Search results for: operational data

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 124

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 159

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 508

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 125

Authors: Veselin Konstantinov Hristov

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In recent years, the lease contract has become more and more applicable and occupies a key place in commercial relations and business. In Bulgaria, the legal regulation of the leasing contract is relatively new and imperfectly developed. There are many legal loopholes and it is they that determine the need for a comparative legal analysis. The purpose of the study is to analyze the various European legislations regarding the leasing contract and to find effective solutions for the legal system of Bulgaria. First of all, are examined the concept of the leasing contract, which originated in the United States of America around the 1950s and spread in Europe, and the etymology of the term "leasing". After that, the main types of lease contracts – financial and operational – are examined and analyzed in detail. Their features and characteristics were studied, as well as a comparative analysis was made between them. Next, in the research, a comparative-legal analysis of the leasing contract in different European countries was made in terms of its development and distribution, as well as its legal characteristics. The mechanism of action and functioning of the leasing contract in several European countries is analyzed. Conclusions are made regarding the legal framework under which the lease contract is most effective. Types of leasing contracts specific only to certain European countries and their advantages are examined. In conclusion, recommendations are made to improve the legal framework of the leasing contract in Bulgaria.

Keywords: alternative financing, leasing contract, financing instruments, innovation

Procedia PDF Downloads 80

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 116

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 106

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 115

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

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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 485

Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

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This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: transportation networks, freight delivery, data flow, monitoring, e-services

Procedia PDF Downloads 125

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 256

Authors: Lenka Krsnakova, Petr Jirsak

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Prior research on facility location in supply chain is mostly focused on improvement of mathematical models. It is due to the fact that supply chain design has been for the long time the area of operational research that underscores mainly quantitative criteria. Qualitative criteria are still highly neglected within the supply chain design research. Facility location in the supply chain has become multi-criteria decision-making problem rather than single criteria decision due to changes of market conditions. Thus, both qualitative and quantitative criteria have to be included in the decision making process. The aim of this study is to emphasize the importance of qualitative criteria as key parameters of relevant mathematical models. We examine which criteria are taken into consideration when Czech companies decide about their facility location. A literature review on criteria being used in facility location decision making process creates a theoretical background for the study. The data collection was conducted through questionnaire survey. Questionnaire was sent to manufacturing and business companies of all sizes (small, medium and large enterprises) with the representation in the Czech Republic within following sectors: automotive, toys, clothing industry, electronics and pharmaceutical industry. Comparison of which criteria prevail in the current research and which are considered important by companies in the Czech Republic is made. Despite the number of articles focused on supply chain design, only minority of them consider qualitative criteria and rarely process supply chain design as a multi-criteria decision making problem. Preliminary results of the questionnaire survey outlines that companies in the Czech Republic see the qualitative criteria and their impact on facility location decision as crucial. Qualitative criteria as company strategy, quality of working environment or future development expectations are confirmed to be considered by Czech companies. This study confirms that the qualitative criteria can significantly influence whether a particular location could or could not be right place for a logistic facility. The research has two major limitations: researchers who focus on improving of mathematical models mostly do not mention criteria that enter the model. Czech supply chain managers selected important criteria from the group of 18 available criteria and assign them importance weights. It does not necessarily mean that these criteria were taken into consideration when the last facility location was chosen, but how they perceive that today. Since the study confirmed the necessity of future research on how qualitative criteria influence decision making process about facility location, the authors have already started in-depth interviews with participating companies to reveal how the inclusion of qualitative criteria into decision making process about facility location influence the company´s performance.

Keywords: criteria influencing facility location, Czech Republic, facility location decision-making, qualitative criteria

Procedia PDF Downloads 321

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 163

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 332

Authors: Shekar Babu, Amalendu Jyothishi

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The New Companies Bill-2013 in India has mandated all the companies with a certain profit to spend on Corporate Social Responsibility (CSR). Despite the Corporate Governance (CG) compliances at the strategic level the firms have to engage in social good. For both the Central Public Sector Enterprises (CPSE) and the private companies in India the need for strategic CSR focus through operational efficiency measures are mandated. In this paper the focus is to find out if the Indian companies understand their responsibility towards the society despite government making CSR mandatory. Analyzing both the CPSEs and Private companies the researchers find out which set of companies behave responsibly towards the society. Does any particular industry group(s) impact the society by disclosing their CSR spending activities. The key financial and non-financial parameters that influence CSR spending were identified and through econometric analysis methodologies (logistic regression and OLS models) the results were analyzed. The innovative methods were developed to identify if the firms operate efficiently and at the same time complying with the new CSR laws. An innovative matrix was developed to explain how companies could operate efficiently and be compliant in parallel how some of the companies can strategically realign their spending by operating efficiently.

Keywords: corporate social responsibility(CSR), corporate governance(CG), India, logit function, ordinary least squares (OLS)

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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 376

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 428

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 285

Authors: M. Irannezhad, E. H. N. Gashti, U. Moback, B. Kløve

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Climate change because of increases in concentration level of greenhouse gases emissions to the atmosphere will result in mean sea level rise about +1 m by 2100. To prevent coastal floods resulted from the sea level rising, different flood control structures have been built, e.g. the Thames barrier on the Thames River in London (UK), with acceptable protection levels at least so far. Gothenburg located on the southwest coast of Sweden, with the River Göta älv running through it, is one of vulnerable cities to the accelerated rises in mean sea level. Developing a water level model by MATLAB, we evaluated using a sea barrage in the Göta älv River as the flood control structure for protecting the Gothenburg city during this century. Considering three operational scenarios for two barriers in upstream and downstream, the highest sea level was estimated to + 2.95 m above the current mean sea level by 2100. To verify flood protection against such high sea levels, both barriers have to be closed. To prevent high water level in the River Göta älv reservoir, the barriers would be open when the sea level is low. The suggested flood control structures would successfully protect the city from flooding events during this century.

Keywords: climate change, flood control structures, gothenburg, sea level rising, water level mode

Procedia PDF Downloads 354

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 156

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 407

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

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Authors: Joeri N. Aulman

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In the remote Indian region of Gulbarga a case study of lean airport infrastructure development is getting ‘cast in stone’; In April the first turbo-props will land, and the optimized terminal building will process its first passengers, using minimal square meters in a facility that is based on a complete dress-down of the core operational processes. Yet the solution that resulted from this case study has such elegance in its simplicity that it has emboldened the local administration to invest in its construction and thus secure this remote region’s connectivity to India’s growth story. This paper aims to provide further background to the Gulbarga case study and its relevance to remote region connectivity, covering the demand that was identified, its practical application and its regulatory context and relevance for today’s airport manager and local administrators. This embodies the scope of the paper. In summary, the paper will give airport managers and regional authorities an overview and background to innovative case studies of lean airport infrastructure developments which combine both optimized CAPEX and running costs/OPEX without losing sight of the aspirational nature of up and coming remote regions; a truly sustainable model.

Keywords: airport, CAPEX, lean, sustainable, air connectivity, remote regions

Procedia PDF Downloads 309

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

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Authors: Wang Liguang, Zhang Xueqing

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The build-operate-transfer (BOT) project delivery system has provided effective routes to mobilize private sector funds, innovative technologies, management skills and operational efficiencies for public infrastructure development and have been widely used in China during the last 20 years. Many BOT projects in China will be smoothly transferred to the government soon and the transfer stage, which is considered as the last stage, must be studied carefully and handled well to achieve the overall success of BOT projects. There will be many issues faced by both the public sector and private sector in the transfer stage of BOT projects, including project post-assessment, technology and documents transfer, personal training and staff transition, etc. and sometimes additional legislation is needed for future operation and management of facilities. However, most previous studies focused on the bidding, financing, and building and operation stages instead of transfer stage. This research identifies nine key issues in the transfer stage of BOT projects through a comprehensive study on three cases in China, and the expert interview and expert discussion meetings are held to validate the key issues and give detail analysis. A proposed framework of transfer management is prepared based on the experiences derived and lessons drawn from the case studies and expert interview and discussions, which is expected to improve the transfer management of BOT projects in practice.

Keywords: BOT project, key issues, transfer management, transfer stage

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Authors: Valentin P. Velikov

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Automatic program generation saves time, human resources, and allows receiving syntactically clear and logically correct modules. The 4-th generation programming languages are related to drawing the data and the processes of the subject area, as well as, to obtain a frame of the respective information system. The application can be separated in interface and business logic. That means, for an interactive generation of the needed system to be used an already existing toolkit or to be created a new one.

Keywords: computer science, graphical user interface, user dialog interface, dialog frames, data modeling, subject area modeling

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Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

Procedia PDF Downloads 283

Authors: Teo Hao Jing, Shane Ho Ken Wae, Lee Jin Yu, Burra Venkata Durga Kumar

Abstract:

Current distributed healthcare systems face the challenge of interoperability of health data. Storing electronic health records (EHR) in local databases causes them to be fragmented. This problem is aggravated as patients visit multiple healthcare providers in their lifetime. Existing solutions are unable to solve this issue and have caused burdens to healthcare specialists and patients alike. Blockchain technology was found to be able to increase the interoperability of health data by implementing digital access rules, enabling uniformed patient identity, and providing data aggregation. Consortium blockchain was found to have high read throughputs, is more trustworthy, more secure against external disruptions and accommodates transactions without fees. Therefore, this paper proposes a blockchain-based model for data management applications. In this model, a consortium blockchain is implemented by using a delegated proof of stake (DPoS) as its consensus mechanism. This blockchain allows collaboration between users from different organizations such as hospitals and medical bureaus. Patients serve as the owner of their information, where users from other parties require authorization from the patient to view their information. Hospitals upload the hash value of patients’ generated data to the blockchain, whereas the encrypted information is stored in a distributed cloud storage.

Keywords: blockchain technology, data management applications, healthcare, interoperability, delegated proof of stake

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Authors: Stanley Fore

Abstract:

The case study company is one of the leading newsprint companies in South Africa. The company has achieved this status through operational expansion, diversification and investing in cutting-edge technology. They have a reputation for the highest quality and personalised service that transcends borders and industries. The company offers a wide variety of small and large scales printing services. The company is faced with the challenge of significant waste production during normal operations. The company generates 1200 kg of plastic waste and 60 – 70 tonnes of paper waste per month. The company operates a waste management process currently, whereby waste paper is sold, at low cost, to recycling firms for further processing. Having considered the quantity of waste being generated, the company has embarked on a venture to find a more profitable solution to its current waste production. As waste management and recycling is not the company’s core business, the aim of the venture is to implement a secondary profitable waste process business. The venture will be expedited as a strategic project. This research aims to estimate the financial feasibility of a selected solution as well as the impact of non-financial considerations thereof. The financial feasibility is analysed using metrics such as Payback period; internal rate of return and net present value.

Keywords: waste, printing industry, up-cycling, management

Procedia PDF Downloads 261