Search results for: manual data inquiry
22339 Deliberation of Daily Evapotranspiration and Evaporative Fraction Based on Remote Sensing Data
Authors: J. Bahrawi, M. Elhag
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Estimation of evapotranspiration is always a major component in water resources management. Traditional techniques of calculating daily evapotranspiration based on field measurements are valid only for local scales. Earth observation satellite sensors are thus used to overcome difficulties in obtaining daily evapotranspiration measurements on regional scale. The Surface Energy Balance System (SEBS) model was adopted to estimate daily evapotranspiration and relative evaporation along with other land surface energy fluxes. The model requires agro-climatic data that improve the model outputs. Advance Along Track Scanning Radiometer (AATSR) and Medium Spectral Resolution Imaging Spectrometer (MERIS) imageries were used to estimate the daily evapotranspiration and relative evaporation over the entire Nile Delta region in Egypt supported by meteorological data collected from six different weather stations located within the study area. Daily evapotranspiration maps derived from SEBS model show a strong agreement with actual ground-truth data taken from 92 points uniformly distributed all over the study area. Moreover, daily evapotranspiration and relative evaporation are strongly correlated. The reliable estimation of daily evapotranspiration supports the decision makers to review the current land use practices in terms of water management, while enabling them to propose proper land use changes.Keywords: daily evapotranspiration, relative evaporation, SEBS, AATSR, MERIS, Nile Delta
Procedia PDF Downloads 25422338 High Secure Data Hiding Using Cropping Image and Least Significant Bit Steganography
Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway
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This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.Keywords: steganography, stego, LSB, crop
Procedia PDF Downloads 26322337 Evaluation of the Energy Performance and Emissions of an Aircraft Engine: J69 Using Fuel Blends of Jet A1 and Biodiesel
Authors: Gabriel Fernando Talero Rojas, Vladimir Silva Leal, Camilo Bayona-Roa, Juan Pava, Mauricio Lopez Gomez
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The substitution of conventional aviation fuels with biomass-derived alternative fuels is an emerging field of study in the aviation transport, mainly due to its energy consumption, the contribution to the global Greenhouse Gas - GHG emissions and the fossil fuel price fluctuations. Nevertheless, several challenges remain as the biofuel production cost and its degradative effect over the fuel systems that alter the operating safety. Moreover, experimentation on full-scale aeronautic turbines are expensive and complex, leading to most of the research to the testing of small-size turbojets with a major absence of information regarding the effects in the energy performance and the emissions. The main purpose of the current study is to present the results of experimentation in a full-scale military turbojet engine J69-T-25A (presented in Fig. 1) with 640 kW of power rating and using blends of Jet A1 with oil palm biodiesel. The main findings are related to the thrust specific fuel consumption – TSFC, the engine global efficiency – η, the air/fuel ratio – AFR and the volume fractions of O2, CO2, CO, and HC. Two fuels are used in the present study: a commercial Jet A1 and a Colombian palm oil biodiesel. The experimental plan is conducted using the biodiesel volume contents - w_BD from 0 % (B0) to 50 % (B50). The engine operating regimes are set to Idle, Cruise, and Take-off conditions. The turbojet engine J69 is used by the Colombian Air Force and it is installed in a testing bench with the instrumentation that corresponds to the technical manual of the engine. The increment of w_BD from 0 % to 50 % reduces the η near 3,3 % and the thrust force in a 26,6 % at Idle regime. These variations are related to the reduction of the 〖HHV〗_ad of the fuel blend. The evolved CO and HC tend to be reduced in all the operating conditions when increasing w_BD. Furthermore, a reduction of the atomization angle is presented in Fig. 2, indicating a poor atomization in the fuel nozzle injectors when using a higher biodiesel content as the viscosity of fuel blend increases. An evolution of cloudiness is also observed during the shutdown procedure as presented in Fig. 3a, particularly after 20 % of biodiesel content in the fuel blend. This promotes the contamination of some components of the combustion chamber of the J69 engine with soot and unburned matter (Fig. 3). Thus, the substitution of biodiesel content above 20 % is not recommended in order to avoid a significant decrease of η and the thrust force. A more detail examination of the mechanical wearing of the main components of the engine is advised in further studies.Keywords: aviation, air to fuel ratio, biodiesel, energy performance, fuel atomization, gas turbine
Procedia PDF Downloads 10222336 A Usability Framework to Influence the Intention to Use Mobile Fitness Applications in South Africa
Authors: Bulelani Ngamntwini, Liezel Cilliers
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South Africa has one of the highest prevalence of obese people on the African continent. Forty-six percent of the adults in South Africa are physically inactive. Fitness applications can be used to increase physical inactivity. However, the uptake of mobile fitness applications in South Africa has been found to be poor due to usability challenges with the technology. The study developed a usability framework to influence the intention to use mobile fitness applications in South Africa. The study made use of a positivistic approach to collect data. A questionnaire was used to collect quantitative data from 377 respondents that have used mobile fitness applications in the past. A response rate of 80.90% was recorded. To analyse the data, the Pearson correlation was used to determine the relationships between the various hypotheses. There are four usability factors, efficiency, effectiveness, satisfaction, and learnability, which contribute to the intention of users to make use of mobile fitness applications. The study, therefore, recommends that for a mobile fitness application to be successful, these four factors must be considered and incorporated by developers when designing the applications.Keywords: obese, overweight, physical inactivity, mobile fitness application, usability factors
Procedia PDF Downloads 15622335 Non-Signaling Chemokine Receptor CCRL1 and Its Active Counterpart CCR7 in Prostate Cancer
Authors: Yiding Qu, Svetlana V. Komarova
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Chemokines acting through their cognate chemokine receptors guide the directional migration of the cell along the chemokine gradient. Several chemokine receptors were recently identified as non-signaling (decoy), based on their ability to bind the chemokine but produce no measurable signal in the cell. The function of these decoy receptors is not well understood. We examined the expression of a decoy receptor CCRL1 and a signaling receptor that binds to the same ligands, CCR7, in prostate cancer using publically available microarray data (www.oncomine.org). The expression of both CCRL1 and CCR7 increased in an approximately half of prostate carcinoma samples and the majority of metastatic cancer samples compared to normal prostate. Moreover, the expression of CCRL1 positively correlated with the expression of CCR7. These data suggest that CCR7 and CCRL1 can be used as clinical markers for the early detection of transformation from carcinoma to metastatic cancer. In addition, these data support our hypothesis that the non-signaling chemokine receptors actively stimulate cell migration.Keywords: bioinformatics, cell migration, decoy receptor, meta-analysis, prostate cancer
Procedia PDF Downloads 46322334 Developing NAND Flash-Memory SSD-Based File System Design
Authors: Jaechun No
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This paper focuses on I/O optimizations of N-hybrid (New-Form of hybrid), which provides a hybrid file system space constructed on SSD and HDD. Although the promising potentials of SSD, such as the absence of mechanical moving overhead and high random I/O throughput, have drawn a lot of attentions from IT enterprises, its high ratio of cost/capacity makes it less desirable to build a large-scale data storage subsystem composed of only SSDs. In this paper, we present N-hybrid that attempts to integrate the strengths of SSD and HDD, to offer a single, large hybrid file system space. Several experiments were conducted to verify the performance of N-hybrid.Keywords: SSD, data section, I/O optimizations, hybrid system
Procedia PDF Downloads 41222333 Air Handling Units Power Consumption Using Generalized Additive Model for Anomaly Detection: A Case Study in a Singapore Campus
Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo
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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning
Procedia PDF Downloads 14422332 Sentiment Analysis: An Enhancement of Ontological-Based Features Extraction Techniques and Word Equations
Authors: Mohd Ridzwan Yaakub, Muhammad Iqbal Abu Latiffi
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Online business has become popular recently due to the massive amount of information and medium available on the Internet. This has resulted in the huge number of reviews where the consumers share their opinion, criticisms, and satisfaction on the products they have purchased on the websites or the social media such as Facebook and Twitter. However, to analyze customer’s behavior has become very important for organizations to find new market trends and insights. The reviews from the websites or the social media are in structured and unstructured data that need a sentiment analysis approach in analyzing customer’s review. In this article, techniques used in will be defined. Definition of the ontology and description of its possible usage in sentiment analysis will be defined. It will lead to empirical research that related to mobile phones used in research and the ontology used in the experiment. The researcher also will explore the role of preprocessing data and feature selection methodology. As the result, ontology-based approach in sentiment analysis can help in achieving high accuracy for the classification task.Keywords: feature selection, ontology, opinion, preprocessing data, sentiment analysis
Procedia PDF Downloads 19122331 Construction of the Large Scale Biological Networks from Microarrays
Authors: Fadhl Alakwaa
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One of the sustainable goals of the system biology is understanding gene-gene interactions. Hence, gene regulatory networks (GRN) need to be constructed for understanding the disease ontology and to reduce the cost of drug development. To construct gene regulatory from gene expression we need to overcome many challenges such as data denoising and dimensionality. In this paper, we develop an integrated system to reduce data dimension and remove the noise. The generated network from our system was validated via available interaction databases and was compared to previous methods. The result revealed the performance of our proposed method.Keywords: gene regulatory network, biclustering, denoising, system biology
Procedia PDF Downloads 22722330 Assessment of Soil Salinity through Remote Sensing Technique in the Coastal Region of Bangladesh
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Soil salinity is a major problem for the coastal region of Bangladesh, which has been increasing for the last four decades. Determination of soil salinity is essential for proper land use planning for agricultural crop production. The aim of the research is to estimate and monitor the soil salinity in the study area. Remote sensing can be an effective tool for detecting soil salinity in data-scarce conditions. In the research, Landsat 8 is used, which required atmospheric and radiometric correction, and nine soil salinity indices are applied to develop a soil salinity map. Ground soil salinity data, i.e., EC value, is collected as a printed map which is then scanned and digitized to develop a point shapefile. Linear regression is made between satellite-based generated map and ground soil salinity data, i.e., EC value. The results show that maximum R² value is found for salinity index SI 7 = G*R/B representing 0.022. This minimal R² value refers that there is a negligible relationship between ground EC value and salinity index generated value. Hence, these indices are not appropriate to assess soil salinity though many studies used those soil salinity indices successfully. Therefore, further research is necessary to formulate a model for determining the soil salinity in the coastal of Bangladesh.Keywords: soil salinity, EC, Landsat 8, salinity indices, linear regression, remote sensing
Procedia PDF Downloads 32922329 Psychogeographic Analysis of Spatial Appropriation within Walking Practice: The City Centre versus University Campus in the Case of Van, Turkey
Authors: Yasemin Ilkay
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Urban spatial pattern interacts with the minds and bodies of citizens and influences their perception and attitudes, which leads to a two-folded map of the same space: physical and Psychogeographic maps. Psychogeography is a field of inquiry (rooted in literature and fiction) investigating how the environment affects the feelings and behaviors of individuals. This term was posed by Situationist International Movement in the 1950s by Guy Debord; in the course of time, the artistic framework evolved into a political issue, especially with the term Dérive, which indicates ‘deviation’ and ‘resistance’ to the existing spatial reality. The term Dérive appeared on the track of Flânéur after one hundred years; and turned out to be a political tool to transform everyday urban life. The three main concepts of psychogeography [walking, dérive, and palimpsest] construct the epistemological framework for a psychogeographic spatial analysis. Mental representations investigating this framework would provide a designer to capture the invisible layers of the gap between ‘how a space is conceived’ and ‘how the same space is perceived and experienced.’ This gap is a neglected but critical issue to discuss in the planning discipline, and psychogeography provides methodological inputs to cover the interrelation among top-down designs of urban patterning and bottom-up reproductions of ‘the soul’ of urban space at the intersection of geography and psychology. City centers and university campuses exemplify opposite poles of spatial organization and walking practice, which may result in differentiated spatial appropriation forms. There is a traditional city center in Van, located at the core of the city with a dense population and several activities, but not connected to Van Lake, which is the largest lake in the country. On the other hand, the university campus is located at the periphery, and although it has a promenade along the lake’s coast and a regional hospital, it presents a limited walking experience with ambiguous forms of spatial appropriation. The city center draws a vivid urban everyday life; however, the campus presents a relatively natural life far away from the center. This paper aims to reveal the differentiated psychogeographic maps of spatial appropriation at the city center vs. the university campus, which is located at the periphery of the city and along the coast of the largest lake in Turkey. The main question of the paper is, “how do the psychogeographic maps of spatial appropriation differentiate at the city center and university campus in Van within the walking experience with reference to the two-folded map assumption.” The experiential maps of a core group of 15 planning students will be created with the techniques of mental mapping, photographing, and narratives through attentive walks conducted together on selected routes; in addition to these attentive walks, 30 more in-depth interviews will be conducted by the core group. The narrative of psychogeographic mapping of spatial appropriation at the two spatial poles would display the conflicting soul of the city with reference to sub-behavioural regions of walking, differentiated forms of derive and layers of palimpsest.Keywords: attentive walk, body, cognitive geography, derive, experiential maps, psychogeography, Van, Turkey
Procedia PDF Downloads 7322328 Despiking of Turbulent Flow Data in Gravel Bed Stream
Authors: Ratul Das
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The present experimental study insights the decontamination of instantaneous velocity fluctuations captured by Acoustic Doppler Velocimeter (ADV) in gravel-bed streams to ascertain near-bed turbulence for low Reynolds number. The interference between incidental and reflected pulses produce spikes in the ADV data especially in the near-bed flow zone and therefore filtering the data are very essential. Nortek’s Vectrino four-receiver ADV probe was used to capture the instantaneous three-dimensional velocity fluctuations over a non-cohesive bed. A spike removal algorithm based on the acceleration threshold method was applied to note the bed roughness and its influence on velocity fluctuations and velocity power spectra in the carrier fluid. The velocity power spectra of despiked signals with a best combination of velocity threshold (VT) and acceleration threshold (AT) are proposed which ascertained velocity power spectra a satisfactory fit with the Kolmogorov “–5/3 scaling-law” in the inertial sub-range. Also, velocity distributions below the roughness crest level fairly follows a third-degree polynomial series.Keywords: acoustic doppler velocimeter, gravel-bed, spike removal, reynolds shear stress, near-bed turbulence, velocity power spectra
Procedia PDF Downloads 29722327 RS Based SCADA System for Longer Distance Powered Devices
Authors: Harkishen Singh, Gavin Mangeni
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This project aims at building an efficient and automatic power monitoring SCADA system, which is capable of monitoring the electrical parameters of high voltage powered devices in real time for example RMS voltage and current, frequency, energy consumed, power factor etc. The system uses RS-485 serial communication interface to transfer data over longer distances. Embedded C programming is the platform used to develop two hardware modules namely: RTU and Master Station modules, which both use the CC2540 BLE 4.0 microcontroller configured in slave / master mode. The Si8900 galvanic ally isolated microchip is used to perform ADC externally. The hardware communicates via UART port and sends data to the user PC using the USB port. Labview software is used to design a user interface to display current state of the power loads being monitored as well as logs data to excel spreadsheet file. An understanding of the Si8900’s auto baud rate process is key to successful implementation of this project.Keywords: SCADA, RS485, CC2540, labview, Si8900
Procedia PDF Downloads 29322326 Creating Database and Building 3D Geological Models: A Case Study on Bac Ai Pumped Storage Hydropower Project
Authors: Nguyen Chi Quang, Nguyen Duong Tri Nguyen
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This article is the first step to research and outline the structure of the geotechnical database in the geological survey of a power project; in the context of this report creating the database that has been carried out for the Bac Ai pumped storage hydropower project. For the purpose of providing a method of organizing and storing geological and topographic survey data and experimental results in a spatial database, the RockWorks software is used to bring optimal efficiency in the process of exploiting, using, and analyzing data in service of the design work in the power engineering consulting. Three-dimensional (3D) geotechnical models are created from the survey data: such as stratigraphy, lithology, porosity, etc. The results of the 3D geotechnical model in the case of Bac Ai pumped storage hydropower project include six closely stacked stratigraphic formations by Horizons method, whereas modeling of engineering geological parameters is performed by geostatistical methods. The accuracy and reliability assessments are tested through error statistics, empirical evaluation, and expert methods. The three-dimensional model analysis allows better visualization of volumetric calculations, excavation and backfilling of the lake area, tunneling of power pipelines, and calculation of on-site construction material reserves. In general, the application of engineering geological modeling makes the design work more intuitive and comprehensive, helping construction designers better identify and offer the most optimal design solutions for the project. The database always ensures the update and synchronization, as well as enables 3D modeling of geological and topographic data to integrate with the designed data according to the building information modeling. This is also the base platform for BIM & GIS integration.Keywords: database, engineering geology, 3D Model, RockWorks, Bac Ai pumped storage hydropower project
Procedia PDF Downloads 15522325 Blockchain Technology for Secure and Transparent Oil and Gas Supply Chain Management
Authors: Gaurav Kumar Sinha
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The oil and gas industry, characterized by its complex and global supply chains, faces significant challenges in ensuring security, transparency, and efficiency. Blockchain technology, with its decentralized and immutable ledger, offers a transformative solution to these issues. This paper explores the application of blockchain technology in the oil and gas supply chain, highlighting its potential to enhance data security, improve transparency, and streamline operations. By leveraging smart contracts, blockchain can automate and secure transactions, reducing the risk of fraud and errors. Additionally, the integration of blockchain with IoT devices enables real-time tracking and monitoring of assets, ensuring data accuracy and integrity throughout the supply chain. Case studies and pilot projects within the industry demonstrate the practical benefits and challenges of implementing blockchain solutions. The findings suggest that blockchain technology can significantly improve trust and collaboration among supply chain participants, ultimately leading to more efficient and resilient operations. This study provides valuable insights for industry stakeholders considering the adoption of blockchain technology to address their supply chain management challenges.Keywords: blockchain technology, oil and gas supply chain, data security, transparency, smart contracts, IoT integration, real-time tracking, asset monitoring, fraud reduction, supply chain efficiency, data integrity, case studies, industry implementation, trust, collaboration.
Procedia PDF Downloads 2922324 The Inequality Effects of Natural Disasters: Evidence from Thailand
Authors: Annop Jaewisorn
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This study explores the relationship between natural disasters and inequalities -both income and expenditure inequality- at a micro-level of Thailand as the first study of this nature for this country. The analysis uses a unique panel and remote-sensing dataset constructed for the purpose of this research. It contains provincial inequality measures and other economic and social indicators based on the Thailand Household Survey during the period between 1992 and 2019. Meanwhile, the data on natural disasters, which are remote-sensing data, are received from several official geophysical or meteorological databases. Employing a panel fixed effects, the results show that natural disasters significantly reduce household income and expenditure inequality as measured by the Gini index, implying that rich people in Thailand bear a higher cost of natural disasters when compared to poor people. The effect on income inequality is mainly driven by droughts, while the effect on expenditure inequality is mainly driven by flood events. The results are robust across heterogeneity of the samples, lagged effects, outliers, and an alternative inequality measure.Keywords: inequality, natural disasters, remote-sensing data, Thailand
Procedia PDF Downloads 11622323 Non-Local Simultaneous Sparse Unmixing for Hyperspectral Data
Authors: Fanqiang Kong, Chending Bian
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Sparse unmixing is a promising approach in a semisupervised fashion by assuming that the observed pixels of a hyperspectral image can be expressed in the form of linear combination of only a few pure spectral signatures (end members) in an available spectral library. However, the sparse unmixing problem still remains a great challenge at finding the optimal subset of endmembers for the observed data from a large standard spectral library, without considering the spatial information. Under such circumstances, a sparse unmixing algorithm termed as non-local simultaneous sparse unmixing (NLSSU) is presented. In NLSSU, the non-local simultaneous sparse representation method for endmember selection of sparse unmixing, is used to finding the optimal subset of endmembers for the similar image patch set in the hyperspectral image. And then, the non-local means method, as a regularizer for abundance estimation of sparse unmixing, is used to exploit the abundance image non-local self-similarity. Experimental results on both simulated and real data demonstrate that NLSSU outperforms the other algorithms, with a better spectral unmixing accuracy.Keywords: hyperspectral unmixing, simultaneous sparse representation, sparse regression, non-local means
Procedia PDF Downloads 23922322 Human Resource Management Practices, Person-Environment Fit and Financial Performance in Brazilian Publicly Traded Companies
Authors: Bruno Henrique Rocha Fernandes, Amir Rezaee, Jucelia Appio
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The relation between Human Resource Management (HRM) practices and organizational performance remains the subject of substantial literature. Though many studies demonstrated positive relationship, still major influencing variables are not yet clear. This study considers the Person-Environment Fit (PE Fit) and its components, Person-Supervisor (PS), Person-Group (PG), Person-Organization (PO) and Person-Job (PJ) Fit, as possible explanatory variables. We analyzed PE Fit as a moderator between HRM practices and financial performance in the “best companies to work” in Brazil. Data from HRM practices were classified through the High Performance Working Systems (HPWS) construct and data on PE-Fit were obtained through surveys among employees. Financial data, consisting of return on invested capital (ROIC) and price earnings ratio (PER) were collected for publicly traded best companies to work. Findings show that PO Fit and PJ Fit play a significant moderator role for PER but not for ROIC.Keywords: financial performance, human resource management, high performance working systems, person-environment fit
Procedia PDF Downloads 16322321 Flow Duration Curves and Recession Curves Connection through a Mathematical Link
Authors: Elena Carcano, Mirzi Betasolo
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This study helps Public Water Bureaus in giving reliable answers to water concession requests. Rapidly increasing water requests can be supported provided that further uses of a river course are not totally compromised, and environmental features are protected as well. Strictly speaking, a water concession can be considered a continuous drawing from the source and causes a mean annual streamflow reduction. Therefore, deciding if a water concession is appropriate or inappropriate seems to be easily solved by comparing the generic demand to the mean annual streamflow value at disposal. Still, the immediate shortcoming for such a comparison is that streamflow data are information available only for few catchments and, most often, limited to specific sites. Subsequently, comparing the generic water demand to mean daily discharge is indeed far from being completely satisfactory since the mean daily streamflow is greater than the water withdrawal for a long period of a year. Consequently, such a comparison appears to be of little significance in order to preserve the quality and the quantity of the river. In order to overcome such a limit, this study aims to complete the information provided by flow duration curves introducing a link between Flow Duration Curves (FDCs) and recession curves and aims to show the chronological sequence of flows with a particular focus on low flow data. The analysis is carried out on 25 catchments located in North-Eastern Italy for which daily data are provided. The results identify groups of catchments as hydrologically homogeneous, having the lower part of the FDCs (corresponding streamflow interval is streamflow Q between 300 and 335, namely: Q(300), Q(335)) smoothly reproduced by a common recession curve. In conclusion, the results are useful to provide more reliable answers to water request, especially for those catchments which show similar hydrological response and can be used for a focused regionalization approach on low flow data. A mathematical link between streamflow duration curves and recession curves is herein provided, thus furnishing streamflow duration curves information upon a temporal sequence of data. In such a way, by introducing assumptions on recession curves, the chronological sequence upon low flow data can also be attributed to FDCs, which are known to lack this information by nature.Keywords: chronological sequence of discharges, recession curves, streamflow duration curves, water concession
Procedia PDF Downloads 17522320 Alternating Expectation-Maximization Algorithm for a Bilinear Model in Isoform Quantification from RNA-Seq Data
Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu
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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq
Procedia PDF Downloads 13522319 A New Distribution and Application on the Lifetime Data
Authors: Gamze Ozel, Selen Cakmakyapan
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We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood
Procedia PDF Downloads 49622318 Comparative Study between the Absorbed Dose of 67ga-Ecc and 68ga-Ecc
Authors: H. Yousefnia, S. Zolghadri, S. Shanesazzadeh, A.Lahooti, A. R. Jalilian
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In this study, 68Ga-ECC and 67Ga-ECC were both prepared with the radiochemical purity of higher than 97% in less than 30 min. The biodistribution data for 68Ga-ECC showed the extraction of the most of the activity from the urinary tract. The absorbed dose was estimated based on biodistribution data in mice by the medical internal radiation dose (MIRD) method. Comparison between human absorbed dose estimation for these two agents indicated the values of approximately ten-fold higher after injection of 67Ga-ECC than 68Ga-ECC in the most organs. The results showed that 68Ga-ECC can be considered as a more potential agent for renal imaging compared to 67Ga-ECC.Keywords: effective absorbed dose, ethylenecysteamine cysteine, Ga-67, Ga-68
Procedia PDF Downloads 46522317 Privacy Label: An Alternative Approach to Present Privacy Policies from Online Services to the User
Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo
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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.Keywords: privacy, policies, user behavior, computer human interaction
Procedia PDF Downloads 29622316 Logistic Regression Model versus Additive Model for Recurrent Event Data
Authors: Entisar A. Elgmati
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Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event
Procedia PDF Downloads 62722315 From Industry 4.0 to Agriculture 4.0: A Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability
Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli
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Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.Keywords: agriculture 4.0, agri-food suppy chain, industry 4.0, voluntary traceability
Procedia PDF Downloads 14022314 Investigation of the Relationship between Personality Components and Tendency to Addiction to Domestic Violence
Authors: Mohamad Reza Khodabakhsh
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Violence against women is a historical phenomenon; although its form and type are common in various societies and cultures, this type of violence occurs in terms of physical, psychological, financial, and sexual dimensions. This is the cause of many social deviations and endangers the center of the family as the most important institution. This research seeks to investigate the relationship between personality characteristics and the tendency to addiction to domestic violence. One hundred fifty women and one hundred fifty men were selected by the available sampling method. One hundred fifty men were admitted to drug addiction camps, and women included domestic violence cases. A questionnaire on addiction tendency, Five Personality Traits (NEO), and attitudes toward violence against women was used. Data were analyzed in descriptive and inferential statistics. The data were analyzed at the level of descriptive mean, mean, and standard deviation and analyzed using SPSS 20 software using correlation and analysis of variance at the level of inferential level. And the data were analyzed at the p≤0.05 significance level. The results showed that there is a significant relationship between personality traits and a tendency to addiction and domestic violence.Keywords: personality, addiction, domestic violence, family
Procedia PDF Downloads 9622313 Artificial Intelligence Assisted Sentiment Analysis of Hotel Reviews Using Topic Modeling
Authors: Sushma Ghogale
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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis
Procedia PDF Downloads 9322312 Modelling Fluoride Pollution of Groundwater Using Artificial Neural Network in the Western Parts of Jharkhand
Authors: Neeta Kumari, Gopal Pathak
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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination
Procedia PDF Downloads 53822311 Translanguaging In Preschools: New Evidence from Polish-English Bilingual Children
Authors: Judyta Pawliszko
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The study draws on the theoretical framework of translanguaging. It investigates translanguaging patterns and how meaning-making processes among bilingual children in preschool are affected by using two different languages, 8 months of observation and 200 hours of vocal recordings of children (3-6 years old) provide data on bilingual children’s linguistic repertoire why children translanguage, and how they achieve understanding with the strategic use of the two languages. The data gathered point to translanguaging as a practice that maximizes meaning-making processes among preschool bilingual children.Keywords: translanguaging, bilingualism, preschool, polish-english bilingual children
Procedia PDF Downloads 10022310 Towards a Framework for Embedded Weight Comparison Algorithm with Business Intelligence in the Plantation Domain
Authors: M. Pushparani, A. Sagaya
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Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.Keywords: embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems
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