Search results for: 2d and 3d data conversion

Authors: Nushrat Khan, Mike Thelwall, Kayvan Kousha

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Making research data openly accessible has been mandated by most funders over the last 5 years as it promotes reproducibility in science and reduces duplication of effort to collect the same data. There are evidence that articles that publicly share research data have higher citation rates in biological and social sciences. However, how and whether shared data is being reused is not always intuitive as such information is not easily accessible from the majority of research data repositories. This study aims to understand the practice of data citation and how data is being reused over the years focusing on biodiversity since research data is frequently reused in this field. Metadata of 38,878 datasets including citation counts were collected through the Global Biodiversity Information Facility (GBIF) API for this purpose. GBIF was used as a data source since it provides citation count for datasets, not a commonly available feature for most repositories. Analysis of dataset types, citation counts, creation and update time of datasets suggests that citation rate varies for different types of datasets, where occurrence datasets that have more granular information have higher citation rates than checklist and metadata-only datasets. Another finding is that biodiversity datasets on GBIF are frequently updated, which is unique to this field. Majority of the datasets from the earliest year of 2007 were updated after 11 years, with no dataset that was not updated since creation. For each year between 2007 and 2017, we compared the correlations between update time and citation rate of four different types of datasets. While recent datasets do not show any correlations, 3 to 4 years old datasets show weak correlation where datasets that were updated more recently received high citations. The results are suggestive that it takes several years to cumulate citations for research datasets. However, this investigation found that when searched on Google Scholar or Scopus databases for the same datasets, the number of citations is often not the same as GBIF. Hence future aim is to further explore the citation count system adopted by GBIF to evaluate its reliability and whether it can be applicable to other fields of studies as well.

Keywords: data citation, data reuse, research data sharing, webometrics

Procedia PDF Downloads 184

Authors: Chandra Gupt Porwal, Preeti C. Porwal

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Transient data reveals much about the machine's condition that steady-state data cannot. New technologies make this information much more available for evaluating the mechanical integrity of a machine train. Recent surveys at various stations indicate that simplicity is preferred over completeness in machine audits throughout the power generation industry. This is most clearly shown by the number of rotating machinery predictive maintenance programs in which only steady-state vibration amplitude is trended while important transient vibration data is not even acquired. Efforts have been made to explain what transient data is, its importance, the types of plots used for its display, and its effective utilization for analysis. In order to demonstrate the value of measuring transient data and its practical application in rotating machinery for resolving complex and persistent issues with turbine generators, the author presents a few case studies that highlight the presence of rotor instabilities due to the shaft moving towards the bearing centre in a 100 MM LMZ unit located in the Northern Capital Region (NCR), heavy misalignment noticed—especially after 2993 rpm—caused by loose coupling bolts, which prevented the machine from being synchronized for more than four months in a 250 MW KWU unit in the Western Region (WR), and heavy preload noticed at Intermediate pressure turbine (IPT) bearing near HP- IP coupling, caused by high points on coupling faces at a 500 MW KWU unit in the Northern region (NR), experienced at Indian power plants.

Keywords: transient data, steady-state-data, intermediate -pressure-turbine, high-points

Procedia PDF Downloads 74

Authors: Avichal Malhotra, Jerome Frisch, Christoph van Treeck

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The utilization of semantic, cadastral and topological data from geographic information systems (GIS) has exponentially increased for building and urban-scale energy performance simulations. Urban planners, simulation scientists, and researchers use virtual 3D city models for energy analysis, algorithms and simulation tools. For dynamic energy simulations at city and district level, this paper provides an overview of the available GIS data models and their levels of detail. Adhering to different norms and standards, these models also intend to describe building and construction industry data. For further investigations, CityGML data models are considered for simulations. Though geographical information modelling has considerably many different implementations, extensions of virtual city data can also be made for domain specific applications. Highlighting the use of the extended CityGML models for energy researches, a brief introduction to the Energy Application Domain Extension (ADE) along with its significance is made. Consequently, addressing specific input simulation data, a workflow using Modelica underlining the usage of GIS information and the quantification of its significance over annual heating energy demand is presented in this paper.

Keywords: CityGML, EnergyADE, energy performance simulation, GIS

Procedia PDF Downloads 175

Authors: Linnea Stenliden

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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors by Latour. The learning conditions are found to be distinguished by broad complexity characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation

Procedia PDF Downloads 380

Authors: A. D. Tayal

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The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.

Keywords: data, innovation, renewable, solar

Procedia PDF Downloads 371

Authors: Hammad Khan, Wookeun Bae

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The objective of this study was to optimize, achieve and control the highly loaded and efficient nitrite production having suitability for autotrophic and heterotrophic denitritation. A lab scale CSTR for partial and full nitritation was operated to treat the livestock manure digester liquor having an ammonium concentration of ~600 mg-NH4+-N/L and biodegradable contents of ~0.35 g-COD/L. The experiments were performed at 30°C, pH: 8.0, DO: 1.5 mg/L and SRT ranging from 7-20 days. After 125 days operation, >95% nitrite buildup having the ammonium loading rate of ~3.2 kg-NH4+-N/m3-day was seen with almost complete ammonium conversion. On increasing the loading rate further (i-e, from 3.2-6.2 kg-NH4+-N/m3-day), stability of the system remained unaffected. On decreasing the pH from 8 to7.5 and further 7.2, removal rate can be easily controlled as 95%, 75%, and even 50%. Results demonstrated that nitritation stability and desired removal rates are controlled by a balance of simultaneous inhibition by FA & FNA, pH affect and DO limitation. These parameters proved to be effective even to produce an appropriate influent for anammox. In addition, a mathematical model, identified through the occurring biological reactions, is proposed to optimize the full and partial nitritation process. The proposed model present relationship between pH, ammonium and produced nitrite for full and partial nitritation under the varying concentrations of DO, and simultaneous inhibition by FA and FNA.

Keywords: stable nitritation, high loading, autrophic denitritation, CSTR

Procedia PDF Downloads 243

Authors: Apurva Saxena, Sunita Gond

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Demand of computation, data storage in large amount are rapidly increases day by day. Cloud computing technology fulfill the demand of today’s computation but this will lead to high power consumption in cloud data centers. Initiative for Green IT try to reduce power consumption and its adverse environmental impacts. Paper also focus on various green computing techniques, proposed models and efficient way to make cloud greener.

Keywords: virtualization, cloud computing, green computing, data center

Procedia PDF Downloads 560

Authors: K. D. R. Jagath-Kumara, D. D. Dias

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The sea waves carry thousands of GWs of power globally. Although there are a number of different approaches to harness offshore energy, they are likely to be expensive, practically challenging and vulnerable to storms. Therefore, this paper considers using the near shore waves for generating mechanical and electrical power. It introduces two new approaches, the wave manipulation and using a variable duct turbine, for intercepting very wide wave fronts and coping with the fluctuations of the wave height and the sea level, respectively. The first approach effectively allows capturing much more energy yet with a much narrower turbine rotor. The second approach allows using a rotor with a smaller radius but captures energy of higher wave fronts at higher sea levels yet preventing it from totally submerging. To illustrate the effectiveness of the approach, the paper contains a description and the simulation results of a scale model of a wave manipulator. Then, it includes the results of testing a physical model of the manipulator and a single duct, axial flow turbine, in a wave flume in the laboratory. The paper also includes comparisons of theoretical predictions, simulation results and wave flume tests with respect to the incident energy, loss in wave manipulation, minimal loss, brake torque and the angular velocity.

Keywords: near-shore sea waves, renewable energy, wave energy conversion, wave manipulation

Procedia PDF Downloads 484

Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina, Evgenii N. Kojaev

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In review the generalized data about biological activity of anthraquinone-containing plants and specimens on their basis is presented. Data of traditional medicine, results of bioscreening and clinical researches of specimens are analyzed.

Keywords: anthraquinones, physiologically active substances, phytopreparation, Ramon

Procedia PDF Downloads 379

Authors: Brian J. Graham, Ronald T. Raines

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The presence of a nearly vacant p orbital on boron endows boronic acids with unique abilities as a catalyst and ligand. An organocatalytic process has been developed for the conversion of biomass-derived sugars to 5-hydroxymethylfurfural, which is a platform chemical. Specifically, 2-carboxyphenylboronic acid (2-CPBA) has been shown to be an optimal catalyst for this process, promoting the desired transformation in the absence of metals. The attributes of 2-CPBA as a catalyst led to additional investigations of its structure and reactivity. 2-CPBA was found to exist as a cyclized benzoxaborolone adduct rather than a free carboxylic acid. This cyclization has profound consequences for the oxidative stability of the boronic acid. Stereoelectronic effects within the oxaborolone ring destabilize the oxidation transition state by reducing electron donation from the cyclic oxygen to the developing p orbital on boron. That leads to a 10,000-fold increase in oxidative stability while maintaining the normal reactivity of boronic acids toward diols (e.g., carbohydrates) and nucleophiles in proteins while also presenting numerous hydrogen-bond accepting and donating groups. Thus, benzoxaborolones are useful in catalysis, chemical biology, medicinal chemistry, and allied fields.

Keywords: bioisosteres, boronic acid, catalysis, oxidative stability, pharmacophore, stereoelectronic effects

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Authors: Veli Durmus, Mert Uydaci

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Every patient who needs to get a medical treatment should share health-related personal data with healthcare providers. Therefore, personal health data plays an important role to make health decisions and identify health threats during every encounter between a patient and caregivers. In other words, health data can be defined as privacy and sensitive information which is protected by various health laws and regulations. In many cases, the data are an outcome of the confidential relationship between patients and their healthcare providers. Globally, almost all nations have own laws, regulations or rules in order to protect personal data. There is a variety of instruments that allow authorities to use the health data or to set the barriers data sharing across international borders. For instance, Directive 95/46/EC of the European Union (EU) (also known as EU Data Protection Directive) establishes harmonized rules in European borders. In addition, the General Data Protection Regulation (GDPR) will set further common principles in 2018. Because of close policy relationship with EU, this study provides not only information on regulations, directives but also how they play a role during the legislative process in Turkey. Even if the decision is controversial, the Board has recently stated that private or public healthcare institutions are responsible for the patient call system, for doctors to call people waiting outside a consultation room, to prevent unlawful processing of personal data and unlawful access to personal data during the treatment. In Turkey, vast majority private and public health organizations provide a service that ensures personal data (i.e. patient’s name and ID number) to call the patient. According to the Board’s decision, hospital or other healthcare institutions are obliged to take all necessary administrative precautions and provide technical support to protect patient privacy. However, this application does not effectively and efficiently performing in most health services. For this reason, it is important to draw a legal framework of personal health data by stating what is the main purpose of this regulation and how to deal with complicated issues on personal health data in Turkey. The research is descriptive on data protection law for health care setting in Turkey. Primary as well as secondary data has been used for the study. The primary data includes the information collected under current national and international regulations or law. Secondary data include publications, books, journals, empirical legal studies. Consequently, privacy and data protection regimes in health law show there are some obligations, principles and procedures which shall be binding upon natural or legal persons who process health-related personal data. A comparative approach presents there are significant differences in some EU member states due to different legal competencies, policies, and cultural factors. This selected study provides theoretical and practitioner implications by highlighting the need to illustrate the relationship between privacy and confidentiality in Personal Data Protection in Health Law. Furthermore, this paper would help to define the legal framework for the health law case studies on data protection and privacy.

Keywords: data protection, personal data, privacy, healthcare, health law

Procedia PDF Downloads 228

Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

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As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

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Authors: Ajish Sreedharan

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With the fast evolution of digital data exchange, security information becomes much important in data storage and transmission. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. As encryption process is applied to the whole image in AES ,it is difficult to improve the efficiency. In this paper, wavelet decomposition is used to concentrate the main information of image to the low frequency part. Then, AES encryption is applied to the low frequency part. The high frequency parts are XORed with the encrypted low frequency part and a wavelet reconstruction is applied. Theoretical analysis and experimental results show that the proposed algorithm has high efficiency, and satisfied security suits for image data transmission.

Keywords: discrete wavelet transforms, AES, dynamic SBox

Procedia PDF Downloads 434

Authors: Taras Agryzkov, Almudena Nolasco-Cirugeda, Jose L. Oliver, Leticia Serrano-Estrada, Leandro Tortosa, Jose F. Vicent

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This paper aims to represent the commercial activity of a city taking as source data the social network Foursquare. The city of Murcia is selected as case study, and the location-based social network Foursquare is the main source of information. After carrying out a reorganisation of the user-generated data extracted from Foursquare, it is possible to graphically display on a map the various city spaces and venues –especially those related to commercial, food and entertainment sector businesses. The obtained visualisation provides information about activity patterns in the city of Murcia according to the people`s interests and preferences and, moreover, interesting facts about certain characteristics of the town itself.

Keywords: social networks, spatial analysis, data visualization, geocomputation, Foursquare

Procedia PDF Downloads 431

Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

Procedia PDF Downloads 300

Authors: T. Thulare, M. Herselman, A. Botha

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Poor system use, including inappropriate design of health information systems, causes difficulties in communication with patients and increased time spent by healthcare professionals in recording the necessary health information for medical records. System features like pop-up reminders, complex menus, and poor user interfaces can make medical records far more time consuming than paper cards as well as affect decision-making processes. Although errors associated with health information and their real and likely effect on the quality of care and patient safety have been documented for many years, more research is needed to measure the occurrence of these errors and determine the causes to implement solutions. Therefore, the purpose of this paper is to identify data integrity challenges in hospital information systems through a scoping review and based on the results provide recommendations on how to manage these. Only 34 papers were found to be most suitable out of 297 publications initially identified in the field. The results indicated that human and computerized systems are the most common challenges associated with data integrity and factors such as policy, environment, health workforce, and lack of awareness attribute to these challenges but if measures are taken the data integrity challenges can be managed.

Keywords: data integrity, data integrity challenges, hospital information systems, South Africa

Procedia PDF Downloads 190

Authors: Shoujia Fang, Guoqing Ding, Xin Chen

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The quality of press-fit assembly is closely related to reliability and safety of product. The paper proposed a keypoint detection method based on convolutional neural network to improve the accuracy of keypoint detection in press-fit curve. It would provide an auxiliary basis for judging quality of press-fit assembly. The press-fit curve is a curve of press-fit force and displacement. Both force data and distance data are time-series data. Therefore, one-dimensional convolutional neural network is used to process the press-fit curve. After the obtained press-fit data is filtered, the multi-layer one-dimensional convolutional neural network is used to perform the automatic learning of press-fit curve features, and then sent to the multi-layer perceptron to finally output keypoint of the curve. We used the data of press-fit assembly equipment in the actual production process to train CNN model, and we used different data from the same equipment to evaluate the performance of detection. Compared with the existing research result, the performance of detection was significantly improved. This method can provide a reliable basis for the judgment of press-fit quality.

Keywords: keypoint detection, curve feature, convolutional neural network, press-fit assembly

Procedia PDF Downloads 236

Authors: Nouf Alourfi

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This study examines the metabolism of amitriptyline (AMI) and verapamil (VER) using a KNIME-based method. KNIME improved workflow is an open-source data-analytics platform that integrates a number of open-source metabolomics tools such as CFMID and MetFrag to provide standard data visualisations, predict candidate metabolites, assess them against experimental data, and produce reports on identified metabolites. The use of this workflow is demonstrated by employing three types of liver microsomes (human, rat, and Guinea pig) to study the in vitro metabolism of the two drugs (AMI and VER). This workflow is used to create and treat UPLC-MS (Orbitrap) data. The formulas and structures of these drugs' metabolites can be assigned automatically. The key metabolic routes for amitriptyline are hydroxylation, N-dealkylation, N-oxidation, and conjugation, while N-demethylation, O-demethylation and N-dealkylation, and conjugation are the primary metabolic routes for verapamil. The identified metabolites are compatible to the published, clarifying the solidity of the workflow technique and the usage of computational tools like KNIME in supporting the integration and interoperability of emerging novel software packages in the metabolomics area.

Keywords: KNIME, CFMID, MetFrag, Data Analysis, Metabolomics

Procedia PDF Downloads 126

Authors: H. M. Takematsu, B. R. De Camargo, E. F. Noronha

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The use of hydrolyzing enzymes for degradation of lignocellulosic biomass is of great concern for the production of second generation ethanol. Although many hollocelulases have already been described in the literature, much more has to be discovered. Therefore, the aim of this study to evaluate hollocelulase production of P. polonicum grown in liquid media containing sugarcane bagasse as the carbon source. From a collection of twenty fungi isolated from Cerrado biome soil, P. polonicum was molecular identified by sequencing of ITS4, βtubulin and Calmodulin genes, and has been chosen to be further investigated regarding its potential production of hydrolyzing enzymes. Spore suspension (1x10-6 ml-1) solution was inoculated in sterilized minimal liquid medium containing 0,5%(w/v) of non-pretreated sugarcane bagasse as the carbon source, and incubated in shaker incubator at 28°C and 120 rpm. The supernatant obtained, was subjected to enzymatic assays to analyze xylanase, mannanase, pectinase and endoglucanase activities. Xylanase activity showed better results (67,36 UI/mg). Xylanases bands were indicated by zymogram and SDS-PAGE, and one of them was partially purified and characterized. It showed maximum activity at 50 °C, was thermostable for 72h at 40°C, and pH5.0 was the optimum observed. This study presents P. polonicum as an interesting source of hollocelulases, especially xylanase, for lignocellulose bio-conversion processes with commercial use.

Keywords: sugarcane bagasse, Cerrado biome , hollocelulase, lignocellulosic biomass

Procedia PDF Downloads 294

Authors: Amara Rafik, Bougherara Maamar, Belhadj Aissa Mostefa

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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, air traffic simulation

Procedia PDF Downloads 91

Authors: Mahfoud Djebbar

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

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

Procedia PDF Downloads 344

Authors: Zohra Mekranfar, Ahmed Saidi, Abdellah Mebrek

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This work aims to develop multi-criteria decision making (MCDM) and spatial data warehouse (SDW) methods, which will be integrated into a GIS according to a ‘GIS dominant’ approach. The GIS operating tools will be operational to operate the SDW. The MCDM methods can provide many solutions to a set of problems with various and multiple criteria. When the problem is so complex, integrating spatial dimension, it makes sense to combine the MCDM process with other approaches like data mining, ascending analyses, we present in this paper an experiment showing a geo-decisional methodology of SWD construction, On-line analytical processing (OLAP) technology which combines both basic multidimensional analysis and the concepts of data mining provides powerful tools to highlight inductions and information not obvious by traditional tools. However, these OLAP tools become more complex in the presence of the spatial dimension. The integration of OLAP with a GIS is the future geographic and spatial information solution. GIS offers advanced functions for the acquisition, storage, analysis, and display of geographic information. However, their effectiveness for complex spatial analysis is questionable due to their determinism and their decisional rigor. A prerequisite for the implementation of any analysis or exploration of spatial data requires the construction and structuring of a spatial data warehouse (SDW). This SDW must be easily usable by the GIS and by the tools offered by an OLAP system.

Keywords: data warehouse, GIS, MCDM, SOLAP

Procedia PDF Downloads 182

Authors: Christian Kapuku, Seung-Young Kho

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An accurate representation of the transportation system serving the region is one of the important aspects of transportation modeling. Such representation often requires developing an abstract model of the system elements, which also requires important amount of data, surveys and time. However, in some cases such as in developing countries, data deficiencies, time and budget constraints do not always allow such accurate representation, leaving opportunities to assumptions that may negatively affect the quality of the analysis. With the emergence of Internet open source data especially in the mapping technologies as well as the advances in Geography Information System, opportunities to tackle these issues have raised. Therefore, the objective of this paper is to demonstrate such application through a practical case of the development of the transportation network for the city of Kinshasa. The GIS geo-referencing was used to construct the digitized map of Transportation Analysis Zones using available scanned images. Centroids were then dynamically placed at the center of activities using an activities density map. Next, the road network with its characteristics was built using OpenStreet data and other official road inventory data by intersecting their layers and cleaning up unnecessary links such as residential streets. The accuracy of the final network was then checked, comparing it with satellite images from Google and Bing. For the validation, the final network was exported into Emme3 to check for potential network coding issues. Results show a high accuracy between the built network and satellite images, which can mostly be attributed to the use of open source data.

Keywords: geographic information system (GIS), network construction, transportation database, open source data

Procedia PDF Downloads 171

Authors: Widya Anggraini Pamungkas, Rosana Budi Setyawati, Awaludin Fitroh Rifai, Candra Pangesti Setiawan, Anatta Wahyu Budiiman, Inayati, Joko Waluyo, Sunu Herwi Pranolo

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The increase in LPG consumption in Indonesia is not balanced with the amount of supply. The high demand for LPG due to the success of the government's kerosene-to-LPG conversion program and the Covid-19 pandemic in 2020 led to an increase in LPG consumption in the household sector and caused Indonesia's trade balance to experience a deficit. The high consumption of LPG encourages the need for alternative fuels as a substitute or which aims to substitute LPG; one of the materials that can be used is Dimethyl Ether (DME). Dimethyl ether (DME) is an organic compound with the chemical formula CH 3. OCH 3 has a high cetane number and has characteristics similar to LPG. DME can be produced from various sources, such as coal, biomass and natural gas. Based on the economic analysis conducted at 10% IRR, coal has the largest NPV of Rp. 20,034,837,497,241 with a payback period of 3.86 years, then biomass with an NPV of Rp. 10,401,526,072,850 and a payback period of 5.16. the latter is natural gas with an NPV of IDR 7,401,272,559,191 and a payback period of 6.17 years. Of the three sources of raw materials used, if the sensitivity is calculated using the selling price of DME equal to the selling price of LPG, it will get an NPV value that is greater than the NPV value when using the current DME price. The advantages of coal as a raw material for DME are not only because it is profitable, namely: low price and abundant resources, but has high greenhouse gas emissions.

Keywords: LPG, DME, coal, biomass, natural gas

Procedia PDF Downloads 128

Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore

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In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.

Keywords: CDSS, EHR, business intelliegence, tools

Procedia PDF Downloads 143

Authors: Sen Tanmoy, Jain Sarika, Panda Jagabandhu

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The studies regarding the impact of urbanization using the WRF-ARW model rely heavily on the static geographical information selected, including domain configuration and land use land cover (LULC) data. Accurate representation of LULC data provides essential information for understanding urban growth and simulating meteorological parameters such as temperature, precipitation etc. Researchers are using different LULC data as per availability and their requirements. As far as India is concerned, we have very limited resources and data availability. So, it is important to understand how we can optimize our results using limited LULC data. In this review article, we explored how a LULC map is generated from different sources in the Indian context and what its significance is in WRF-ARW modeling to study urbanization/Climate change or any other meteorological parameters. Bibliometric analyses were also performed in this review article based on countries of study and indexed keywords. Finally, some key points are marked out for selecting the most suitable LULC map for any urbanization-related study.

Keywords: LULC, LULC mapping, LANDSAT, WRF-ARW, ISRO, bibliometric Analysis.

Procedia PDF Downloads 34

Authors: T. S. Olugbemi, T. S. Friday, O. O. Olusola

Abstract:

This experiment was carried out to assess the effect of different stocking densities and vitamin C supplementation on the performance of Japanese quails. Five hundred and twenty (520) unsexed quail birds of two (2) weeks of age were allotted randomly into nine (9) groups with 3 replicates each in a 3x3 factorial arrangement (3 stocking density levels and 3 graded vitamin C levels) with densities of 150, 120, 90 cm2/bird(11, 16, 21 birds). During the five weeks growing trial (2- 6 weeks), results showed that stocking density had significant effects on final weight (131.59g compared to 111.10g for the lowest), total and daily weight gain. No significance difference was observed for feed conversion ratio, age at first lay and first egg weight. Observations on haematological parameters (packed cell volume (PCV), total protein (TP), haemoglobin, red blood cell (RBC), lymphocyte, heterophil) on stocking density showed no significant differences. Vitamin C supplementation at 50mg/kg and 100mg/kg did not have any significant effect on the growth performance parameters of growing quails. Stocking density at 150cm2/bird had a better performance with or without vitamin C supplementation hence it is recommended that stocking rates of quails between the ages of 2 – 6 weeks should not be below 150cm2/bird.

Keywords: anti-oxidants, performance, stress, stocking density

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Authors: Mikel Niño, Roberto V. Zicari, Todor Ivanov, Kim Hee, Naveed Mushtaq, Marten Rosselli, Concha Sánchez-Ocaña, Karsten Tolle, José Miguel Blanco, Arantza Illarramendi, Jörg Besier, Harry Underwood

Abstract:

One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.

Keywords: data-driven projects, humanitarian operations, personal and sensitive data, social good, stakeholders analysis

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Authors: B. Y. Danjuma, A. Archibong-Eso, Aliyu M. Aliyu, H. Yeung

Abstract:

In this experimental investigation, a new data for slugging frequency for high viscosity oil-gas flow are reported. Scale experiments were carried out using a mixture of air and mineral oil as the liquid phase in a 17 m long horizontal pipe with 0.0762 ID. The data set was acquired using two high-speed Gamma Densitometers at a data acquisition frequency of 250 Hz over a time interval of 30 seconds. For the range of flow conditions investigated, increase in liquid oil viscosity was observed to strongly influence the slug frequency. A comparison of the present data with prediction models available in the literature revealed huge discrepancies. A new correlation incorporating the effect of viscosity on slug frequency has been proposed for the horizontal flow, which represents the main contribution of this work.

Keywords: gamma densitometer, flow pattern, pressure gradient, slug frequency

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Authors: Tolga Hayit, Ucman Ergun, Ugur Fidan

Abstract:

Being healthy is undoubtedly an indispensable necessity for human life. With technological improvements, in the literature, various health monitoring and imaging systems have been developed to satisfy your health needs. In this context, the work of monitoring and recording the data of individual health monitoring data via wireless technology is also being part of these studies. Nowadays, mobile devices which are located in almost every house and which become indispensable of our life and have wireless technology infrastructure have an important place of making follow-up health everywhere and every time because these devices were using in the health monitoring systems. In this study, Arduino an open-source microcontroller card was used in which a sample sugar measuring device was connected in series. In this way, the glucose data (glucose ratio, time) obtained with the glucometer is transferred to the mobile device based on the Android operating system with the Bluetooth technology channel. A mobile application was developed using the Apache Cordova framework for listing data, presenting graphically and reading data over Arduino. Apache Cordova, HTML, Javascript and CSS are used in coding section. The data received from the glucometer is stored in the local database of the mobile device. It is intended that people can transfer their measurements to their mobile device by using wireless technology and access the graphical representations of their data. In this context, the aim of the study is to be able to perform health monitoring by using different wireless technologies in mobile devices that can respond to different wireless technologies at present. Thus, that will contribute the other works done in this area.

Keywords: Arduino, Bluetooth, glucose measurement, mobile health monitoring

Procedia PDF Downloads 326