is, among other factors, one of the governing parameters for maintaining electrical grid stability. The quality of an electrical transmission and supply system is mainly described by the stability of the grid frequency. Over the past few decades, energy generation by intermittent sustainable sources like wind and solar has seen a significant increase globally. Consequently, controlling the associated deviations in grid frequency within safe limits has been gaining momentum so that the balance between demand and supply can be maintained. Lithium-ion battery energy storage system (Li-Ion BESS) has been a promising technology to tackle the challenges associated with grid instability. BESS is, therefore, an effective response to the ongoing debate whether it is feasible to have an electrical grid constantly functioning on a hundred percent renewable power in the near future. In recent years, large-scale manufacturing and capital investment into battery production processes have made the Li-ion battery systems cost-effective and increasingly efficient. The Li-ion systems require very low maintenance and are also independent of geographical constraints while being easily scalable. The paper highlights the use of stationary and moving BESS for balancing electrical energy, thereby maintaining grid frequency at a rapid rate. Moving BESS technology, as implemented in the selected railway network in Germany, is here considered as an exemplary concept for demonstrating the same functionality in the electrical grid system. Further, using certain applications of Li-ion batteries, such as self-consumption of wind and solar parks or their ancillary services, wind and solar energy storage during low demand, black start, island operation, residential home storage, etc. offers a solution to effectively integrate the renewables and support Europe’s future smart grid. EMT software tool DIgSILENT PowerFactory has been utilised to model an electrical transmission system with 100% renewable energy penetration. The stability of such a transmission system has been evaluated together with BESS within a defined frequency band. The transmission system operators (TSO) have the superordinate responsibility for system stability and must also coordinate with the other European transmission system operators. Frequency control is implemented by TSO by maintaining a balance between electricity generation and consumption. Li-ion battery systems are here seen as flexible, controllable loads and flexible, controllable generation for balancing energy pools. Thus using Li-ion battery storage solution, frequency-dependent load shedding, i.e., automatic gradual disconnection of loads from the grid, and frequency-dependent electricity generation, i.e., automatic gradual connection of BESS to the grid, is used as a perfect security measure to maintain grid stability in any case scenario. The paper emphasizes the use of stationary and moving Li-ion battery storage for meeting the demands of maintaining grid frequency and stability for near future operations.

Keywords: frequency control, grid stability, li-ion battery storage, smart grid

Procedia PDF Downloads 130