Search results for: regional features
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5437

Search results for: regional features

2707 Safety Effect of Smart Right-Turn Design at Intersections

Authors: Upal Barua

Abstract:

The risk of severe crashes at high-speed right-turns at intersections is a major safety concern these days. The application of a smart right-turn at an intersection is increasing day by day to address is an issue. The design, ‘Smart Right-turn’ consists of a narrow-angle of channelization at approximately 70°. This design increases the cone of vision of the right-tuning drivers towards the crossing pedestrians as well as traffic on the cross-road. As part of the Safety Improvement Program in Austin Transportation Department, several smart right-turns were constructed at high crash intersections where high-speed right-turns were found to be a contributing factor. This paper features the state of the art techniques applied in planning, engineering, designing and construction of this smart right-turn, key factors driving the success, and lessons learned in the process. This paper also presents the significant crash reductions achieved from the application of this smart right-turn design using Empirical Bayes method. The result showed that smart right-turns can reduce overall right-turn crashes by 43% and severe right-turn crashes by 70%.

Keywords: smart right-turn, intersection, cone of vision, empirical Bayes method

Procedia PDF Downloads 265
2706 A Mathematical Model for 3-DOF Rotary Accuracy Measurement Method Based on a Ball Lens

Authors: Hau-Wei Lee, Yu-Chi Liu, Chien-Hung Liu

Abstract:

A mathematical model is presented for a system that measures rotational errors in a shaft using a ball lens. The geometric optical characteristics of the ball lens mounted on the shaft allows the measurement of rotation axis errors in both the radial and axial directions. The equipment used includes two quadrant detectors (QD), two laser diodes and a ball lens that is mounted on the rotating shaft to be evaluated. Rotational errors in the shaft cause changes in the optical geometry of the ball lens. The resulting deflection of the laser beams is detected by the QDs and their output signals are used to determine rotational errors. The radial and the axial rotational errors can be calculated as explained by the mathematical model. Results from system calibration show that the measurement error is within ±1 m and resolution is about 20 nm. Using a direct drive motor (DD motor) as an example, experimental results show a rotational error of less than 20 m. The most important features of this system are that it does not require the use of expensive optical components, it is small, very easy to set up, and measurements are highly accurate.

Keywords: ball lens, quadrant detector, axial error, radial error

Procedia PDF Downloads 473
2705 Keypoint Detection Method Based on Multi-Scale Feature Fusion of Attention Mechanism

Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

Abstract:

Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

Procedia PDF Downloads 119
2704 The Study of Fine and Nanoscale Gold in the Ores of Primary Deposits and Gold-Bearing Placers of Kazakhstan

Authors: Omarova Gulnara, Assubayeva Saltanat, Tugambay Symbat, Bulegenov Kanat

Abstract:

The article discusses the problem of developing a methodology for studying thin and nanoscale gold in ores and placers of primary deposits, which will allow us to develop schemes for revealing dispersed gold inclusions and thus improve its recovery rate to increase the gold reserves of the Republic of Kazakhstan. The type of studied gold, is characterized by a number of features. In connection with this, the conditions of its concentration and distribution in ore bodies and formations, as well as the possibility of reliably determining it by "traditional" methods, differ significantly from that of fine gold (less than 0.25 microns) and even more so from that of larger grains. The mineral composition of rocks (metasomatites) and gold ore and the mineralization associated with them were studied in detail on the Kalba ore field in Kazakhstan. Mineralized zones were identified, and samples were taken from them for analytical studies. The research revealed paragenetic relationships of newly formed mineral formations at the nanoscale, which makes it possible to clarify the conditions for the formation of deposits with a particular type of mineralization. This will provide significant assistance in developing a scheme for study. Typomorphic features of gold were revealed, and mechanisms of formation and aggregation of gold nanoparticles were proposed. The presence of a large number of particles isolated at the laboratory stage from concentrates of gravitational enrichment can serve as an indicator of the presence of even smaller particles in the object. Even the most advanced devices based on gravitational methods for gold concentration provide extraction of metal at a level of around 50%, while pulverized metal is extracted much worse, and gold of less than 1 micron size is extracted at only a few percent. Therefore, when particles of gold smaller than 10 microns are detected, their actual numbers may be significantly higher than expected. In particular, at the studied sites, enrichment of slurry and samples with volumes up to 1 m³ was carried out using a screw lock or separator to produce a final concentrate weighing up to several kilograms. Free gold particles were extracted from the concentrates in the laboratory using a number of processes (magnetic and electromagnetic separation, washing with bromoform in a cup to obtain an ultracontentrate, etc.) and examined under electron microscopes to investigate the nature of their surface and chemical composition. The main result of the study was the detection of gold nanoparticles located on the surface of loose metal grains. The most characteristic forms of gold secretions are individual nanoparticles and aggregates of different configurations. Sometimes, aggregates form solid dense films, deposits, and crusts, all of which are confined to the negative forms of the nano- and microrelief on the surfaces of golden. The results will provide significant knowledge about the prevalence and conditions for the distribution of fine and nanoscale gold in Kazakhstan deposits, as well as the development of methods for studying it, which will minimize losses of this type of gold during extraction. Acknowledgments: This publication has been produced within the framework of the Grant "Development of methodology for studying fine and nanoscale gold in ores of primary deposits, placers and products of their processing" (АР23485052, №235/GF24-26).

Keywords: electron microscopy, microminerology, placers, thin and nanoscale gold

Procedia PDF Downloads 21
2703 Post-modernist Tragi-Comedy: A Study of Tom Stoppard’s “Rosencrantz and Guildenstern Are Dead”

Authors: Azza Taha Zaki

Abstract:

The death of tragedy is probably the most distinctive literary controversy of the twentieth century. There is common critical consent that tragedy in the classical sense of the word is no longer possible. Thinkers, philosophers, and critics such as Nietzsche, Durrenmatt, and George Steiner have all agreed that the decline of the genre in the modern age is due to the total lack of a unified world image and the absence of a shared vision in a fragmented and ideologically diversified world. The production of Rosencrantz and Guildenstern are Dead in 1967 marked the rise of the genre of tragi-comedy as a more appropriate reflection of the spirit of the age. At the hands of such great dramatists as Tom Stoppard (1937- ), the revived genre was not used as an extra comic element to give some comic relief to an otherwise tragic text, but it was given a postmodernist touch to serve the interpretation of the dilemma of man in the postmodernist world. This paper will study features of postmodernist tragi-comedy in Rosencrantz and Guildenstern are Dead as one of the most important plays in modern British theatre and investigate Stoppard’s vision of man and life as influenced by postmodernist thought and philosophy.

Keywords: British, drama, postmodernist, Stoppard, tragi-comedy

Procedia PDF Downloads 186
2702 [Keynote Talk]: Animation of Objects on the Website by Application of CSS3 Language

Authors: Vladimir Simovic, Matija Varga, Robert Svetlacic

Abstract:

Scientific work analytically explores and demonstrates techniques that can animate objects and geometric characters using CSS3 language by applying proper formatting and positioning of elements. This paper presents examples of optimum application of the CSS3 descriptive language when generating general web animations (e.g., billiards and movement of geometric characters, etc.). The paper presents analytically, the optimal development and animation design with the frames within which the animated objects are. The originally developed content is based on the upgrading of existing CSS3 descriptive language animations with more complex syntax and project-oriented work. The purpose of the developed animations is to provide an overview of the interactive features of CSS3 descriptive language design for computer games and the animation of important analytical data based on the web view. It has been analytically demonstrated that CSS3 as a descriptive language allows inserting of various multimedia elements into websites for public and internal sites.

Keywords: web animation recording, KML GML HTML5 forms, Cascading Style Sheets 3, Google Earth Professional

Procedia PDF Downloads 335
2701 Deep Learning for SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 68
2700 Immobilization of Enzymes and Proteins on Epoxy-Activated Supports

Authors: Ehsan Khorshidian, Afshin Farahbakhsh, Sina Aghili

Abstract:

Enzymes are promising biocatalysts for many organic reactions. They have excellent features like high activity, specificity and selectivity, and can catalyze under mild and environment friendly conditions. Epoxy-activated supports are almost-ideal ones to perform very easy immobilization of proteins and enzymes at both laboratory and industrial scale. The activated epoxy supports (chitosan/alginate, Eupergit C) may be very suitable to achieve the multipoint covalent attachment of proteins and enzymes, therefore, to stabilize their three-dimensional structure. The enzyme is firstly covalently immobilized under conditions pH 7.0 and 10.0. The remaining groups of the support are blocked to stop additional interaction between the enzyme and support by mercaptoethanol or Triton X-100. The results show support allowed obtaining biocatalysts with high immobilized protein amount and hydrolytic activity. The immobilization of lipases on epoxy support may be considered as attractive tool for obtaining highly active biocatalysts to be used in both aqueous and anhydrous aqueous media.

Keywords: immobilization of enzymes, epoxy supports, enzyme multipoint covalent attachment, microbial lipases

Procedia PDF Downloads 388
2699 The Wear Recognition on Guide Surface Based on the Feature of Radar Graph

Authors: Youhang Zhou, Weimin Zeng, Qi Xie

Abstract:

Abstract: In order to solve the wear recognition problem of the machine tool guide surface, a new machine tool guide surface recognition method based on the radar-graph barycentre feature is presented in this paper. Firstly, the gray mean value, skewness, projection variance, flat degrees and kurtosis features of the guide surface image data are defined as primary characteristics. Secondly, data Visualization technology based on radar graph is used. The visual barycentre graphical feature is demonstrated based on the radar plot of multi-dimensional data. Thirdly, a classifier based on the support vector machine technology is used, the radar-graph barycentre feature and wear original feature are put into the classifier separately for classification and comparative analysis of classification and experiment results. The calculation and experimental results show that the method based on the radar-graph barycentre feature can detect the guide surface effectively.

Keywords: guide surface, wear defects, feature extraction, data visualization

Procedia PDF Downloads 519
2698 Numerical Analysis of a Strainer Using Porous Media Technique

Authors: Ji-Hoon Byeon, Kwon-Hee Lee

Abstract:

Strainer filter serves to block the inflow of impurities while mixed fluid is entering or exiting the piping. The filter of the strainer has a perforated structure, so that the pressure drop and the velocity change necessarily occur when the mixed fluid passes through the filter. It is possible to predict the pressure drop and velocity change of the strainer by numerical analysis by implementing all the perforated plates. However, if the size of the perforated plate exceeds a certain size, it is difficult to perform the numerical analysis, and sometimes we cannot guarantee its accuracy. In this study, we tried to predict the pressure drop and velocity change by using the porous media technique to obtain the equivalent resistance without actual implementation of the perforation shape of the strainer. Ansys-CFX, a commercial software, is used to perform the numerical analysis. The analysis procedure is as follows. Firstly, the unit pattern of the perforated plate is modeled, and the pressure drop is analyzed by varying the velocity by symmetry of the wall surface. Secondly, since the equation for obtaining resistance is a quadratic equation of pressure having unknown velocity, the viscous resistance and the inertia resistance of the perforated plate are obtained from the relationship between pressure and speed. Thirdly, by using the calculated resistance values, the values are substituted into the flat plate implemented as a two-dimensional porous media, and the accuracy is verified by comparing the pressure drop and the velocity change. Fourthly, the pressure drop and velocity change in the whole strainer are analyzed by using the resistance values obtained on the perforated plate in the actual whole strainer model. Using the porous media technique, it is found that pressure drop and velocity change can be predicted in relatively short time without modeling the overall shape of the filter. Acknowledgements: This work was supported by the Valve Center from the Regional Innovation Center(RIC) Program of Ministry of Trade, Industry & Energy (MOTIE).

Keywords: strainer, porous media, CFD, numerical analysis

Procedia PDF Downloads 371
2697 Numerical Simulation of Ultraviolet Disinfection in a Water Reactor

Authors: H. Shokouhmand, H. Sobhani, B. Sajadi, M. Degheh

Abstract:

In recent years, experimental and numerical investigation of water UV reactors has increased significantly. The main drawback of experimental methods is confined and expensive survey of UV reactors features. In this study, a CFD model utilizing the eulerian-lagrangian framework is applied to analysis the disinfection performance of a closed conduit reactor which contains four UV lamps perpendicular to the flow. A discrete ordinates (DO) model was employed to evaluate the UV irradiance field. To investigate the importance of each of lamps on the inactivation performance, in addition to the reference model (with 4 bright lamps), several models with one or two bright lamps in various arrangements were considered. All results were reported in three inactivation kinetics. The results showed that the log inactivation of the two central bright lamps model was between 88-99 percent, close to the reference model results. Also, whatever the lamps are closer to the main flow region, they have more effect on microbial inactivation. The effect of some operational parameters such as water flow rate, inlet water temperature, and lamps power were also studied.

Keywords: Eulerian-Lagrangian framework, inactivation kinetics, log inactivation, water UV reactor

Procedia PDF Downloads 251
2696 Renegotiating International Contract Clauses: The Case of Investment Environment Changes in Egypt

Authors: Marwa Zein

Abstract:

The long-term of the contract is one of the major features that distinguish international trade and investment contracts from other internal contracts. This is due to the nature of the contract and the huge works required to be performed from one hand or the desire of the parties to achieve stability in their transactions. However, long-term contracts might expose them to certain events and circumstances that impact the capability of the parties to execute their obligations pursuant to these contracts. During the year 2016, the Egyptian government has taken series of economic decisions which greatly impacted the economic and investment environment. Consequently, many contracts have encountered many problems in their execution due to such changes that greatly influence the performance of their obligation, a matter that necessitated the renegotiation of the conditions of these contracts on the basis of the unpredicted changes that could be listed under the Force Majeure Clause. The principle of fair and equitable treatment in investment placed on an obligation on the Egyptian government to consider the renegotiation of contract clauses based on the new conditions. This paper will discuss the idea of renegotiating international trade and investment contracts in Egypt with reference to the changes the economic environment has witnessed lately.

Keywords: change of circumstances, international contracts, investment contracts, renegotiation

Procedia PDF Downloads 197
2695 Science Communication: A Possible Dialogue between Researchers and Agribusiness Farmers

Authors: Cristiane Hengler Corrêa Bernardo

Abstract:

The communication is an essential part of the process that characterizes scientific research. It should be present in every stage of research in a systemic way. However, this process is not always efficient and effective. Reports of researchers focused on agribusiness point to difficulties in communicating with farmers that negatively impact on research results and may cause distortions and even quite significant inconsistencies. This research aims at identifying the main noise and barriers in communication between agribusiness researchers and farmers. It discusses the possibility of creating a specific strategy to correct or minimize such failures. The main research question: what features of the communication process will be decisive for the communication between agribusiness researcher and farmer occur with greater efficiency? It is expected that the research will result in processes that may correct or minimize such problems, promoting dialogues more efficient knowledge. The research will adopt a qualitative approach, using action research as a form of investigative action for social and educational nature, aiming at promoting understanding and interaction between researchers and members of the investigated situations. To collect and analyze data to document analysis will be used; questionnaires and interviews and content analysis.

Keywords: agribusiness farmers, researchers, science communication, analysis

Procedia PDF Downloads 276
2694 The Guide Presentation: The Grand Palace

Authors: Nuchanat Handumrongkul Danaya Darnsawasdi, Anantachai Aeka

Abstract:

To be a model for performing oral presentations by the tour guides, this research has been conducted. In order to develop French language teaching and studying for tourism, its purpose is to analyze the content used by tour guides. The study employed audio recordings of these presentations as an interview method in authentic situations, having four guides as respondents and information providers. The data was analyzed through content analysis. The results found that the tour guides described eight important items by giving more importance to details at Wat Phra Kaew or the Temple of the Emerald Buddha than at the palaces. They preferred the buildings upon the upper terrace, Buddhist cosmology, the decoration techniques, the royal chapel, the mural paintings, Thai offerings to Buddha images, palaces with architectural features and functions including royal ceremonies and others. This information represents the Thai characteristics of each building and other related content. The findings were used as a manual for guides for how to describe a tourist attraction, especially the temple and other related cultural topics of interest.

Keywords: guide, guide presentation, Grand Palace, Buddhist cosmology

Procedia PDF Downloads 500
2693 Under the ‘Fourth World’: A Discussion to the Transformation of Character-Settings in Chinese Ethnic Minority Films

Authors: Sicheng Liu

Abstract:

Based on the key issue of the current fourth world studies, the article aims to analyze the features of character-settings in Chinese ethnic minority films. As a generalizable transformation, this feature progresses from a microcosmic representation. It argues that, as the mediation, films note down the current state of people and their surroundings, while the ‘fourth world’ theorization (or the fourth cinema) provides a new perspective to ethnic minority topics in China. Like the ‘fourth cinema’ focusing on the depiction of indigeneity groups, the ethnic minority films portrait the non-Han nationalities in China. Both types possess the motif of returning history-writing to the minority members’ own hand. In this article, the discussion entirely involves three types of cinematic role-settings in Chinese minority themed films, which illustrates that, similar to the creative principle of the fourth film, the themes and narratives of these films are becoming more individualized, with more concern to minority grassroots.

Keywords: 'fourth world', Chinese ethnic minority films, ethnicity and culture reflection, 'mother tongue' (muyu), highlighting to individual spiritual

Procedia PDF Downloads 188
2692 Land Use Change Detection Using Satellite Images for Najran City, Kingdom of Saudi Arabia (KSA)

Authors: Ismail Elkhrachy

Abstract:

Determination of land use changing is an important component of regional planning for applications ranging from urban fringe change detection to monitoring change detection of land use. This data are very useful for natural resources management.On the other hand, the technologies and methods of change detection also have evolved dramatically during past 20 years. So it has been well recognized that the change detection had become the best methods for researching dynamic change of land use by multi-temporal remotely-sensed data. The objective of this paper is to assess, evaluate and monitor land use change surrounding the area of Najran city, Kingdom of Saudi Arabia (KSA) using Landsat images (June 23, 2009) and ETM+ image(June. 21, 2014). The post-classification change detection technique was applied. At last,two-time subset images of Najran city are compared on a pixel-by-pixel basis using the post-classification comparison method and the from-to change matrix is produced, the land use change information obtained.Three classes were obtained, urban, bare land and agricultural land from unsupervised classification method by using Erdas Imagine and ArcGIS software. Accuracy assessment of classification has been performed before calculating change detection for study area. The obtained accuracy is between 61% to 87% percent for all the classes. Change detection analysis shows that rapid growth in urban area has been increased by 73.2%, the agricultural area has been decreased by 10.5 % and barren area reduced by 7% between 2009 and 2014. The quantitative study indicated that the area of urban class has unchanged by 58.2 km〗^2, gained 70.3 〖km〗^2 and lost 16 〖km〗^2. For bare land class 586.4〖km〗^2 has unchanged, 53.2〖km〗^2 has gained and 101.5〖km〗^2 has lost. While agriculture area class, 20.2〖km〗^2 has unchanged, 31.2〖km〗^2 has gained and 37.2〖km〗^2 has lost.

Keywords: land use, remote sensing, change detection, satellite images, image classification

Procedia PDF Downloads 524
2691 Jabodebek Light Rail Transit with Grade of Automation (GoA) No.3 (Driverless) Technology towards Jakarta Net-Zero Emissions (NZE) 2050

Authors: Nadilla Saskia, Octoria Nur, Assegaf Zareeva

Abstract:

Mass transport infrastructures are essential to enhance the connectivity between regions and regional equity in Indonesia. Indonesia’s capital city, Jakarta, ranked the 10th highest congestion rate in the world based on the 2019 traffic index, contributing to air pollution and energy consumption. Other than that, the World Air Quality Report in 2019 depicted Jakarta’s air pollutant concentration at 49.4 mg, the 5th highest in the world. Issues of severe traffic congestion, lack of sufficient urban infrastructure in Jakarta, and greenhouse gas emissions have to be addressed through mass transportation. Indonesia’s government is currently constructing The Greater Jakarta LRT (Light Rapid Transit) as convenient, efficient, and environmentally friendly transportation connecting Jakarta with Bekasi and Cibubur areas and plans to serve the passengers in August 2023. Greater Jakarta LRT is operated with Grade of Automation (GoA) No.3, Driverless Train Operation (DTO). Hence, the automated technology used in rail infrastructure is anticipated to address these issues with greater results. The paper will be validated and establish the extent to which the automation system would increase energy efficiency, help reduce carbon emissions, and benefit the environment. Based on the calculated CO2 emissions and fuel consumption for the existing condition (2015) during the feasibility study of the LRT Project and the predicted condition in 2030, it is obtained that Greater Jakarta LRT with GoA3 operation will reduce the CO2 emissions and fuel consumption by more than 50% in 2030. In the bigger picture, Greater Jakarta LRT supports the government's goal of achieving Jakarta Net-Zero Emissions (NZE) 2050.

Keywords: LRT, Grade of Automation (GoA), energy efficiency, carbon emissions, railway infrastructure, DKI Jakarta

Procedia PDF Downloads 82
2690 Pod and Wavelets Application for Aerodynamic Design Optimization

Authors: Bonchan Koo, Junhee Han, Dohyung Lee

Abstract:

The research attempts to evaluate the accuracy and efficiency of a design optimization procedure which combines wavelets-based solution algorithm and proper orthogonal decomposition (POD) database management technique. Aerodynamic design procedure calls for high fidelity computational fluid dynamic (CFD) simulations and the consideration of large number of flow conditions and design constraints. Even with significant computing power advancement, current level of integrated design process requires substantial computing time and resources. POD reduces the degree of freedom of full system through conducting singular value decomposition for various field simulations. For additional efficiency improvement of the procedure, adaptive wavelet technique is also being employed during POD training period. The proposed design procedure was applied to the optimization of wing aerodynamic performance. Throughout the research, it was confirmed that the POD/wavelets design procedure could significantly reduce the total design turnaround time and is also able to capture all detailed complex flow features as in full order analysis.

Keywords: POD (Proper Orthogonal Decomposition), wavelets, CFD, design optimization, ROM (Reduced Order Model)

Procedia PDF Downloads 467
2689 Smallholder Farmers’ Adaptation Strategies and Socioeconomic Determinants of Climate Variability in Boset District, Oromia, Ethiopia

Authors: Hurgesa Hundera, Samuel Shibeshibikeko, Tarike Daba, Tesfaye Ganamo

Abstract:

The study aimed at examining the ongoing adaptation strategies used by smallholder farmers in response to climate variability in Boset district. It also assessed the socioeconomic factors that influence the choice of adaptation strategies of smallholder farmers to climate variability risk. For attaining the objectives of the study, both primary and secondary sources of data were employed. The primary data were obtained through a household questionnaire, key informant interviews, focus group discussions, and observations, while secondary data were acquired through desk review. Questionnaires were distributed and filled by 328 respondents, and they were identified through systematic random sampling technique. Descriptive statistics and binary logistic regression model were applied in this study as the main analytical methods. The findings of the study reveal that the sample households have utilized multiple adaptation strategies in response to climate variability, such as cropping early mature crops, planting drought resistant crops, growing mixed crops on the same farm lands, and others. The results of the binary logistic model revealed that education, sex, age, family size, off farm income, farm experience, access to climate information, access to farm input, and farm size were significant and key factors determining farmers’ choice of adaptation strategies to climate variability in the study area. To enable effective adaptation measures, Ministry of Agriculture and Natural Resource, with its regional bureaus and offices and concerned non–governmental organizations, should consider climate variability in their planning and budgeting in all levels of decision making.

Keywords: adaptation strategies, boset district, climate variability, smallholder farmers

Procedia PDF Downloads 87
2688 Commercialization of Smallholder Rice Producers and Its Determinants in Ethiopia

Authors: Abebaw Assaye, Seiichi Sakurai, Marutama Atsush, Dawit Alemu

Abstract:

Rice is considered as a strategic agricultural commodity targeting national food security and import substitution in Ethiopia and diverse measures are put in place a number of initiatives to ensure the growth and development of rice sector in the country. This study assessed factors that influence smallholder farmers' level of rice commercialization in Ethiopia. The required data were generated from 594 randomly sampled rice producers using multi-stage sampling techniques from four major rice-producing regional states. Both descriptive and econometric methods were used to analyze the data. We adopted the ordered probit model to analyze factors determining output commercialization in the rice market. The ordered probit model result showed that the sex of the household head, educational status of the household head, credit use, proportion of irrigated land cultivated, membership in social groups, and land dedicated to rice production were found to influence significantly and positively the probability of being commercial-oriented. Conversely, the age of the household, total cultivated land, and distance to the main market were found to influence negatively. These findings suggest that promoting productivity-increasing technologies, development of irrigation facilities, strengthening of social institutions, and facilitating access to credit are crucial for enhancing the commercialization of rice in the study area. Since agricultural lands are limited, intensified farming through promoting improved rice technologies and mechanized farming could be an option to enhance marketable surplus and increase level of rice market particicpation.

Keywords: rice, commercialization, Tobit, ordered probit, Ethiopia

Procedia PDF Downloads 83
2687 Optimal Feature Extraction Dimension in Finger Vein Recognition Using Kernel Principal Component Analysis

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

Abstract:

In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

Procedia PDF Downloads 365
2686 Connecting Students and Faculty Research Efforts through the Research and Projects Portal

Authors: Havish Nalapareddy, Mark V. Albert, Ranak Bansal, Avi Udash, Lin Lin

Abstract:

Students engage in many course projects during their degree programs. However, impactful projects often need a time frame longer than a single semester. Ideally, projects are documented and structured to be readily accessible to future students who may choose to continue the project, with features that emphasize the local community, university, or course structure. The Research and Project Portal (RAPP) is a place where students can post both their completed and ongoing projects with all the resources and tools used. This portal allows students to see what other students have done in the past, in the same university environment, related to their domain of interest. Computer science instructors or students selecting projects can use this portal to assign or choose an incomplete project. Additionally, this portal allows non-computer science faculty and industry collaborators to document their project ideas for students in courses to prototype directly, rather than directly soliciting the help of instructors in engaging students. RAPP serves as a platform linking students across classes and faculty both in and out of computer science courses on joint projects to encourage long-term project efforts across semesters or years.

Keywords: education, technology, research, academic portal

Procedia PDF Downloads 137
2685 Deep Learning Based Polarimetric SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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2684 Comparative Study Between Two Different Techniques for Postoperative Analgesia in Cesarean Section Delivery

Authors: Nermeen Elbeltagy, Sara Hassan, Tamer Hosny, Mostafa Abdelaziz

Abstract:

Introduction: Adequate postoperative analgesia after caesarean section (CS) is crucial as it impacts the distinct surgical recovery needs of the parturient. Over recent years, there has been increased interest in regional nerve block techniques with promising results on efficacy. These techniques reduce the need for additional analgesia, thereby lowering the incidence of drug-related side effects. As postoperative pain after cesarean is mainly due to abdominal incision, the transverses abdomenis plane ( TAP ) block is a relatively new abdominal nerve block with excellent efficacy after different abdominal surgeries, including cesarean section. Objective: The main objective is to compare ultrasound-guided TAP block provided by the anesthesiologist with TAP provided by the surgeon through a caesarean incision regarding the duration of postoperative analgesia, intensity of analgesia, timing of mobilization, and easiness of the procedure. Method: Ninety pregnant females at term who were scheduled for delivery by elective cesarean section were randomly distributed into two groups. The first group (45) received spinal anesthesia and postoperative ultrasound guided TAP block using 20ml on each side of 0.25% bupivacaine which was provided by the anesthesiologist. The second group (45) received spinal anesthesia plus a TAP block using 20ml on each side of 0.25% bupivacaine, which was provided by the surgeon through the cesarean incision. Visual Analogue Scale (VAS) was used for the comparison between the two groups. Results: VAS score after four hours was higher among the TAP block group provided by the surgeon through the surgical incision than the postoperative analgesic profile using ultrasound-guided TAP block provided by the anesthesiologist (P=0.011). On the contrary, there was no statistical difference in the patient’s dose of analgesia after four hours of the TAP block (P=0.228). Conclusion: TAP block provided through the surgical incision is safe and enhances early patient’s mobilization.

Keywords: TAP block, CS, VAS, analgesia

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2683 Impacts of Building Design Factors on Auckland School Energy Consumptions

Authors: Bin Su

Abstract:

This study focuses on the impact of school building design factors on winter extra energy consumption which mainly includes space heating, water heating and other appliances related to winter indoor thermal conditions. A number of Auckland schools were randomly selected for the study which introduces a method of using real monthly energy consumption data for a year to calculate winter extra energy data of school buildings. The study seeks to identify the relationships between winter extra energy data related to school building design data related to the main architectural features, building envelope and elements of the sample schools. The relationships can be used to estimate the approximate saving in winter extra energy consumption which would result from a changed design datum for future school development, and identify any major energy-efficient design problems. The relationships are also valuable for developing passive design guides for school energy efficiency.

Keywords: building energy efficiency, building thermal design, building thermal performance, school building design

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2682 The Hair Growth Effects of Undariopsis peterseniana

Authors: Jung-Il Kang, Jeon Eon Park, Yu-Jin Moon, Young-Seok Ahn, Eun-Sook Yoo, Hee-Kyoung Kang

Abstract:

This study was conducted to evaluate the effect of Undariopsis peterseniana, a seaweed native to Jeju Island, Korea, on the growth of hair. The dermal papilla cells (DPCs) have known to regulate hair growth cycle and length of hair follicle through interact with epithelial cells. When immortalized vibrissa DPCs were treated with the U. peterseniana extract, the U. peterseniana extract significantly increased the proliferation of DPCs. The effect of U. peterseniana extract on the growth of vibrissa follicles was also examined. U. peterseniana extract significantly increased the hair-fiber lengths of the vibrissa follicles. Hair loss is partly caused by dihydrotestosterone (DHT) binding to androgen receptor in hair follicles, and the inhibition of 5α-reductase activity can prevent hair loss through the decrease of DHT level. The U. peterseniana extract inhibited 5α-reductase activity. Minoxidil, a potent hair-growth agent, can induce proliferation in NIH3T3 fibroblasts by opening KATP channels. We thus examined the proliferative effects of U. peterseniana extract in NIH3T3 fibroblasts. U. peterseniana extract significantly increased the proliferation of NIH3T3 fibroblasts. Tetraethylammonium chloride (TEA), a K+ channel blocker, inhibited U. peterseniana-induced proliferation in NIH3T3 fibroblasts. These results suggest that U. peterseniana could have the potential to treat alopecia through the proliferation of DPCs, the inhibition of 5α-reductase activity and the opening of KATP channels. [Acknowledgement] This research was supported by The Leading Human Resource Training Program of Regional Neo industry through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and future Planning (2016H1D5A1908786).

Keywords: hair growth, Undariopsis peterseniana, vibrissa follicles, dermal papilla cells, 5α-reductase, KATP channels

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2681 Using AI Based Software as an Assessment Aid for University Engineering Assignments

Authors: Waleed Al-Nuaimy, Luke Anastassiou, Manjinder Kainth

Abstract:

As the process of teaching has evolved with the advent of new technologies over the ages, so has the process of learning. Educators have perpetually found themselves on the lookout for new technology-enhanced methods of teaching in order to increase learning efficiency and decrease ever expanding workloads. Shortly after the invention of the internet, web-based learning started to pick up in the late 1990s and educators quickly found that the process of providing learning material and marking assignments could change thanks to the connectivity offered by the internet. With the creation of early web-based virtual learning environments (VLEs) such as SPIDER and Blackboard, it soon became apparent that VLEs resulted in higher reported computer self-efficacy among students, but at the cost of students being less satisfied with the learning process . It may be argued that the impersonal nature of VLEs, and their limited functionality may have been the leading factors contributing to this reported dissatisfaction. To this day, often faced with the prospects of assigning colossal engineering cohorts their homework and assessments, educators may frequently choose optimally curated assessment formats, such as multiple-choice quizzes and numerical answer input boxes, so that automated grading software embedded in the VLEs can save time and mark student submissions instantaneously. A crucial skill that is meant to be learnt during most science and engineering undergraduate degrees is gaining the confidence in using, solving and deriving mathematical equations. Equations underpin a significant portion of the topics taught in many STEM subjects, and it is in homework assignments and assessments that this understanding is tested. It is not hard to see that this can become challenging if the majority of assignment formats students are engaging with are multiple-choice questions, and educators end up with a reduced perspective of their students’ ability to manipulate equations. Artificial intelligence (AI) has in recent times been shown to be an important consideration for many technologies. In our paper, we explore the use of new AI based software designed to work in conjunction with current VLEs. Using our experience with the software, we discuss its potential to solve a selection of problems ranging from impersonality to the reduction of educator workloads by speeding up the marking process. We examine the software’s potential to increase learning efficiency through its features which claim to allow more customized and higher-quality feedback. We investigate the usability of features allowing students to input equation derivations in a range of different forms, and discuss relevant observations associated with these input methods. Furthermore, we make ethical considerations and discuss potential drawbacks to the software, including the extent to which optical character recognition (OCR) could play a part in the perpetuation of errors and create disagreements between student intent and their submitted assignment answers. It is the intention of the authors that this study will be useful as an example of the implementation of AI in a practical assessment scenario insofar as serving as a springboard for further considerations and studies that utilise AI in the setting and marking of science and engineering assignments.

Keywords: engineering education, assessment, artificial intelligence, optical character recognition (OCR)

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2680 Early Childhood Developmental Delay in 63 Low- and Middle-Income Countries: Prevalence and Inequalities Estimated from National Health Surveys

Authors: Jesus D. Cortes Gil, Fernanda Ewerling, Leonardo Ferreira, Aluisio J. D. Barros

Abstract:

Background: The sustainable development goals call for inclusive, equitable, and quality learning opportunities for all. This is especially important for children, to ensure they all develop to their full potential. We studied the prevalence and inequalities of suspected delay in child development in 63 low- and middle-income countries. Methods and Findings: We used the early child development module from national health surveys, which covers four developmental domains (physical, social-emotional, learning, literacy-numeracy) and provides a combined indicator (early child development index, ECDI) of whether children are on track. We calculated the age-adjusted prevalence of suspected delay at the country level and stratifying by wealth, urban/rural residence, sex of the child, and maternal education. We also calculated measures of absolute and relative inequality. We studied 330.613 children from 63 countries. The prevalence of suspected delay for the ECDI ranged from 3% in Barbados to 67% in Chad. For all countries together, 25% of the children were suspected of developmental delay. At regional level, the prevalence of delay ranged from 10% in Europe and Central Asia to 42% in West and Central Africa. The literacy-numeracy domain was by far the most challenging, with the highest proportions of delay. We observed very large inequalities, and most markedly for the literacy-numeracy domain. Conclusions: To date, our study presents the most comprehensive analysis of child development using an instrument especially developed for national health surveys. With a quarter of the children globally suspected of developmental delay, we face an immense challenge. The multifactorial aspect of early child development and the large gaps we found only add to the challenge of not leaving these children behind.

Keywords: child development, inequalities, global health, equity

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2679 Deproteinization of Moroccan Sardine (Sardina pilchardus) Scales: A Pilot-Scale Study

Authors: F. Bellali, M. Kharroubi, Y. Rady, N. Bourhim

Abstract:

In Morocco, fish processing industry is an important source income for a large amount of by-products including skins, bones, heads, guts, and scales. Those underutilized resources particularly scales contain a large amount of proteins and calcium. Sardina plichardus scales from resulting from the transformation operation have the potential to be used as raw material for the collagen production. Taking into account this strong expectation of the regional fish industry, scales sardine upgrading is well justified. In addition, political and societal demands for sustainability and environment-friendly industrial production systems, coupled with the depletion of fish resources, drive this trend forward. Therefore, fish scale used as a potential source to isolate collagen has a wide large of applications in food, cosmetic, and biomedical industry. The main aim of this study is to isolate and characterize the acid solubilize collagen from sardine fish scale, Sardina pilchardus. Experimental design methodology was adopted in collagen processing for extracting optimization. The first stage of this work is to investigate the optimization conditions of the sardine scale deproteinization on using response surface methodology (RSM). The second part focus on the demineralization with HCl solution or EDTA. And the last one is to establish the optimum condition for the isolation of collagen from fish scale by solvent extraction. The advancement from lab scale to pilot scale is a critical stage in the technological development. In this study, the optimal condition for the deproteinization which was validated at laboratory scale was employed in the pilot scale procedure. The deproteinization of fish scale was then demonstrated on a pilot scale (2Kg scales, 20l NaOH), resulting in protein content (0,2mg/ml) and hydroxyproline content (2,11mg/l). These results indicated that the pilot-scale showed similar performances to those of lab-scale one.

Keywords: deproteinization, pilot scale, scale, sardine pilchardus

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2678 Psychosocial Predictors of Brand Loyalty in Pakistani Consumers

Authors: Muhammad Sulman, Tabinda Khurshid, Afsheen Masood

Abstract:

The current research focused on determining the factors that determine the brand loyalty in consumers. It was hypothesized that there are certain demographical features that lead the consumers to adhere more towards certain brands. Cross-sectional research design was used. The sample for the current research comprised of participants (N=500) from age group 16 to 55 years. The data was collected through self-constructed demographic questionnaire as well as from a self-constructed Brand Loyalty Questionnaire. Brand Loyalty Questionnaire was adapted after taking permission from researchers. A pilot study was conducted to chalk out all the ambiguities of the questionnaire. The final version was administered on 250 participants. The descriptive and inferential analyses were carried on through SPSS version 24.00 to explore the factors that determine Brand Loyalty. The findings revealed that there is a relationship between brand loyalty and brand loyalty demographics and certain factors emerged as significant predictors of brand loyalty in young and middle aged consumers. The research findings carry strong implications for organizational and consumer psychologists in particular and for professionals in marketing and policy making in general.

Keywords: consumers, consumer psychologists, marketing, organizational, policy making

Procedia PDF Downloads 271