Search results for: wind tunnel data
24434 Optimization of Maintenance of PV Module Arrays Based on Asset Management Strategies: Case of Study
Authors: L. Alejandro Cárdenas, Fernando Herrera, David Nova, Juan Ballesteros
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This paper presents a methodology to optimize the maintenance of grid-connected photovoltaic systems, considering the cleaning and module replacement periods based on an asset management strategy. The methodology is based on the analysis of the energy production of the PV plant, the energy feed-in tariff, and the cost of cleaning and replacement of the PV modules, with the overall revenue received being the optimization variable. The methodology is evaluated as a case study of a 5.6 kWp solar PV plant located on the Bogotá campus of the Universidad Nacional de Colombia. The asset management strategy implemented consists of assessing the PV modules through visual inspection, energy performance analysis, pollution, and degradation. Within the visual inspection of the plant, the general condition of the modules and the structure is assessed, identifying dust deposition, visible fractures, and water accumulation on the bottom. The energy performance analysis is performed with the energy production reported by the monitoring systems and compared with the values estimated in the simulation. The pollution analysis is performed using the soiling rate due to dust accumulation, which can be modelled by a black box with an exponential function dependent on historical pollution values. The pollution rate is calculated with data collected from the energy generated during two years in a photovoltaic plant on the campus of the National University of Colombia. Additionally, the alternative of assessing the temperature degradation of the PV modules is evaluated by estimating the cell temperature with parameters such as ambient temperature and wind speed. The medium-term energy decrease of the PV modules is assessed with the asset management strategy by calculating the health index to determine the replacement period of the modules due to degradation. This study proposes a tool for decision making related to the maintenance of photovoltaic systems. The above, projecting the increase in the installation of solar photovoltaic systems in power systems associated with the commitments made in the Paris Agreement for the reduction of CO2 emissions. In the Colombian context, it is estimated that by 2030, 12% of the installed power capacity will be solar PV.Keywords: asset management, PV module, optimization, maintenance
Procedia PDF Downloads 5324433 Data Security: An Enhancement of E-mail Security Algorithm to Secure Data Across State Owned Agencies
Authors: Lindelwa Mngomezulu, Tonderai Muchenje
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Over the decades, E-mails provide easy, fast and timely communication enabling businesses and state owned agencies to communicate with their stakeholders and with their own employees in real-time. Moreover, since the launch of Microsoft office 365 and many other clouds based E-mail services, many businesses have been migrating from the on premises E-mail services to the cloud and more precisely since the beginning of the Covid-19 pandemic, there has been a significant increase of E-mails utilization, which then leads to the increase of cyber-attacks. In that regard, E-mail security has become very important in the E-mail transportation to ensure that the E-mail gets to the recipient without the data integrity being compromised. The classification of the features to enhance E-mail security for further from the enhanced cyber-attacks as we are aware that since the technology is advancing so at the cyber-attacks. Therefore, in order to maximize the data integrity we need to also maximize security of the E-mails such as enhanced E-mail authentication. The successful enhancement of E-mail security in the future may lessen the frequency of information thefts via E-mails, resulting in the data of South African State-owned agencies not being compromised.Keywords: e-mail security, cyber-attacks, data integrity, authentication
Procedia PDF Downloads 13624432 Semi-Supervised Outlier Detection Using a Generative and Adversary Framework
Authors: Jindong Gu, Matthias Schubert, Volker Tresp
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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning
Procedia PDF Downloads 15124431 Testing the Change in Correlation Structure across Markets: High-Dimensional Data
Authors: Malay Bhattacharyya, Saparya Suresh
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The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition
Procedia PDF Downloads 12524430 Survey the Effects of Climate in Traditional and Modern Architecture of Iran
Authors: Yousefali Ziari, Hamidreza Joudaki
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Humans have regularly been interacting with their environment, and have a close relation with their environment. House as a shelter which protects us against hot and cold weather and the other climatic occurrences in the environment has a close relation with climate. Before human could have access to the fossil fuels, preparing the comfort for the house was done by adjusting the building according to the climate conditions, and the help of natural resources. However after the man could access the fossil fuel, this way was forgotten, and caused much use of energy for heating & cooling. This research is trying to find some methods for designing suitable building that create comfort fitting with the zone by studying the climate condition of Arak city and as a result to find a way to reduce the use of energy and improving the design. So for the aim of this research we have used the statistics and information such as temperature, rain, wind and the approximate moisture from a period of 40 years from synoptic station of Arak. After specifying the climate of Arak by the use of effective temperature, Ulgi, Guni, Mahani and Ovenz indicator, we investigated the climate comfort conditions and the harmonious architecture with the climate and then some suggestion was given according to the climate situation of each month of the year and quality of human comfort according to this indicators.Keywords: climate, architecture, traditional and modern architecture, comfort indicator, Arak city
Procedia PDF Downloads 47924429 Development of a Nanocompound Based Fibre to Combat Insects
Authors: Merle Bischoff, Thomas Gries, Gunnar Seide
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Pesticides, which harm crop enemies, but can also interfere with the human body, are nowadays mostly used for crop spraying. Silica particles (SiO2) in the nanometer and micrometer scale offer a physical way to combat insects without harming humans and other mammals. Thereby, they allow foregoing pesticides, which can harm the environment. As silica particles are supplied as a powder or in a suspension to farmers, the silica use in large scale agriculture is not sufficient due to erosion through wind and rain. When silica is implemented in a textile’s surface (nanocompound), particles are locally bound and do resist erosion, but can function against bugs. By choosing polypropylene as a matrix polymer, the production of an inexpensive agritextile with an 'anti-bug' effect is made possible. In the Symposium the results of the manufacturing and filament spinning of silica nanocomposites from a polypropylene basis is compared to the fabrication from nanocomposites based on Polybutylene succinate, a biodegradable composite. The investigation focuses on the difference between degradable nanocomposite and stable nanocomposite. Focus will be laid on the filament characteristics as well as the degradation of the nanocompound to underline their potential use and application as an agricultural textile.Keywords: agriculture, environment, insects, protection, silica, textile, nanocomposite
Procedia PDF Downloads 24924428 Development and Evaluation of a Portable Ammonia Gas Detector
Authors: Jaheon Gu, Wooyong Chung, Mijung Koo, Seonbok Lee, Gyoutae Park, Sangguk Ahn, Hiesik Kim, Jungil Park
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In this paper, we present a portable ammonia gas detector for performing the gas safety management efficiently. The display of the detector is separated from its body. The display module is received the data measured from the detector using ZigBee. The detector has a rechargeable li-ion battery which can be use for 11~12 hours, and a Bluetooth module for sending the data to the PC or the smart devices. The data are sent to the server and can access using the web browser or mobile application. The range of the detection concentration is 0~100ppm.Keywords: ammonia, detector, gas, portable
Procedia PDF Downloads 41824427 Development of a Shape Based Estimation Technology Using Terrestrial Laser Scanning
Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park
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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement
Procedia PDF Downloads 23524426 A Non-Invasive Blood Glucose Monitoring System Using near-Infrared Spectroscopy with Remote Data Logging
Authors: Bodhayan Nandi, Shubhajit Roy Chowdhury
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This paper presents the development of a portable blood glucose monitoring device based on Near-Infrared Spectroscopy. The system supports Internet connectivity through WiFi and uploads the time series data of glucose concentration of patients to a server. In addition, the server is given sufficient intelligence to predict the future pathophysiological state of a patient given the current and past pathophysiological data. This will enable to prognosticate the approaching critical condition of the patient much before the critical condition actually occurs.The server hosts web applications to allow authorized users to monitor the data remotely.Keywords: non invasive, blood glucose concentration, microcontroller, IoT, application server, database server
Procedia PDF Downloads 22024425 Proposal to Increase the Efficiency, Reliability and Safety of the Centre of Data Collection Management and Their Evaluation Using Cluster Solutions
Authors: Martin Juhas, Bohuslava Juhasova, Igor Halenar, Andrej Elias
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This article deals with the possibility of increasing efficiency, reliability and safety of the system for teledosimetric data collection management and their evaluation as a part of complex study for activity “Research of data collection, their measurement and evaluation with mobile and autonomous units” within project “Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants”. Possible weaknesses in existing system are identified. A study of available cluster solutions with possibility of their deploying to analysed system is presented.Keywords: teledosimetric data, efficiency, reliability, safety, cluster solution
Procedia PDF Downloads 51524424 Chemical and Physical Modification of Carbon Fiber Reinforced Polymers Based on Thermoplastic Acrylic Resin
Authors: Kamil Dydek, Szymon Demski, Kamil Majchrowicz, Paulina Kozera, Bogna Sztorch, Dariusz Brząkalski, Zuzanna Krawczyk, Robert Przekop, Anna Boczkowska
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Thanks to their excellent properties, i.e. high stiffness and strength in relation to their weight, corrosion resistance, and low thermal expansion, Carbon Fiber Reinforced Polymers (CFRPs) are a group of materials readily used in many industrial sectors, e.g. aviation, automotive, wind energy. Conventional CFRPs also have their disadvantages, namely, relatively low electrical conductivity and brittle cracking. To counteract this, a thermoplastic acrylic resin was proposed, which was further modified by the addition of organosilicon compounds and multi-walled carbon nanotubes (MWCNTs). The addition of the organosilicon compounds was aimed at improving the dispersion of the MWCNTs and obtaining good adhesion between the resin and the carbon fibre, where the MWCNTs were used as a conductive filler. In addition, during the fabrication of laminates using the infusion method, thermoplastic nonwovens doped with MWCNTs were placed between the carbon reinforcement layers to achieve a synergistic effect with an increase in electrical and mechanical properties.Keywords: CFRP, acrylic resin, organosilicon compounds, mechanical properties, electrical properties
Procedia PDF Downloads 12824423 Efficient Storage in Cloud Computing by Using Index Replica
Authors: Bharat Singh Deora, Sushma Satpute
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Cloud computing is based on resource sharing. Like other resources which can be shareable, storage is a resource which can be shared. We can use collective resources of storage from different locations and maintain a central index table for storage details. The storage combining of different places can form a suitable data storage which is operated from one location and is very economical. Proper storage of data should improve data reliability & availability and bandwidth utilization. Also, we are moving the contents of one storage to other according to our need.Keywords: cloud computing, cloud storage, Iaas, PaaS, SaaS
Procedia PDF Downloads 34024422 Thermodynamic Analysis of Ventilated Façades under Operating Conditions in Southern Spain
Authors: Carlos A. Domínguez Torres, Antonio Domínguez Delgado
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In this work we study the thermodynamic behavior of some ventilated facades under summer operating conditions in Southern Spain. Under these climatic conditions, indoor comfort implies a high energetic demand due to high temperatures that usually are reached in this season in the considered geographical area. The aim of this work is to determine if during summer operating conditions in Southern Spain, ventilated façades provide some energy saving compared to the non-ventilated façades and to deduce their behavior patterns in terms of energy efficiency. The modeling of the air flow in the channel has been performed by using Navier-Stokes equations for thermodynamic flows. Numerical simulations have been carried out with a 2D Finite Element approach. This way, we analyze the behavior of ventilated façades under different weather conditions as variable wind, variable temperature and different levels of solar irradiation. CFD computations show that the combined effect of the shading of the external wall and the ventilation by the natural convection into the air gap achieve a reduction of the heat load during the summer period. This reduction has been evaluated by comparing the thermodynamic performances of two ventilated and two unventilated façades with the same geometry and thermophysical characteristics.Keywords: passive cooling, ventilated façades, energy-efficient building, CFD, FEM
Procedia PDF Downloads 35524421 Atomic Decomposition Audio Data Compression and Denoising Using Sparse Dictionary Feature Learning
Authors: T. Bryan , V. Kepuska, I. Kostnaic
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A method of data compression and denoising is introduced that is based on atomic decomposition of audio data using “basis vectors” that are learned from the audio data itself. The basis vectors are shown to have higher data compression and better signal-to-noise enhancement than the Gabor and gammatone “seed atoms” that were used to generate them. The basis vectors are the input weights of a Sparse AutoEncoder (SAE) that is trained using “envelope samples” of windowed segments of the audio data. The envelope samples are extracted from the audio data by performing atomic decomposition with Gabor or gammatone seed atoms. This process identifies segments of audio data that are locally coherent with the seed atoms. Envelope samples are extracted by identifying locally coherent audio data segments with Gabor or gammatone seed atoms, found by matching pursuit. The envelope samples are formed by taking the kronecker products of the atomic envelopes with the locally coherent data segments. Oracle signal-to-noise ratio (SNR) verses data compression curves are generated for the seed atoms as well as the basis vectors learned from Gabor and gammatone seed atoms. SNR data compression curves are generated for speech signals as well as early American music recordings. The basis vectors are shown to have higher denoising capability for data compression rates ranging from 90% to 99.84% for speech as well as music. Envelope samples are displayed as images by folding the time series into column vectors. This display method is used to compare of the output of the SAE with the envelope samples that produced them. The basis vectors are also displayed as images. Sparsity is shown to play an important role in producing the highest denoising basis vectors.Keywords: sparse dictionary learning, autoencoder, sparse autoencoder, basis vectors, atomic decomposition, envelope sampling, envelope samples, Gabor, gammatone, matching pursuit
Procedia PDF Downloads 25324420 Platform-as-a-Service Sticky Policies for Privacy Classification in the Cloud
Authors: Maha Shamseddine, Amjad Nusayr, Wassim Itani
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In this paper, we present a Platform-as-a-Service (PaaS) model for controlling the privacy enforcement mechanisms applied on user data when stored and processed in Cloud data centers. The proposed architecture consists of establishing user configurable ‘sticky’ policies on the Graphical User Interface (GUI) data-bound components during the application development phase to specify the details of privacy enforcement on the contents of these components. Various privacy classification classes on the data components are formally defined to give the user full control on the degree and scope of privacy enforcement including the type of execution containers to process the data in the Cloud. This not only enhances the privacy-awareness of the developed Cloud services, but also results in major savings in performance and energy efficiency due to the fact that the privacy mechanisms are solely applied on sensitive data units and not on all the user content. The proposed design is implemented in a real PaaS cloud computing environment on the Microsoft Azure platform.Keywords: privacy enforcement, platform-as-a-service privacy awareness, cloud computing privacy
Procedia PDF Downloads 22724419 Estimating Tree Height and Forest Classification from Multi Temporal Risat-1 HH and HV Polarized Satellite Aperture Radar Interferometric Phase Data
Authors: Saurav Kumar Suman, P. Karthigayani
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In this paper the height of the tree is estimated and forest types is classified from the multi temporal RISAT-1 Horizontal-Horizontal (HH) and Horizontal-Vertical (HV) Polarised Satellite Aperture Radar (SAR) data. The novelty of the proposed project is combined use of the Back-scattering Coefficients (Sigma Naught) and the Coherence. It uses Water Cloud Model (WCM). The approaches use two main steps. (a) Extraction of the different forest parameter data from the Product.xml, BAND-META file and from Grid-xxx.txt file come with the HH & HV polarized data from the ISRO (Indian Space Research Centre). These file contains the required parameter during height estimation. (b) Calculation of the Vegetation and Ground Backscattering, Coherence and other Forest Parameters. (c) Classification of Forest Types using the ENVI 5.0 Tool and ROI (Region of Interest) calculation.Keywords: RISAT-1, classification, forest, SAR data
Procedia PDF Downloads 40724418 Presenting a Model for Predicting the State of Being Accident-Prone of Passages According to Neural Network and Spatial Data Analysis
Authors: Hamd Rezaeifar, Hamid Reza Sahriari
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Accidents are considered to be one of the challenges of modern life. Due to the fact that the victims of this problem and also internal transportations are getting increased day by day in Iran, studying effective factors of accidents and identifying suitable models and parameters about this issue are absolutely essential. The main purpose of this research has been studying the factors and spatial data affecting accidents of Mashhad during 2007- 2008. In this paper it has been attempted to – through matching spatial layers on each other and finally by elaborating them with the place of accident – at the first step by adding landmarks of the accident and through adding especial fields regarding the existence or non-existence of effective phenomenon on accident, existing information banks of the accidents be completed and in the next step by means of data mining tools and analyzing by neural network, the relationship between these data be evaluated and a logical model be designed for predicting accident-prone spots with minimum error. The model of this article has a very accurate prediction in low-accident spots; yet it has more errors in accident-prone regions due to lack of primary data.Keywords: accident, data mining, neural network, GIS
Procedia PDF Downloads 4724417 Methodology of the Turkey’s National Geographic Information System Integration Project
Authors: Buse A. Ataç, Doğan K. Cenan, Arda Çetinkaya, Naz D. Şahin, Köksal Sanlı, Zeynep Koç, Akın Kısa
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With its spatial data reliability, interpretation and questioning capabilities, Geographical Information Systems make significant contributions to scientists, planners and practitioners. Geographic information systems have received great attention in today's digital world, growing rapidly, and increasing the efficiency of use. Access to and use of current and accurate geographical data, which are the most important components of the Geographical Information System, has become a necessity rather than a need for sustainable and economic development. This project aims to enable sharing of data collected by public institutions and organizations on a web-based platform. Within the scope of the project, INSPIRE (Infrastructure for Spatial Information in the European Community) data specifications are considered as a road-map. In this context, Turkey's National Geographic Information System (TUCBS) Integration Project supports sharing spatial data within 61 pilot public institutions as complied with defined national standards. In this paper, which is prepared by the project team members in the TUCBS Integration Project, the technical process with a detailed methodology is explained. In this context, the main technical processes of the Project consist of Geographic Data Analysis, Geographic Data Harmonization (Standardization), Web Service Creation (WMS, WFS) and Metadata Creation-Publication. In this paper, the integration process carried out to provide the data produced by 61 institutions to be shared from the National Geographic Data Portal (GEOPORTAL), have been trying to be conveyed with a detailed methodology.Keywords: data specification, geoportal, GIS, INSPIRE, Turkish National Geographic Information System, TUCBS, Turkey's national geographic information system
Procedia PDF Downloads 14424416 Secure Content Centric Network
Authors: Syed Umair Aziz, Muhammad Faheem, Sameer Hussain, Faraz Idris
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Content centric network is the network based on the mechanism of sending and receiving the data based on the interest and data request to the specified node (which has cached data). In this network, the security is bind with the content not with the host hence making it host independent and secure. In this network security is applied by taking content’s MAC (message authentication code) and encrypting it with the public key of the receiver. On the receiver end, the message is first verified and after verification message is saved and decrypted using the receiver's private key.Keywords: content centric network, client-server, host security threats, message authentication code, named data network, network caching, peer-to-peer
Procedia PDF Downloads 64424415 Fuel Inventory/ Depletion Analysis for a Thorium-Uranium Dioxide (Th-U) O2 Pin Cell Benchmark Using Monte Carlo and Deterministic Codes with New Version VIII.0 of the Evaluated Nuclear Data File (ENDF/B) Nuclear Data Library
Authors: Jamal Al-Zain, O. El Hajjaji, T. El Bardouni
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A (Th-U) O2 fuel pin benchmark made up of 25 w/o U and 75 w/o Th was used. In order to analyze the depletion and inventory of the fuel for the pressurized water reactor pin-cell model. The new version VIII.0 of the ENDF/B nuclear data library was used to create a data set in ACE format at various temperatures and process the data using the MAKXSF6.2 and NJOY2016 programs to process the data at the various temperatures in order to conduct this study and analyze cross-section data. The infinite multiplication factor, the concentrations and activities of the main fission products, the actinide radionuclides accumulated in the pin cell, and the total radioactivity were all estimated and compared in this study using the Monte Carlo N-Particle 6 (MCNP6.2) and DRAGON5 programs. Additionally, the behavior of the Pressurized Water Reactor (PWR) thorium pin cell that is dependent on burn-up (BU) was validated and compared with the reference data obtained using the Massachusetts Institute of Technology (MIT-MOCUP), Idaho National Engineering and Environmental Laboratory (INEEL-MOCUP), and CASMO-4 codes. The results of this study indicate that all of the codes examined have good agreements.Keywords: PWR thorium pin cell, ENDF/B-VIII.0, MAKXSF6.2, NJOY2016, MCNP6.2, DRAGON5, fuel burn-up.
Procedia PDF Downloads 10324414 Nest-Site Selection of Crested Lark (Galerida cristata) in Yazd Province, Iran
Authors: Shirin Aghanajafizadeh
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Nest site selection of Crested Lark was investigated in Boroyeh wildlife sanctuary of Harat during spring 2014. Habitat variables such as number of plant species, soil texture, distance to the nearest water resources, farms and roads were compared in the species presence plots with absence ones. Our analysis showed that the average number of Zygophyllum atriplicoidesand, Artemisia sieberi were higher while fine-textured soil percent cover (with very little and gravel) was lower in species presence plots than control plots. We resulted that the most affecting factor in the species nest site selection is the number of Z .atriplicoides and soil texture. Z. atriplicoides and A. sieberi can provide cover for nests and chickens against predators and environmental harsh events such as sunshine and wind. The stability of built nest forces the birds to select sites with not fine-textured soil. Some of the nests were detected in Alfalfa farms that can be related to its cover producing capability.Keywords: habitat selection, Yazd Province, presence and absence plots, habitat variables
Procedia PDF Downloads 18624413 Natural Language News Generation from Big Data
Authors: Bastian Haarmann, Likas Sikorski
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In this paper, we introduce an NLG application for the automatic creation of ready-to-publish texts from big data. The fully automatic generated stories have a high resemblance to the style in which the human writer would draw up a news story. Topics may include soccer games, stock exchange market reports, weather forecasts and many more. The generation of the texts runs according to the human language production. Each generated text is unique. Ready-to-publish stories written by a computer application can help humans to quickly grasp the outcomes of big data analyses, save time-consuming pre-formulations for journalists and cater to rather small audiences by offering stories that would otherwise not exist.Keywords: big data, natural language generation, publishing, robotic journalism
Procedia PDF Downloads 43124412 Performance Evaluation of the Classic seq2seq Model versus a Proposed Semi-supervised Long Short-Term Memory Autoencoder for Time Series Data Forecasting
Authors: Aswathi Thrivikraman, S. Advaith
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The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.Keywords: LSTM, autoencoder, forecasting, seq2seq model
Procedia PDF Downloads 15624411 The Analysis of Emergency Shutdown Valves Torque Data in Terms of Its Use as a Health Indicator for System Prognostics
Authors: Ewa M. Laskowska, Jorn Vatn
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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL
Procedia PDF Downloads 9124410 Spatial Distribution of Ambient BTEX Concentrations at an International Airport in South Africa
Authors: Raeesa Moolla, Ryan S. Johnson
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Air travel, and the use of airports, has experienced proliferative growth in the past few decades, resulting in the concomitant release of air pollutants. Air pollution needs to be monitored because of the known relationship between exposure to air pollutants and increased adverse effects on human health. This study monitored a group of volatile organic compounds (VOCs); specifically BTEX (viz. benzene, toluene, ethyl-benzene and xylenes), as many are detrimental to human health. Through the use of passive sampling methods, the spatial variability of BTEX within an international airport was investigated, in order to determine ‘hotspots’ where occupational exposure to BTEX may be intensified. The passive sampling campaign revealed BTEXtotal concentrations ranged between 12.95–124.04 µg m-3. Furthermore, BTEX concentrations were dispersed heterogeneously within the airport. Due to the slow wind speeds recorded (1.13 m.s-1); the hotspots were located close to their main BTEX sources. The main hotspot was located over the main apron of the airport. Employees working in this area may be chronically exposed to these emissions, which could be potentially detrimental to their health.Keywords: air pollution, air quality, hotspot monitoring, volatile organic compounds
Procedia PDF Downloads 17224409 Block Mining: Block Chain Enabled Process Mining Database
Authors: James Newman
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Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.Keywords: blockchain, process mining, memory optimization, protocol
Procedia PDF Downloads 10324408 Vulnerability of Groundwater to Pollution in Akwa Ibom State, Southern Nigeria, using the DRASTIC Model and Geographic Information System (GIS)
Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze
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Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.Keywords: groundwater, vulnerability, DRASTIC model, pollution
Procedia PDF Downloads 20724407 A Review Paper on Data Security in Precision Agriculture Using Internet of Things
Authors: Tonderai Muchenje, Xolani Mkhwanazi
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Precision agriculture uses a number of technologies, devices, protocols, and computing paradigms to optimize agricultural processes. Big data, artificial intelligence, cloud computing, and edge computing are all used to handle the huge amounts of data generated by precision agriculture. However, precision agriculture is still emerging and has a low level of security features. Furthermore, future solutions will demand data availability and accuracy as key points to help farmers, and security is important to build robust and efficient systems. Since precision agriculture comprises a wide variety and quantity of resources, security addresses issues such as compatibility, constrained resources, and massive data. Moreover, conventional protection schemes used in the traditional internet may not be useful for agricultural systems, creating extra demands and opportunities. Therefore, this paper aims at reviewing state of the art of precision agriculture security, particularly in open field agriculture, discussing its architecture, describing security issues, and presenting the major challenges and future directions.Keywords: precision agriculture, security, IoT, EIDE
Procedia PDF Downloads 9024406 Commercial Automobile Insurance: A Practical Approach of the Generalized Additive Model
Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou
Abstract:
The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.Keywords: insurance, data science, modeling, monitoring, regulation, processes
Procedia PDF Downloads 7624405 Crater Pattern on the Moon and Origin of the Moon
Authors: Xuguang Leng
Abstract:
The crater pattern on the Moon indicates the Moon was captured by Earth in the more recent years, disproves the theory that the Moon was born as a satellite to the Earth. The Moon was tidal locked since it became the satellite of the Earth. Moon’s near side is shielded by Earth from asteroid/comet collisions, with the center of the near side most protected. Yet the crater pattern on the Moon is fairly random, with no distinguishable empty spot/strip, no distinguishable difference near side vs. far side. Were the Moon born as Earth’s satellite, there would be a clear crater free spot, or strip should the tial lock shifts over time, on the near side; and far more craters on the far side. The nonexistence of even a vague crater free spot on the near side of the Moon indicates the capture was a more recent event. Given Earth’s much larger mass and sphere size over the Moon, Earth should have collided with asteroids and comets in much higher frequency, resulting in significant mass gain over the lifespan. Earth’s larger mass and magnetic field are better at retaining water and gas from solar wind’s stripping effect, thus accelerating the mass gain. A dwarf planet Moon can be pulled closer and closer to the Earth over time as Earth’s gravity grows stronger, eventually being captured as a satellite. Given enough time, it is possible Earth’s mass would be large enough to cause the Moon to collide with Earth.Keywords: moon, origin, crater, pattern
Procedia PDF Downloads 97