Search results for: data infrastructure
24749 Challenges and Opportunities of Cloud-Based E-Learning Systems
Authors: Kashif Laeeq, Zubair A. Shaikh
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The paradigm of education is drastically changing from conventional to e-learning model. Due to ease of learning with various other benefits, several educational institutions are adopting the e-learning models. Some institutions are still willing to transform their educational system on to e-learning, but due to limited resources, they are still compromising on the old traditional system. The cloud computing could be one of the best solutions to overcome this problem by providing hardware, software, and infrastructure resources with cost efficient manner. The adoption of cloud computing in education will bring revolution in this paradigm. This paper introduces various positive features of e-learning and presents a way how cloud computing technology can be provisioned e-learning model. This paper also investigates the numerous challenges and opportunities that would be observed in cloud computing adoption in e-learning domain. The concept and knowledge present in this paper may create a new direction of research in the domain of cloud-based e-learning.Keywords: cloud-based e-learning, e-learning, cloud computing application, smart learning
Procedia PDF Downloads 41224748 A Biometric Template Security Approach to Fingerprints Based on Polynomial Transformations
Authors: Ramon Santana
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The use of biometric identifiers in the field of information security, access control to resources, authentication in ATMs and banking among others, are of great concern because of the safety of biometric data. In the general architecture of a biometric system have been detected eight vulnerabilities, six of them allow obtaining minutiae template in plain text. The main consequence of obtaining minutia templates is the loss of biometric identifier for life. To mitigate these vulnerabilities several models to protect minutiae templates have been proposed. Several vulnerabilities in the cryptographic security of these models allow to obtain biometric data in plain text. In order to increase the cryptographic security and ease of reversibility, a minutiae templates protection model is proposed. The model aims to make the cryptographic protection and facilitate the reversibility of data using two levels of security. The first level of security is the data transformation level. In this level generates invariant data to rotation and translation, further transformation is irreversible. The second level of security is the evaluation level, where the encryption key is generated and data is evaluated using a defined evaluation function. The model is aimed at mitigating known vulnerabilities of the proposed models, basing its security on the impossibility of the polynomial reconstruction.Keywords: fingerprint, template protection, bio-cryptography, minutiae protection
Procedia PDF Downloads 17324747 Improving Digital Data Security Awareness among Teacher Candidates with Digital Storytelling Technique
Authors: Veysel Çelik, Aynur Aker, Ebru Güç
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Developments in information and communication technologies have increased both the speed of producing information and the speed of accessing new information. Accordingly, the daily lives of individuals have started to change. New concepts such as e-mail, e-government, e-school, e-signature have emerged. For this reason, prospective teachers who will be future teachers or school administrators are expected to have a high awareness of digital data security. The aim of this study is to reveal the effect of the digital storytelling technique on the data security awareness of pre-service teachers of computer and instructional technology education departments. For this purpose, participants were selected based on the principle of volunteering among third-grade students studying at the Computer and Instructional Technologies Department of the Faculty of Education at Siirt University. In the research, the pretest/posttest half experimental research model, one of the experimental research models, was used. In this framework, a 6-week lesson plan on digital data security awareness was prepared in accordance with the digital narration technique. Students in the experimental group formed groups of 3-6 people among themselves. The groups were asked to prepare short videos or animations for digital data security awareness. The completed videos were watched and evaluated together with prospective teachers during the evaluation process, which lasted approximately 2 hours. In the research, both quantitative and qualitative data collection tools were used by using the digital data security awareness scale and the semi-structured interview form consisting of open-ended questions developed by the researchers. According to the data obtained, it was seen that the digital storytelling technique was effective in creating data security awareness and creating permanent behavior changes for computer and instructional technology students.Keywords: digital storytelling, self-regulation, digital data security, teacher candidates, self-efficacy
Procedia PDF Downloads 13024746 A Remote Sensing Approach to Calculate Population Using Roads Network Data in Lebanon
Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba
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In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.Keywords: population, road network, statistical correlations, remote sensing
Procedia PDF Downloads 16824745 A Multicopy Strategy for Improved Security Wireless Sensor Network
Authors: Tuğçe Yücel
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A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.Keywords: MIP, sensor, telecommunications, WSN
Procedia PDF Downloads 51724744 Research on the Ecological Impact Evaluation Index System of Transportation Construction Projects
Authors: Yu Chen, Xiaoguang Yang, Lin Lin
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Traffic engineering construction is an important infrastructure for economic and social development. In the process of construction and operation, the ability to make a correct evaluation of the project's environmental impact appears to be crucial to the rational operation of existing transportation projects, the correct development of transportation engineering construction and the adoption of corresponding measures to scientifically carry out environmental protection work. Most of the existing research work on ecological and environmental impact assessment is limited to individual aspects of the environment and less to the overall evaluation of the environmental system; in terms of research conclusions, there are more qualitative analyses from the technical and policy levels, and there is a lack of quantitative research results and quantitative and operable evaluation models. In this paper, a comprehensive analysis of the ecological and environmental impacts of transportation construction projects is conducted, and factors such as the accessibility of data and the reliability of calculation results are comprehensively considered to extract indicators that can reflect the essence and characteristics. The qualitative evaluation indicators were screened using the expert review method, the qualitative indicators were measured using the fuzzy statistics method, the quantitative indicators were screened using the principal component analysis method, and the quantitative indicators were measured by both literature search and calculation. An environmental impact evaluation index system with the general objective layer, sub-objective layer and indicator layer was established, dividing the environmental impact of the transportation construction project into two periods: the construction period and the operation period. On the basis of the evaluation index system, the index weights are determined using the hierarchical analysis method, and the individual indicators to be evaluated are dimensionless, eliminating the influence of the original background and meaning of the indicators. Finally, the thesis uses the above research results, combined with the actual engineering practice, to verify the correctness and operability of the evaluation method.Keywords: transportation construction projects, ecological and environmental impact, analysis and evaluation, indicator evaluation system
Procedia PDF Downloads 11224743 Wikipedia World: A Computerized Process for Cultural Heritage Data Dissemination
Authors: L. Rajaonarivo, M. N. Bessagnet, C. Sallaberry, A. Le Parc Lacayrelle, L. Leveque
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TCVPYR is a European FEDER (European Regional Development Fund) project which aims to promote tourism in the French Pyrenees region by leveraging its cultural heritage. It involves scientists from various domains (geographers, historians, anthropologists, computer scientists...). This paper presents a fully automated process to publish any dataset as Wikipedia articles as well as the corresponding linked information on Wikidata and Wikimedia Commons. We validate this process on a sample of geo-referenced cultural heritage data collected by TCVPYR researchers in different regions of the Pyrenees. The main result concerns the technological prerequisites, which are now in place. Moreover, we demonstrated that we can automatically publish cultural heritage data on Wikimedia.Keywords: cultural heritage dissemination, digital humanities, open data, Wikimedia automated publishing
Procedia PDF Downloads 13024742 Adaptive Decision Feedback Equalizer Utilizing Fixed-Step Error Signal for Multi-Gbps Serial Links
Authors: Alaa Abdullah Altaee
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This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication
Procedia PDF Downloads 12624741 Data-Driven Market Segmentation in Hospitality Using Unsupervised Machine Learning
Authors: Rik van Leeuwen, Ger Koole
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Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.Keywords: hierarchical cluster analysis, hospitality, market segmentation
Procedia PDF Downloads 11124740 Geographic Information System for Simulating Air Traffic By Applying Different Multi-Radar Positioning Techniques
Authors: Amara Rafik, Mostefa Belhadj Aissa
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Radar data is one of the many data sources used by ATM Air Traffic Management systems. These data come from air navigation radar antennas. These radars intercept signals emitted by the various aircraft crossing the controlled airspace and calculate the position of these aircraft and retransmit their positions to the Air Traffic Management System. For greater reliability, these radars are positioned in such a way as to allow their coverage areas to overlap. An aircraft will therefore be detected by at least one of these radars. However, the position coordinates of the same aircraft and sent by these different radars are not necessarily identical. Therefore, the ATM system must calculate a single position (radar track) which will ultimately be sent to the control position and displayed on the air traffic controller's monitor. There are several techniques for calculating the radar track. Furthermore, the geographical nature of the problem requires the use of a Geographic Information System (GIS), i.e. a geographical database on the one hand and geographical processing. The objective of this work is to propose a GIS for traffic simulation which reconstructs the evolution over time of aircraft positions from a multi-source radar data set and by applying these different techniques.Keywords: ATM, GIS, radar data, simulation
Procedia PDF Downloads 12424739 Exploring Gaming-Learning Interaction in MMOG Using Data Mining Methods
Authors: Meng-Tzu Cheng, Louisa Rosenheck, Chen-Yen Lin, Eric Klopfer
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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 36124738 From Two-Way to Multi-Way: A Comparative Study for Map-Reduce Join Algorithms
Authors: Marwa Hussien Mohamed, Mohamed Helmy Khafagy
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Map-Reduce is a programming model which is widely used to extract valuable information from enormous volumes of data. Map-reduce designed to support heterogeneous datasets. Apache Hadoop map-reduce used extensively to uncover hidden pattern like data mining, SQL, etc. The most important operation for data analysis is joining operation. But, map-reduce framework does not directly support join algorithm. This paper explains and compares two-way and multi-way map-reduce join algorithms for map reduce also we implement MR join Algorithms and show the performance of each phase in MR join algorithms. Our experimental results show that map side join and map merge join in two-way join algorithms has the longest time according to preprocessing step sorting data and reduce side cascade join has the longest time at Multi-Way join algorithms.Keywords: Hadoop, MapReduce, multi-way join, two-way join, Ubuntu
Procedia PDF Downloads 49224737 Learning Grammars for Detection of Disaster-Related Micro Events
Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev
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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter
Procedia PDF Downloads 48424736 An Assessment of Rice Yield Improvement Among Smallholder Rice Farmers in Asunafo North Municipality of Ghana
Authors: Isaac Diaka, Matsui Kenichi
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Ghana’s rice production has increased mainly because of increased cultivated areas. On this point, scholars who promoted crop production increase for food security have overlooked the fact that its per-acre yield has not increased. Also, Ghana’s domestic rice production has not contributed much to domestic rice consumption especially in major cities where consumers tend to rely on imported rice from Asia. Considering these points, the paper seeks to understand why smallholder rice farmers have not been able to increase per acre rice yield. It also examines smallholder rice farmers’ rice yield improvement needs, and the relationship that exist between rice farmers’ socioeconomic factors and their yield levels by rice varieties. The study adopted a simple random sampling technique to select 154 rice farmers for a questionnaire survey between October and November 2020. The data was analyzed by performing a correlation analysis, an independent t-test, and Kendall’s coefficient of concordance. The results showed that 58.4% of the respondents cultivated popular high-yield varieties like AGRA and Jasmine. The rest used local varieties. Regarding respondents’ yield differentials, AGRA and Jasmine had an average yield of 2.6 mt/ha, which is higher than that of local varieties (1.6mt/ha). The study found untimely availability of improved seed varieties and high cost of inputs some of the major reasons affecting yield in the area. For respondents’ yield improvement needs, Kendall’s coefficient of concordance showed that access to improved varieties, irrigation infrastructure, and row planting were respondents’ major technological needs. As to their non-technological needs, the respondents needed timely information about rice production, access to credit support options, and extension services. The correlation analysis revealed that farm size and off-farm income exhibited a positive and negative association towards respondents’ yield level, respectively. This paper then discusses recommendations for providing with improved rice production technologies to farmers.Keywords: Ghana, rice, smallholder farmers, yield improvement.
Procedia PDF Downloads 9824735 Regulating Issues concerning Data Protection in Cloud Computing: Developing a Saudi Approach
Authors: Jumana Majdi Qutub
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Rationale: Cloud computing has rapidly developed the past few years. Because of the importance of providing protection for personal data used in cloud computing, the role of data protection in promoting trust and confidence in users’ data has become an important policy priority. This research examines key regulatory challenges rose by the growing use and importance of cloud computing with focusing on protection of individuals personal data. Methodology: Describing and analyzing governance challenges facing policymakers and industry in Saudi Arabia, with an account of anticipated governance responses. The aim of the research is to describe and define the regulatory challenges on cloud computing for policy making in Saudi Arabia and comparing it with potential complied issues rose in respect of transported data to EU member state. In addition, it discusses information privacy issues. Finally, the research proposes policy recommendation that would resolve concerns surrounds the privacy and effectiveness of clouds computing frameworks for data protection. Results: There are still no clear regulation in Saudi Arabia specialized in legalizing cloud computing and specialty regulations in transferring data internationally and locally. Decision makers need to review the applicable law in Saudi Arabia that protect information in cloud computing. This should be from an international and a local view in order to identify all requirements surrounding this area. It is important to educate cloud computing users about their information value and rights before putting it in the cloud to avoid further legal complications, such as making an educational program to prevent giving personal information to a bank employee. Therefore, with many kinds of cloud computing services, it is important to have it covered by the law in all aspects.Keywords: cloud computing, cyber crime, data protection, privacy
Procedia PDF Downloads 26324734 Multistage Data Envelopment Analysis Model for Malmquist Productivity Index Using Grey's System Theory to Evaluate Performance of Electric Power Supply Chain in Iran
Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh
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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.Keywords: Malmquist Index, Grey's Theory, CCR Model, network data envelopment analysis, Iran electricity power chain
Procedia PDF Downloads 17024733 Cloud Shield: Model to Secure User Data While Using Content Delivery Network Services
Authors: Rachna Jain, Sushila Madan, Bindu Garg
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Cloud computing is the key powerhouse in numerous organizations due to shifting of their data to the cloud environment. In recent years it has been observed that cloud-based-services are being used on large scale for content storage, distribution and processing. Various issues have been observed in cloud computing environment that need to be addressed. Security and privacy are found topmost concern area. In this paper, a novel security model is proposed to secure data by utilizing CDN services like image to icon conversion. CDN Service is a content delivery service which converts an image to icon, word to pdf & Latex to pdf etc. Presented model is used to convert an image into icon by keeping image secret. Here security of image is imparted so that image should be encrypted and decrypted by data owners only. It is also discussed in the paper that how server performs multiplication and selection on encrypted data without decryption. The data can be image file, word file, audio or video file. Moreover, the proposed model is capable enough to multiply images, encrypt them and send to a server application for conversion. Eventually, the prime objective is to encrypt an image and convert the encrypted image to image Icon by utilizing homomorphic encryption.Keywords: cloud computing, user data security, homomorphic encryption, image multiplication, CDN service
Procedia PDF Downloads 34024732 Data Mining Approach: Classification Model Evaluation
Authors: Lubabatu Sada Sodangi
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The rapid growth in exchange and accessibility of information via the internet makes many organisations acquire data on their own operation. The aim of data mining is to analyse the different behaviour of a dataset using observation. Although, the subset of the dataset being analysed may not display all the behaviours and relationships of the entire data and, therefore, may not represent other parts that exist in the dataset. There is a range of techniques used in data mining to determine the hidden or unknown information in datasets. In this paper, the performance of two algorithms Chi-Square Automatic Interaction Detection (CHAID) and multilayer perceptron (MLP) would be matched using an Adult dataset to find out the percentage of an/the adults that earn > 50k and those that earn <= 50k per year. The two algorithms were studied and compared using IBM SPSS statistics software. The result for CHAID shows that the most important predictors are relationship and education. The algorithm shows that those are married (husband) and have qualification: Bachelor, Masters, Doctorate or Prof-school whose their age is > 41<57 earn > 50k. Also, multilayer perceptron displays marital status and capital gain as the most important predictors of the income. It also shows that individuals that their capital gain is less than 6,849 and are single, separated or widow, earn <= 50K, whereas individuals with their capital gain is > 6,849, work > 35 hrs/wk, and > 27yrs their income will be > 50k. By comparing the two algorithms, it is observed that both algorithms are reliable but there is strong reliability in CHAID which clearly shows that relation and education contribute to the prediction as displayed in the data visualisation.Keywords: data mining, CHAID, multi-layer perceptron, SPSS, Adult dataset
Procedia PDF Downloads 38224731 Developing an Information Model of Manufacturing Process for Sustainability
Authors: Jae Hyun Lee
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Manufacturing companies use life-cycle inventory databases to analyze sustainability of their manufacturing processes. Life cycle inventory data provides reference data which may not be accurate for a specific company. Collecting accurate data of manufacturing processes for a specific company requires enormous time and efforts. An information model of typical manufacturing processes can reduce time and efforts to get appropriate reference data for a specific company. This paper shows an attempt to build an abstract information model which can be used to develop information models for specific manufacturing processes.Keywords: process information model, sustainability, OWL, manufacturing
Procedia PDF Downloads 43324730 An Interpretable Data-Driven Approach for the Stratification of the Cardiorespiratory Fitness
Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers
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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning
Procedia PDF Downloads 28924729 Life Cycle Assessment in Road Pavements: A Literature Review and the Potential Use in Brazil
Authors: B. V. Santos, M. T. M. Carvalho, J. H. S. Rêgo
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The article presents a literature review on recent advances related to studies of the environmental impact of road pavements, with reference to the concepts of Life Cycle Assessment (LCA). An introduction with the main motivations for the development of the research is presented, with a current overview of the Brazilian transport infrastructure and the projections for the road mode for the coming years, and the possibility of using the referred methodology by the road sector in Brazil. The article explores the origin of LCA in road pavements and the details linked to its implementation from the perspective of the four main phases of the study (goal and scope definition, inventory analysis, impact assessment, and interpretation). Finally, the main advances and deficiencies observed in the selected studies are gathered, with the proposition of research fields that can be explored in future national or international studies of LCA of road pavements.Keywords: Brazil, life cycle assessment, road pavements, sustainable
Procedia PDF Downloads 8224728 India’s Developmental Assistance in Africa: Analyzing India’s Aid and Developmental Projects
Authors: Daniel Gidey, Kunwar Siddarth Dadhwal
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By evaluating India's aid systems and ongoing development initiatives, this conference paper offers light on India's role as a source of developmental assistance in Africa. This research attempts to provide insights into the developing landscape of foreign aid and development cooperation by focusing on understanding India's motivations and strategy. In recent years, India's connection with Africa has grown significantly, driven by economic, political, and strategic reasons. This conference paper covers India's many forms of aid, including financial, capacity building efforts, technical assistance, and infrastructure development projects, via a thorough investigation. The article seeks to establish India's priorities and highlight the possible impacts of its development assistance in Africa by examining the industries and locations of concentration. Using secondary data sources, the investigation delves into the underlying goals of India's aid policy in Africa. It investigates whether India's development assistance is consistent with its broader geopolitical aims, such as access to resources, competing with regional rivals, or strengthening diplomatic ties. Furthermore, the article investigates how India's aid policy combines the ideals of South-South cooperation and mutual development, as well as the ramifications for recipient countries. Furthermore, the paper assesses the efficacy and sustainability of India's aid operations in Africa. It takes into account the elements that influence their success, the problems they face, and the amount to which they contribute to local development goals, community empowerment, and poverty alleviation. The study also focuses on the accountability systems, transparency, and knowledge transfer aspects of India's development assistance. By providing a detailed examination of India's aid endeavors in Africa, the paper adds to the current literature on international development cooperation. By offering fresh insights into the motives, strategies, and impacts of India's assistance programs, it seeks to enhance understanding of the emerging patterns in South-South cooperation and the complex dynamics of contemporary international aid architecture.Keywords: India, Africa, developmental assistance, aid projects and South-South cooperation
Procedia PDF Downloads 6724727 Infrastructure Problems in Indonesia: The Uncontrolled Increase of Motor Vehicle Usage in Indonesia
Authors: Tanda Soala Gogo Sirait
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The existence of motor vehicle in Indonesia has a very essential role for daily mobility in urban areas. The motor vehicle market is growing tremendously particularly for the motorcycle. The growth of motorcycles ownership was 15 % annually from 2002 to 2012. It is predicted that the number of motorcycles still continue to grow in the future. The increase of motor vehicle has led to the creation of serious urban problems and Indonesian economy structure. Today, Indonesia's cities are well known as the jungle of motorcycle world. The volume of motor vehicle traffic in Indonesia cities is astounding, which more than 55% of motorised transport is on motorcycle and car. The reason it happens is due lack and inconvenient of the public transportation in Indonesia. Motor vehicle ownership by individual households tends to rising rapidly. Indonesian government still does not have a clear direction how to face this phenomenon.Keywords: Indonesian economy, inconvenient public transportation, motor vehicle growth, urban problems
Procedia PDF Downloads 44524726 Dissecting Big Trajectory Data to Analyse Road Network Travel Efficiency
Authors: Rania Alshikhe, Vinita Jindal
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Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE
Procedia PDF Downloads 16024725 Groundwater Geophysical Studies in the Developed and Sub-Urban BBMP Area, Bangalore, Karnataka, South India
Authors: G. Venkatesha, Urs Samarth, H. K. Ramaraju, Arun Kumar Sharma
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The projection for Groundwater states that the total domestic water demand for greater Bangalore would increase from 1,170 MLD in 2010 to 1,336 MLD in 2016. Dependence on groundwater is ever increasing due to rapid Industrialization & Urbanization. It is estimated that almost 40% of the population of Bangalore is dependent on groundwater. Due to the unscientific disposal of domestic and industrial waste generated, groundwater is getting highly polluted in the city. The scale of this impact will depend mainly upon the water-service infrastructure, the superficial geology and the regional setting. The quality of ground water is equally important as that of quantity. Jointed and fractured granites and gneisses constitute the major aquifer system of BBMP area. Two new observatory Borewells were drilled and lithology report has been prepared. Petrographic Analysis (XRD/XRF) and Water quality Analysis were carried out as per the standard methods. Petrographic samples were analysed by collecting chip of rock from the borewell for every 20ft depth, most of the samples were similar and samples were identified as Biotite-Gneiss, Schistose Amphibolite. Water quality analysis was carried out for individual chemical parameters for two borewells drilled. 1st Borewell struck water at 150ft (Total depth-200ft) & 2nd struck at 740ft (Total depth-960ft). 5 water samples were collected till end of depth in each borewell. Chemical parameter values such as, Total Hardness (360-348, 280-320) mg/ltr, Nitrate (12.24-13.5, 45-48) mg/ltr, Chloride (104-90, 70-70)mg/ltr, Fe (0.75-0.09, 1.288-0.312)mg/ltr etc. are calculated respectively. Water samples were analysed from various parts of BBMP covering 750 sq kms, also thematic maps (IDW method) of water quality is generated for these samples for Post-Monsoon season. The study aims to explore the sub-surface Lithological layers and the thickness of weathered zone, which indirectly helps to know the Groundwater pollution source near surface water bodies, dug wells, etc. The above data are interpreted for future ground water resources planning and management.Keywords: lithology, petrographic, pollution, urbanization
Procedia PDF Downloads 29424724 Mitigating Supply Chain Risk for Sustainability Using Big Data Knowledge: Evidence from the Manufacturing Supply Chain
Authors: Mani Venkatesh, Catarina Delgado, Purvishkumar Patel
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The sustainable supply chain is gaining popularity among practitioners because of increased environmental degradation and stakeholder awareness. On the other hand supply chain, risk management is very crucial for the practitioners as it potentially disrupts supply chain operations. Prediction and addressing the risk caused by social issues in the supply chain is paramount importance to the sustainable enterprise. More recently, the usage of Big data analytics for forecasting business trends has been gaining momentum among professionals. The aim of the research is to explore the application of big data, predictive analytics in successfully mitigating supply chain social risk and demonstrate how such mitigation can help in achieving sustainability (environmental, economic & social). The method involves the identification and validation of social issues in the supply chain by an expert panel and survey. Later, we used a case study to illustrate the application of big data in the successful identification and mitigation of social issues in the supply chain. Our result shows that the company can predict various social issues through big data, predictive analytics and mitigate the social risk. We also discuss the implication of this research to the body of knowledge and practice.Keywords: big data, sustainability, supply chain social sustainability, social risk, case study
Procedia PDF Downloads 41324723 E-Learning in Life-Long Learning: Best Practices from the University of the Aegean
Authors: Chryssi Vitsilaki, Apostolos Kostas, Ilias Efthymiou
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This paper presents selected best practices on online learning and teaching derived from a novel and innovating Lifelong Learning program through e-Learning, which has during the last five years been set up at the University of the Aegean in Greece. The university, capitalizing on an award-winning, decade-long experience in e-learning and blended learning in undergraduate and postgraduate studies, recently expanded into continuous education and vocational training programs in various cutting-edge fields. So, in this article we present: (a) the academic structure/infrastructure which has been developed for the administrative, organizational and educational support of the e-Learning process, including training the trainers, (b) the mode of design and implementation based on a sound pedagogical framework of open and distance education, and (c) the key results of the assessment of the e-learning process by the participants, as they are used to feedback on continuous organizational and teaching improvement and quality control.Keywords: distance education, e-learning, life-long programs, synchronous/asynchronous learning
Procedia PDF Downloads 33724722 Improving the Analytical Power of Dynamic DEA Models, by the Consideration of the Shape of the Distribution of Inputs/Outputs Data: A Linear Piecewise Decomposition Approach
Authors: Elias K. Maragos, Petros E. Maravelakis
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In Dynamic Data Envelopment Analysis (DDEA), which is a subfield of Data Envelopment Analysis (DEA), the productivity of Decision Making Units (DMUs) is considered in relation to time. In this case, as it is accepted by the most of the researchers, there are outputs, which are produced by a DMU to be used as inputs in a future time. Those outputs are known as intermediates. The common models, in DDEA, do not take into account the shape of the distribution of those inputs, outputs or intermediates data, assuming that the distribution of the virtual value of them does not deviate from linearity. This weakness causes the limitation of the accuracy of the analytical power of the traditional DDEA models. In this paper, the authors, using the concept of piecewise linear inputs and outputs, propose an extended DDEA model. The proposed model increases the flexibility of the traditional DDEA models and improves the measurement of the dynamic performance of DMUs.Keywords: Dynamic Data Envelopment Analysis, DDEA, piecewise linear inputs, piecewise linear outputs
Procedia PDF Downloads 16424721 Disability in the Course of a Chronic Disease: The Example of People Living with Multiple Sclerosis in Poland
Authors: Milena Trojanowska
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Disability is a phenomenon for which meanings and definitions have evolved over the decades. This became the trigger to start a project to answer the question of what disability constitutes in the course of an incurable chronic disease. The chosen research group are people living with multiple sclerosis.The contextual phase of the research was participant observation at the Polish Multiple Sclerosis Society, the largest NGO in Poland supporting people living with MS and their relatives. The research techniques used in the project are (in order of implementation): group interviews with people living with MS and their relatives, narrative interviews, asynchronous technique, participant observation during events organised for people living with MS and their relatives.The researcher is currently conducting follow-up interviews, as inaccuracies in the respondents' narratives were identified during the data analysis. Interviews and supplementary research techniques were used over the four years of the research, and the researcher also benefited from experience gained from 12 years of working with NGOs (diaries, notes). The research was carried out in Poland with the participation of people living in this country only.The research has been based on grounded theory methodology in a constructivist perspectivedeveloped by Kathy Charmaz. The goal was to follow the idea that research must be reliable, original, and useful. The aim was to construct an interpretive theory that assumes temporality and the processualityof social life. TheAtlas.ti software was used to collect research material and analyse it. It is a program from the CAQDAS(Computer-Assisted Qualitative Data Analysis Software) group.Several key factors influencing the construction of a disability identity by people living with multiple sclerosis was identified:-course of interaction with significant relatives,- the expectation of identification with disability (expressed by close relatives),- economic profitability (pension, allowances),- institutional advantages (e.g. parking card),- independence and autonomy (not equated with physical condition, but access to adapted infrastructure and resources to support daily functioning),- the way a person with MS construes the meaning of disability,- physical and mental state,- medical diagnosis of illness.In addition, it has been shown that making an assumption about the experience of disability in the course of MS is a form of cognitive reductionism leading to further phenomenon such as: the expectation of the person with MS to construct a social identity as a person with a disability (e.g. giving up work), the occurrence of institutional inequalities. It can also be a determinant of the choice of a life strategy that limits social and individual functioning, even if this necessity is not influenced by the person's physical or psychological condition.The results of the research are important for the development of knowledge about the phenomenon of disability. It indicates the contextuality and complexity of the disability phenomenon, which in the light of the research is a set of different phenomenon of heterogeneous nature and multifaceted causality. This knowledge can also be useful for institutions and organisations in the non-governmental sector supporting people with disabilities and people living with multiple sclerosis.Keywords: disability, multiple sclerosis, grounded theory, poland
Procedia PDF Downloads 11324720 A Proposal of Advanced Key Performance Indicators for Assessing Six Performances of Construction Projects
Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim
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Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation
Procedia PDF Downloads 49