Search results for: Geographic Information System
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25169

Search results for: Geographic Information System

8789 GPU Accelerated Fractal Image Compression for Medical Imaging in Parallel Computing Platform

Authors: Md. Enamul Haque, Abdullah Al Kaisan, Mahmudur R. Saniat, Aminur Rahman

Abstract:

In this paper, we have implemented both sequential and parallel version of fractal image compression algorithms using CUDA (Compute Unified Device Architecture) programming model for parallelizing the program in Graphics Processing Unit for medical images, as they are highly similar within the image itself. There is several improvements in the implementation of the algorithm as well. Fractal image compression is based on the self similarity of an image, meaning an image having similarity in majority of the regions. We take this opportunity to implement the compression algorithm and monitor the effect of it using both parallel and sequential implementation. Fractal compression has the property of high compression rate and the dimensionless scheme. Compression scheme for fractal image is of two kinds, one is encoding and another is decoding. Encoding is very much computational expensive. On the other hand decoding is less computational. The application of fractal compression to medical images would allow obtaining much higher compression ratios. While the fractal magnification an inseparable feature of the fractal compression would be very useful in presenting the reconstructed image in a highly readable form. However, like all irreversible methods, the fractal compression is connected with the problem of information loss, which is especially troublesome in the medical imaging. A very time consuming encoding process, which can last even several hours, is another bothersome drawback of the fractal compression.

Keywords: accelerated GPU, CUDA, parallel computing, fractal image compression

Procedia PDF Downloads 317
8788 Irrigation and Thermal Buffering Mathematical Modeling

Authors: Yara Elborolosy, Harsho Sanyal, Joseph Cataldo

Abstract:

Two methods of irrigation, drip and sprinkler, were studied to determine the response of the Javits green roof to irrigation. The control study were dry unirrigated plots. Drip irrigation consisted of irrigation tubes running through the green roof that would water the soil throughout, and sprinkler irrigation used a sprinkler system to irrigate the green roof from above. In all cases, the irrigated roofs had increased the soil moisture, reduced temperatures of both the upper and lower surfaces, reduced growing medium temperatures and reduced air temperatures above the green roof relative to the unirrigated roof. The buffered temperature fluctuations were also studied via air conditioner energy consumption. There was a 28% reductionin air conditioner energy consumption and 33% reduction in overall energy consumption between dry and irrigated plots. Values of thermal resistance or S were determined for accuracy, and for this study, there was little change which is ideal. A series of infra-red and thermal probe measurements were used to determine temperatures in the air and sedum. It was determined that the sprinkler irrigation did a better job than the drip irrigation in keeping cooler temperatures within the green roof.

Keywords: green infrastructure, black roof, thermal buffering, irrigation

Procedia PDF Downloads 51
8787 Exploring Gaming-Learning Interaction in MMOG Using Data Mining Methods

Authors: Meng-Tzu Cheng, Louisa Rosenheck, Chen-Yen Lin, Eric Klopfer

Abstract:

The purpose of the research is to explore some of the ways in which gameplay data can be analyzed to yield results that feedback into the learning ecosystem. Back-end data for all users as they played an MMOG, The Radix Endeavor, was collected, and this study reports the analyses on a specific genetics quest by using the data mining techniques, including the decision tree method. In the study, different reasons for quest failure between participants who eventually succeeded and who never succeeded were revealed. Regarding the in-game tools use, trait examiner was a key tool in the quest completion process. Subsequently, the results of decision tree showed that a lack of trait examiner usage can be made up with additional Punnett square uses, displaying multiple pathways to success in this quest. The methods of analysis used in this study and the resulting usage patterns indicate some useful ways that gameplay data can provide insights in two main areas. The first is for game designers to know how players are interacting with and learning from their game. The second is for players themselves as well as their teachers to get information on how they are progressing through the game, and to provide help they may need based on strategies and misconceptions identified in the data.

Keywords: MMOG, decision tree, genetics, gaming-learning interaction

Procedia PDF Downloads 344
8786 Emotional State and Cognitive Workload during a Flight Simulation: Heart Rate Study

Authors: Damien Mouratille, Antonio R. Hidalgo-Muñoz, Nadine Matton, Yves Rouillard, Mickael Causse, Radouane El Yagoubi

Abstract:

Background: The monitoring of the physiological activity related to mental workload (MW) on pilots will be useful to improve aviation safety by anticipating human performance degradation. The electrocardiogram (ECG) can reveal MW fluctuations due to either cognitive workload or/and emotional state since this measure exhibits autonomic nervous system modulations. Arguably, heart rate (HR) is one of its most intuitive and reliable parameters. It would be particularly interesting to analyze the interaction between cognitive requirements and emotion in ecologic sets such as a flight simulator. This study aims to explore by means of HR the relation between cognitive demands and emotional activation. Presumably, the effects of cognition and emotion overloads are not necessarily cumulative. Methodology: Eight healthy volunteers in possession of the Private Pilot License were recruited (male; 20.8±3.2 years). ECG signal was recorded along the whole experiment by placing two electrodes on the clavicle and left pectoral of the participants. The HR was computed within 4 minutes segments. NASA-TLX and Big Five inventories were used to assess subjective workload and to consider the influence of individual personality differences. The experiment consisted in completing two dual-tasks of approximately 30 minutes of duration into a flight simulator AL50. Each dual-task required the simultaneous accomplishment of both a pre-established flight plan and an additional task based on target stimulus discrimination inserted between Air Traffic Control instructions. This secondary task allowed us to vary the cognitive workload from low (LC) to high (HC) levels, by combining auditory and visual numerical stimuli to respond to meeting specific criteria. Regarding emotional condition, the two dual-tasks were designed to assure analogous difficulty in terms of solicited cognitive demands. The former was realized by the pilot alone, i.e. Low Arousal (LA) condition. In contrast, the latter generates a high arousal (HA), since the pilot was supervised by two evaluators, filmed and involved into a mock competition with the rest of the participants. Results: Performance for the secondary task showed significant faster reaction times (RT) for HA compared to LA condition (p=.003). Moreover, faster RT was found for LC compared to HC (p < .001) condition. No interaction was found. Concerning HR measure, despite the lack of main effects an interaction between emotion and cognition is evidenced (p=.028). Post hoc analysis showed smaller HR for HA compared to LA condition only for LC (p=.049). Conclusion. The control of an aircraft is a very complex task including strong cognitive demands and depends on the emotional state of pilots. According to the behavioral data, the experimental set has permitted to generate satisfactorily different emotional and cognitive levels. As suggested by the interaction found in HR measure, these two factors do not seem to have a cumulative impact on the sympathetic nervous system. Apparently, low cognitive workload makes pilots more sensitive to emotional variations. These results hint the independency between data processing and emotional regulation. Further physiological data are necessary to confirm and disentangle this relation. This procedure may be useful for monitoring objectively pilot’s mental workload.

Keywords: cognitive demands, emotion, flight simulator, heart rate, mental workload

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8785 Effect of Vesicular Arbuscular mycorrhiza on Phytoremedial Potential and Physiological Changes in Solanum melongena Plants Grown under Heavy Metal Stress

Authors: Ritu Chaturvedi, Mayank Varun, M. S. Paul

Abstract:

Heavy metal contamination of soil is a growing area of concern since the soil is the matrix that supports flora and impacts humans directly. Phytoremediation of contaminated sites is gaining popularity due to its cost effectiveness and solar driven nature. Some hyperaccumulators have been identified for their potential. Metal-accumulating plants have various mechanisms to cope up with stress and one of them is increasing antioxidative capacity. The aim of this research is to assess the effect of Vesicular arbuscular mycorrhiza (VAM) application on the phytoremedial potential of Solanum melongena (Eggplant) and level of photosynthetic pigments along with antioxidative enzymes. Results showed that VAM application increased shoot length, root proliferation pattern of plants. The level of photosynthetic pigments, proline, SOD, CAT, APX altered significantly in response to heavy metal treatment. In conclusion, VAM increased the uptake of heavy metals which lead to the activation of the defense system in plants for scavenging free radicals.

Keywords: heavy metal, phytoextraction, phytostabilization, reactive oxygen species

Procedia PDF Downloads 266
8784 Functionalized DOX Nanocapsules by Iron Oxide Nanoparticles for Targeted Drug Delivery

Authors: Afsaneh Ghorbanzadeh, Afshin Farahbakhsh, Zakieh Bayat

Abstract:

The drug capsulation was used for release and targeted delivery in determined time, place and temperature or pH. The DOX nanocapsules were used to reduce and to minimize the unwanted side effects of drug. In this paper, the encapsulation methods of doxorubicin (DOX) and the labeling it by the magnetic core of iron (Fe3O4) has been studied. The Fe3O4 was conjugated with DOX via hydrazine bond. The solution was capsuled by the sensitive polymer of heat or pH such as chitosan-g-poly (N-isopropylacrylamide-co-N,N-dimethylacrylamide), dextran-g-poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide) and mPEG-G2.5 PAMAM by hydrazine bond. The drug release was very slow at temperatures lower than 380°C. There was a rapid and controlled drug release at temperatures higher than 380°C. According to experiments, the use mPEG-G2.5PAMAM is the best method of DOX nanocapsules synthesis, because in this method, the drug delivery time to certain place is lower than other methods and the percentage of released drug is higher. The synthesized magnetic carrier system has potential applications in magnetic drug-targeting delivery and magnetic resonance imaging.

Keywords: drug carrier, drug release, doxorubicin, iron oxide NPs

Procedia PDF Downloads 403
8783 A Dynamic Neural Network Model for Accurate Detection of Masked Faces

Authors: Oladapo Tolulope Ibitoye

Abstract:

Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

Procedia PDF Downloads 53
8782 Generation of 3d Models Obtained with Low-Cost RGB and Thermal Sensors Mounted on Drones

Authors: Julio Manuel De Luis Ruiz, Javier Sedano Cibrián, RubéN Pérez Álvarez, Raúl Pereda García, Felipe Piña García

Abstract:

Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In this sense, the classic 3D models are being applied to investigate the direction towards which the generally subterranean structures of an archaeological site may continue and therefore, to help in making the decisions that define the location of new excavations. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimise the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain).

Keywords: process optimization, RGB models, thermal models, , UAV, workflow

Procedia PDF Downloads 126
8781 The Use of Authentic Materials in the Chinese Language Classroom

Authors: Yiwen Jin, Jing Xiao, Pinfang Su

Abstract:

The idea of adapting authentic materials in language teaching is from the communicative method in the 1970s. Different from the language in language textbooks, authentic materials is not deliberately written, it is from the native speaker’s real life and contains real information, which can meet social needs. It could improve learners ' interest, create authentic context and improve learners ' communicative competence. Authentic materials play an important role in CFL(Chinese as a foreign language) classroom. Different types of authentic materials can be used in different ways during learning and teaching. Because of the COVID-19 pandemic,a lot of Chinese learners are learning Chinese without the real language environment. Although there are some well-written textbooks, there is a certain distance between textbook language materials and daily life. Learners cannot automatically fill this gap. That is why it is necessary to apply authentic materials as a supplement to the language textbook to create the real context. Chinese teachers around the world are working together, trying to integrate the resources and apply authentic materials through different approach. They apply authentic materials in the form of new textbooks, manuals, apps and short videos they collect and create to help Chinese learning and teaching. A review of previous research on authentic materials and the Chinese teachers’ attempt to adapt it in the classroom are offered in this manuscript.

Keywords: authentic materials, Chinese as a second language, developmental use of digital resources, materials development for language teaching

Procedia PDF Downloads 161
8780 Efficacy of Isometric Neck Exercises and Stretching with Ergonomics for Neck Pain in Computer Professionals

Authors: Esther Liyanage, Indrajith Liyanage, Masih Khan

Abstract:

Neck pain has become a common epidemiological problem. One of the reasons for this is a sedentary way of life, connected with using a personal computer during all daily activities. Work place and work duration has not been properly adapted to the personal physical conditions of these employees. During 1990’s the importance of workstation design and work methods, or ergonomics on health was brought to the forefront of public attention. Ergonomics is the application of scientific information concerning humans to the design of objects. Ergonomic intervention results in improvement of working posture and a decrease in prevalence of musculoskeletal symptoms. Stretching and resistance exercises to the neck are easy to do, when performed 1-2 times daily reduce discomfort and ease neck stiffness. This study is aimed at finding if ergonomics with exercises to the neck prove beneficial to reduce neck pain in Computer Professionals. The outcomes measures used were: Oswestry neck disability index and VAS score for pain. 100 subjects satisfying the inclusion criteria were included in the study. Results: Ergonomic intervention along with isometric neck exercises and stretching proved to reduce neck pain and disability among computer professionals.

Keywords: ergonomics, neck pain, neck exercises, physiotherapy for neck pain

Procedia PDF Downloads 306
8779 Bayesian Value at Risk Forecast Using Realized Conditional Autoregressive Expectiel Mdodel with an Application of Cryptocurrency

Authors: Niya Chen, Jennifer Chan

Abstract:

In the financial market, risk management helps to minimize potential loss and maximize profit. There are two ways to assess risks; the first way is to calculate the risk directly based on the volatility. The most common risk measurements are Value at Risk (VaR), sharp ratio, and beta. Alternatively, we could look at the quantile of the return to assess the risk. Popular return models such as GARCH and stochastic volatility (SV) focus on modeling the mean of the return distribution via capturing the volatility dynamics; however, the quantile/expectile method will give us an idea of the distribution with the extreme return value. It will allow us to forecast VaR using return which is direct information. The advantage of using these non-parametric methods is that it is not bounded by the distribution assumptions from the parametric method. But the difference between them is that expectile uses a second-order loss function while quantile regression uses a first-order loss function. We consider several quantile functions, different volatility measures, and estimates from some volatility models. To estimate the expectile of the model, we use Realized Conditional Autoregressive Expectile (CARE) model with the bayesian method to achieve this. We would like to see if our proposed models outperform existing models in cryptocurrency, and we will test it by using Bitcoin mainly as well as Ethereum.

Keywords: expectile, CARE Model, CARR Model, quantile, cryptocurrency, Value at Risk

Procedia PDF Downloads 96
8778 Progress and Challenges of Smart Cities in India: An Exploratory Study

Authors: Sushil K. Sharma, Jeff Zhang, Saeed Tabar

Abstract:

Worldwide, several governments are utilizing the Internet of Things (IoT) and other information and communication technologies (ICTs) to create smart city infrastructures to improve both the quality of government services and citizen welfare. Over 700 cities from around the world have already started implementing their smart city projects. Smart City utilizes the network of connected things, or the Internet of Things (IoT), that interconnects devices and various components across city infrastructure, making them work together seamlessly to enhance the quality, performance, and interactivity of urban services, optimize resources, and reduce costs. Without developing smart cities, the accelerating growth of cities, and their disproportionate consumption of physical and social resources are unsustainable. In 2016, the Indian Government released a list of 100 cities with the intention of kick-starting the process of developing them into 'smart cities’ as part of the Smart Cities Mission. This study reports the progress and challenges of Smart City projects in India. The data were collected through the city/state government websites, media reports, and focus group discussions/interviews. The preliminary results indicate that smart city projects are not only behind in their implementation and scope but also lacks the sincerity for its implementation.

Keywords: smart city, smart government, Internet of Things, digital government

Procedia PDF Downloads 163
8777 Performance Analysis of Deterministic Stable Election Protocol Using Fuzzy Logic in Wireless Sensor Network

Authors: Sumanpreet Kaur, Harjit Pal Singh, Vikas Khullar

Abstract:

In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols.

Keywords: DSEP, fuzzy logic, energy model, WSN

Procedia PDF Downloads 189
8776 Measurement of Convective Heat Transfer from a Vertical Flat Plate Using Mach-Zehnder Interferometer with Wedge Fringe Setting

Authors: Divya Haridas, C. B. Sobhan

Abstract:

Laser interferometric methods have been utilized for the measurement of natural convection heat transfer from a heated vertical flat plate, in the investigation presented here. The study mainly aims at comparing two different fringe orientations in the wedge fringe setting of Mach-Zehnder interferometer (MZI), used for the measurements. The interference fringes are set in horizontal and vertical orientations with respect to the heated surface, and two different fringe analysis methods, namely the stepping method and the method proposed by Naylor and Duarte, are used to obtain the heat transfer coefficients. The experimental system is benchmarked with theoretical results, thus validating its reliability in heat transfer measurements. The interference fringe patterns are analyzed digitally using MATLAB 7 and MOTIC Plus softwares, which ensure improved efficiency in fringe analysis, hence reducing the errors associated with conventional fringe tracing. The work also discuss the relative merits and limitations of the two methods used.

Keywords: Mach-Zehnder interferometer (MZI), natural convection, Naylor method, Vertical Flat Plate

Procedia PDF Downloads 351
8775 Artificial Intelligent Tax Simulator to Minimize Tax Liability for Multinational Corporations

Authors: Sean Goltz, Michael Mayo

Abstract:

The purpose of this research is to use Global-Regulation.com database of the world laws, focusing on tax treaties between countries, in order to create an AI-driven tax simulator that will run an AI agent through potential tax scenarios across countries. The AI agent goal is to identify the scenario that will result in minimum tax liability based on tax treaties between countries. The results will be visualized by a three dimensional matrix. This will be an online web application. Multinational corporations are running their business through multiple countries. These countries, in turn, have a tax treaty with many other countries to regulate the payment of taxes on income that is transferred between these countries. As a result, planning the best tax scenario across multiple countries and numerous tax treaties is almost impossible. This research propose to use Global-Regulation.com database of word laws in English (machine translated by Google and Microsoft API’s) in order to create a simulator that will include the information in the tax treaties. Once ready, an AI agent will be sent through the simulator to identify the scenario that will result in minimum tax liability. Identifying the best tax scenario across countries may save multinational corporations, like Google, billions of dollars annually. Given the nature of the raw data and the domain of taxes (i.e., numbers), this is a promising ground to employ artificial intelligence towards a practical and beneficial purpose.

Keywords: taxation, law, multinational, corporation

Procedia PDF Downloads 182
8774 Evaluating the Effects of Community Informatics on Sustainable Livelihoods: a Case Model for Rural Communities in Nigeria

Authors: Adebayo J. Julius, Oluremi N. Iluyomade

Abstract:

Livelihood in Nigeria is a paradox of poverty amidst plenty. The Country is endowed with a good climate for agriculture, naturally growing fruit trees and vegetables, and undomesticated water resources. In spite of all its endowment, Nigeria continues to live in poverty year in year out. Rural communities adopted for this study are Ido, Omi-Adio, Onigambari, Okija and Lambata, 500 questionnaires were administered to solicit information from the respondents. This study focused on comparative analysis of the utilization of community informatics for sustainable livelihoods through agriculture. The idea projected in this study is that small strategic changes in the modus operandi of social informatics can have a significant impact on the sustainability of livelihoods. This paper carefully explored the theories of community informatics and its efficacies in dealing with sustainability issues. This study identified, described and evaluates the roles of community informatics in some sectors of the economy, different analytical tools to benchmark the influence of social informatics in agriculture against what is obtainable in agricultural sectors of the economy were used. It further employed comparative analysis to build a case model for sustainable livelihood in agriculture through community informatics.

Keywords: informatics, model, rural community, livelihood, Nigeria

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8773 Dilution Effect in Islamic Finance: The Case of Convertible Sukuk

Authors: Mahfoud Djebbar

Abstract:

Stock dilution is a financial phenomenon resulting from the issue of additional shares by a company, or when holders convert their convertibles into new shares (capital increase). This issue and/or conversion enlarge the company’s share base that will result in marginal dilution (loss) for existing shareholders, and a benefit to new ones. Dilution issues have already been addressed in mainstream finance, particularly as far as information disclosure is concerned. However, in Islamic finance, stock dilution problems have not been deeply studied and the subject has not received sufficient attention from shariah-compatible firms, investors, and scholars. In this regard, this paper emphasises the forms, the effects of capital dilution on current shareholders as well as the ways and techniques of compensating them. And since the research in this field, in its Islamic perspective, is still in its infancy, the paper tries to analyse the phenomenon theoretically in detail using numerical examples, and expose some case studies of Shariah-compliant issuers of convertible Sukuk and how they compensate their existing shareholders. Finally, this study shows that the Sukuk issuers compensate old shareholders using the right of shuf’ah as a well known and practiced pre-emptive right in Islamic transactions centuries ago, as well as the ways conventional bond issuers use.

Keywords: compensating shareholders, convertible Sukuk, Islamic financial innovation, Shuf’ah

Procedia PDF Downloads 316
8772 Effects of Thermal Properties of Aggregate Materials on Energy Consumption and Ghg Emissions of Transportation Infrastructure Assets Construction: Case Study for Japan

Authors: Ali Jamshidi, Kiyofumi Kurumisawa, Toyoharu Nawa

Abstract:

Transportation infrastructure assets can be considered as backbone of transportation system. They are routinely developed and or maintained which can be used effectively for movement of passengers, commodities and providing vital services. However, the infrastructure assets construction, maintenance and rehabilitation significantly depend on non-renewable natural resources, such as carbon-based energy carriers and aggregate materials. In this study, effects of thermal properties of aggregate materials were characterized for production of hot-mix asphalt in Japan, as a case study. The results indicated that incorporation of the aggregate with lower required heat energy significantly reduces fuel consumption greenhouse gas emission, irrespective of physical property of aggregate. The results also clearly showed that as 75% high-energy limestone is replaced with low-energy limestone in producing an asphalt mixture at 180 °C, 97,879 Japanese households would be energized per annum using the saved energy without any modification in the current asphalt mixing plants.

Keywords: zero energy infrastructure, sustainable development, greenhouse gas emission, asphalt pavement

Procedia PDF Downloads 227
8771 Deep Learning Based Road Crack Detection on an Embedded Platform

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

Abstract:

It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

Procedia PDF Downloads 326
8770 Multi-Modal Visualization of Working Instructions for Assembly Operations

Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

Abstract:

Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

Procedia PDF Downloads 153
8769 New Opportunities in Business as a Result of the Corona Virus

Authors: Lasha Kamashidze

Abstract:

COVID19 has already become one of the biggest challenges in the modern world. The virus has also had a significant impact on the world economy, which has faced a major crisis. Each crisis and challenge creates new opportunities. Changes in the world have allowed us to see business in a new light. The aim of the article is to explore new opportunities in the business that have arisen as a result of the Corona virus. Now, organizations with a service profile are working to meet the rapidly changing needs of their staff and customers. Due to the situation created by the pandemic, it became necessary to make some changes in people's daily lives. It became necessary to adapt to the new reality. The changes caused by Coronavirus require in-depth research and analysis in the world economy, as the current situation is not ruled out to be repeated in the future. Many companies have resorted to remote work methods, which require organizational changes. The form of remote work is not new to the Georgian reality. In Georgia, as well as in the rest of the world, the business sector has undergone changes. It will be beneficial for many Georgian companies to make organizational changes that will allow them to work remotely. The current situation has shown the managers of both Georgian and other companies to have "weak points" in organizing modern business. A survey was conducted (online survey), as a result of which it received important information about the problems of remote work in Georgia.

Keywords: organizational change, coronomics, remote work, management

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8768 Developing a Performance Measurement System for Arts-Based Initiatives: Action Research on Italian Corporate Museums

Authors: Eleonora Carloni, Michela Arnaboldi

Abstract:

In academia, the investigation of the relationship between cultural heritage and corporations is ubiquitous in several fields of studies. In practice corporations are more and more integrating arts and cultural heritage in their strategies for disparate benefits, such as: to foster customer’s purchase intention with authentic and aesthetic experiences, to improve their reputation towards local communities, and to motivate employees with creative thinking. There are diverse forms under which corporations set these artistic interventions, from sponsorships to arts-based training centers for employees, but scholars agree that the maximum expression of this cultural trend are corporate museums, growing in number and relevance. Corporate museums are museum-like settings, hosting artworks of corporations’ history and interests. In academia they have been ascribed as strategic asset and they have been associated with diverse uses for corporations’ benefits, from place for preservation of cultural heritage, to tools for public relations and cultural flagship stores. Previous studies have thus extensively but fragmentally studied the diverse benefits of corporate museum opening to corporations, with a lack of comprehensive approach and a digression on how to evaluate and report corporate museum’s performances. Stepping forward, the present study aims to investigate: 1) what are the key performance measures corporate museums need to report to the associated corporations; 2) how are the key performance measures reported to the concerned corporations. This direction of study is not only suggested as future direction in academia but it has solid basis in practice, aiming to answer to the need of corporate museums’ directors to account for corporate museum’s activities to the concerned corporation. Coherently, at an empirical level the study relies on action research method, whose distinctive feature is to develop practical knowledge through a participatory process. This paper indeed relies on the experience of a collaborative project between the researchers and a set of corporate museums in Italy, aimed at co-developing a performance measurement system. The project involved two steps: a first step, in which researchers derived the potential performance measures from literature along with exploratory interviews; a second step, in which researchers supported the pool of corporate museums’ directors in co-developing a set of key performance indicators for reporting. Preliminary empirical findings show that while scholars insist on corporate museums’ capability to develop networking relations, directors insist on the role of museums as internal supplier of knowledge for innovation goals. Moreover, directors stress museums’ cultural mission and outcomes as potential benefits for corporation, by remarking to include both cultural and business measures in the final tool. In addition, they give relevant attention to the wording used in humanistic terms while struggling to express all measures in economic terms. The paper aims to contribute to corporate museums’ and more broadly to arts-based initiatives’ literature in two directions. Firstly, it elaborates key performance measures with related indicators to report on cultural initiatives for corporations. Secondly, it provides evidence of challenges and practices to handle reporting on these initiatives, because of tensions arising from the co-existence of diverse perspectives, namely arts and business worlds.

Keywords: arts-based initiative, corporate museum, hybrid organization, performance measurement

Procedia PDF Downloads 166
8767 Regulated Output Voltage Double Switch Buck-Boost Converter for Photovoltaic Energy Application

Authors: M. Kaouane, A. Boukhelifa, A. Cheriti

Abstract:

In this paper, a new Buck-Boost DC-DC converter is designed and simulated for photovoltaic energy system. The presented Buck-Boost converter has a double switch. Moreover, its output voltage is regulated to a constant value whatever its input is. In the presented work, the Buck-Boost transfers the produced energy from the photovoltaic generator to an R-L load. The converter is controlled by the pulse width modulation technique in a way to have a suitable output voltage, in the other hand, to carry the generator’s power, and put it close to the maximum possible power that can be generated by introducing the right duty cycle of the pulse width modulation signals that control the switches of the converter; each component and each parameter of the proposed circuit is well calculated using the equations that describe each operating mode of the converter. The proposed configuration of Buck-Boost converter has been simulated in Matlab/Simulink environment; the simulation results show that it is a good choice to take in order to maintain the output voltage constant while ensuring a good energy transfer.

Keywords: Buck-Boost converter, switch, photovoltaic, PWM, power, energy transfer

Procedia PDF Downloads 883
8766 Child-Friendly Cities: A Child's Participation in the Local Government to Improve the Status of Rights of the Child

Authors: Asma Khalid

Abstract:

Children’s drawings are unique as children are. Children manifest their happiness, sadness, future dreams, likes, dislikes through drawings. Research with children aged 8-12 was conducted in 2017 in which it was asked to them ‘what they think about child-friendly cities?’ The focus was to get ideas from children about the cities in which they live and what they want in their cities. The research was conducted in different private schools. Children were accessed through teachers and principals of the schools (the gatekeepers). Consent forms were developed for children which contained information about the research project and their consent was taken on paper. It was ensured that children are not forced to take part in the research and they can leave the research whenever they want, without informing anyone. The qualitative participatory approach was taken where children were given papers and colors to draw their ideas. During the research, it was found that children are interested in showing their emotions and liking through drawing as this medium seems easy and comfortable to them as compared to have the individual face to face interviews or participate in surveys. However, the clarity of the ideas presented in the drawings was discussed at length with children in their school’s premises. Results of the research show that children like to live in clean, green places which are also safe for them. Furthermore, they want to live with their families and want to have recreational activities including parks in their nearby vicinity.

Keywords: qualitative participative research clean, children, drawing, clean, green and protected place, family

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8765 Detectability Analysis of Typical Aerial Targets from Space-Based Platforms

Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

Abstract:

In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms.

Keywords: space-based detection, aerial targets, detectability analysis, scene environment

Procedia PDF Downloads 134
8764 Collaborative Leadership in a Post-COVID-19 Era in Saudi Arabia

Authors: Norah Alshayhan

Abstract:

Dealing with public problems is one of the struggles that may face the leaders in the public sector. Collaborative leadership is one of the most important approaches in dealing with difficult situations that affect both public, private, and nonprofit organizations. Current literature does not show exactly the extent of utilizing collaborative leadership during the post-COVID-19 world in Saudi Arabia. This study is worth exploring in order to examine collaborative leadership in similar environments. This research will utilize both integrative public leadership and transformational leadership theories to guide the researcher in answering the research question. The researcher utilizes content analysis and reviews government documents, plans, and reports to gain more information about collaborative leadership in Saudi Arabia. The researcher analyzes the data in themes and sub-themes to categorize the data in answering the research question. Leader’s behavior and performance in the public sector will be the focus of this study. Findings from this research will benefit leaders in both public, private, and nonprofit sectors in their leadership during a post-disaster time. Findings from this study support collaborative leadership practices and performance in leading future post-crises/disasters.

Keywords: collaborative leadership, post-COVID-19, Saudi Arabia, performance, skills

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8763 A Technique for Image Segmentation Using K-Means Clustering Classification

Authors: Sadia Basar, Naila Habib, Awais Adnan

Abstract:

The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

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8762 Vibratinal Spectroscopic Identification of Beta-Carotene in Usnic Acid and PAHs as a Potential Martian Analogue

Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

Abstract:

Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: raman spectroscopy, mars-analog, beta-carotene, PAHs

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8761 City versus Suburb: The Effects of Neighborhood on Place Attachment and Residential Satisfaction

Authors: Elif Aksel, Çagrı Imamoglu

Abstract:

This ongoing study aims to investigate the effects of neighborhood location on place attachment and residential satisfaction. Place attachment will be examined by comparing place of residence in different areas of the city. Furthermore, the relationship between neighborhood and residential satisfaction will be investigated in terms of physical and social aspects of the places influencing residential satisfaction. This study will be carried out in two different districts of Ankara which are Çankaya, located in the city center, and Sincan, a suburb. Two-hundred adult respondents will participate in this research; 100 men and 100 women aged between 18-65 years with different socio-economic status using snowball sampling. A place attachment scale and a questionnaire related with residential satisfaction, including open-ended questions and 7-point Likert type scale, will be used as instruments. Apart from these, demographic information of the participants such as gender, age, education, the length of residence will be collected. The findings of the study are expected to demonstrate that neighborhood is seen to be influential on place attachment by affecting the intensity of attachment. The level of place attachment is expected to be greater in areas far from the city compared to areas in the center of the city. Apart from this, the neighborhood is also effective in residential satisfaction. The residents living in these neighborhoods having strong physical and social opportunities will be expected to have higher residential satisfaction.

Keywords: neighborhood, neighborhood satisfaction, place attachment, residential satisfaction

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8760 Multi-Vehicle Detection Using Histogram of Oriented Gradients Features and Adaptive Sliding Window Technique

Authors: Saumya Srivastava, Rina Maiti

Abstract:

In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

Procedia PDF Downloads 110