Search results for: error information
2888 Place Recommendation Using Location-Based Services and Real-time Social Network Data
Authors: Kanda Runapongsa Saikaew, Patcharaporn Jiranuwattanawong, Patinya Taearak
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Currently, there is excessively growing information about places on Facebook, which is the largest social network but such information is not explicitly organized and ranked. Therefore users cannot exploit such data to recommend places conveniently and quickly. This paper proposes a Facebook application and an Android application that recommend places based on the number of check-ins of those places, the distance of those places from the current location, the number of people who like Facebook page of those places, and the number of talking about of those places. Related Facebook data is gathered via Facebook API requests. The experimental results of the developed applications show that the applications can recommend places and rank interesting places from the most to the least. We have found that the average satisfied score of the proposed Facebook application is 4.8 out of 5. The users’ satisfaction can increase by adding the app features that support personalization in terms of interests and preferences.
Keywords: Mobile computing, location-based services, recommendation system, social network analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17802887 Satisfying and Frustrating Aspects of ICT Teaching: A Comparison Based On Self-Efficacy
Authors: Deniz Deryakulu, Sener Buyukozturk, Sirin Karadeniz, Sinan Olkun
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The purpose of this study was to determine the most satisfying and frustrating aspects of ICT (Information and Communications Technologies) teaching in Turkish schools. Another aim was to compare these aspects based-on ICT teachers- selfefficacy. Participants were 119 ICT teachers from different geographical areas of Turkey. Participants were asked to list salient satisfying and frustrating aspects of ICT teaching, and to fill out the Self-Efficacy Scale for ICT Teachers. Results showed that the high self-efficacy teachers listed more positive and negative aspects of ICT teaching then did the low self-efficacy teachers. The satisfying aspects of ICT teaching were the dynamic nature of ICT subject, higher student interest, having opportunity to help other subject teachers, and lecturing in well-equipped labs, whereas the most frequently cited frustrating aspects of ICT teaching were ICT-related extra works of schools and colleagues, shortages of hardware and technical problems, indifferent students, insufficient teaching time, and the status of ICT subject in school curriculum. This information could be useful in redesigning ICT teachers- roles and responsibilities as well as job environment in schools.
Keywords: ICT teachers, frustrating aspects of ICT teaching, satisfying aspects of ICT teaching, teacher self-efficacy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17412886 Real-Time Land Use and Land Information System in Homagama Divisional Secretariat Division
Authors: Kumara Jayapathma J. H. M. S. S., Dampegama S. D. P. J.
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Lands are valuable & limited resource which constantly changes with the growth of the population. An efficient and good land management system is essential to avoid conflicts associated with lands. This paper aims to design the prototype model of a Mobile GIS Land use and Land Information System in real-time. Homagama Divisional Secretariat Division situated in the western province of Sri Lanka was selected as the study area. The prototype model was developed after reviewing related literature. The methodology was consisted of designing and modeling the prototype model into an application running on a mobile platform. The system architecture mainly consists of a Google mapping app for real-time updates with firebase support tools. Thereby, the method of implementation consists of front-end and back-end components. Software tools used in designing applications are Android Studio with JAVA based on GeoJSON File structure. Android Studio with JAVA in GeoJSON File Synchronize to Firebase was found to be the perfect mobile solution for continuously updating Land use and Land Information System (LIS) in real-time in the present scenario. The mobile-based land use and LIS developed in this study are multiple user applications catering to different hierarchy levels such as basic users, supervisory managers, and database administrators. The benefits of this mobile mapping application will help public sector field officers with non-GIS expertise to overcome the land use planning challenges with land use updated in real-time.
Keywords: Android, Firebase, GeoJSON, GIS, JAVA, JSON, LIS, mobile GIS, real-time, REST API.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5652885 Methods for Distinction of Cattle Using Supervised Learning
Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl
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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.
Keywords: Genetic data, Pinzgau cattle, supervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23182884 Sperm Identification Using Elliptic Model and Tail Detection
Authors: Vahid Reza Nafisi, Mohammad Hasan Moradi, Mohammad Hosain Nasr-Esfahani
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The conventional assessment of human semen is a highly subjective assessment, with considerable intra- and interlaboratory variability. Computer-Assisted Sperm Analysis (CASA) systems provide a rapid and automated assessment of the sperm characteristics, together with improved standardization and quality control. However, the outcome of CASA systems is sensitive to the method of experimentation. While conventional CASA systems use digital microscopes with phase-contrast accessories, producing higher contrast images, we have used raw semen samples (no staining materials) and a regular light microscope, with a digital camera directly attached to its eyepiece, to insure cost benefits and simple assembling of the system. However, since the accurate finding of sperms in the semen image is the first step in the examination and analysis of the semen, any error in this step can affect the outcome of the analysis. This article introduces and explains an algorithm for finding sperms in low contrast images: First, an image enhancement algorithm is applied to remove extra particles from the image. Then, the foreground particles (including sperms and round cells) are segmented form the background. Finally, based on certain features and criteria, sperms are separated from other cells.Keywords: Computer-Assisted Sperm Analysis (CASA), Sperm identification, Tail detection, Elliptic shape model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19282883 COVID_ICU_BERT: A Fine-tuned Language Model for COVID-19 Intensive Care Unit Clinical Notes
Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo
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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as physiological vital signs, images and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful to influence the judgement of clinical sentiment in ICU clinical notes. This paper presents two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of a clinical transformer model that can reliably predict clinical sentiment for notes of COVID patients in ICU. We train the model on clinical notes for COVID-19 patients, ones not previously seen by Bio_ClinicalBERT or Bio_Discharge_Summary_BERT. The model which was based on Bio_ClinicalBERT achieves higher predictive accuracy than the one based on Bio_Discharge_Summary_BERT (Acc 93.33%, AUC 0.98, and Precision 0.96). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and Precision 0.92).
Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2762882 Direct Growth Rates of the Information Model for Traffic at the Service of Sustainable Development of Tourism in Dubrovacko-Neretvanska County 2014-2020
Authors: V. Viduĉić, J. Žanić Mikuliĉić, M. Raĉić, K. Sladojević
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The research presented in this paper has been focused on analysing the impact of traffic on the sustainable development of tourism in Croatia's Dubrovacko-Neretvanska County by the year 2020, based on the figures and trends reported in 2014 and using the relevant variables that characterise the synergy of traffic and tourism in, speaking from the geographic viewpoint, the most problematic county in the Republic of Croatia. The basic hypothesis has been confirmed through scientifically obtained research results, through the quantification of the model's variables and the direct growth rates of the designed model. On the basis of scientific insights into the sustainable development of traffic and tourism in Dubrovacko- Neretvanska County, it is possible to propose a new information model for traffic at the service of the sustainable development of tourism in the County for the period 2014-2020.
Keywords: Environment protection, hotel industry, private sector, quantification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19872881 Using Data Mining Technique for Scholarship Disbursement
Authors: J. K. Alhassan, S. A. Lawal
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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.Keywords: Decision tree, classification, data mining, scholarship.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21572880 Digital Geomatics Trends for Production and Updating Topographic Map by Using Digital Generalization Procedures
Authors: O. Z. Jasim
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An accuracy digital map must satisfy the users for two main requirements, first, map must be visually readable and second, all the map elements must be in a good representation. These two requirements hold especially true for map generalization which aims at simplifying the representation of cartographic data. Different scales of maps are very important for any decision in any maps with different scales such as master plan and all the infrastructures maps in civil engineering. Cartographer cannot project the data onto a piece of paper, but he has to worry about its readability. The map layout of any geodatabase is very important, this layout is help to read, analyze or extract information from the map. There are many principles and guidelines of generalization that can be find in the cartographic literature. A manual reduction method for generalization depends on experience of map maker and therefore produces incompatible results. Digital generalization, rooted from conventional cartography, has become an increasing concern in both Geographic Information System (GIS) and mapping fields. This project is intended to review the state of the art of the new technology and help to understand the needs and plans for the implementation of digital generalization capability as well as increase the knowledge of production topographic maps.
Keywords: Cartography, digital generalization, mapping, GIS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12892879 Comparison of Hough Transform and Mean Shift Algorithm for Estimation of the Orientation Angle of Industrial Data Matrix Codes
Authors: Ion-Cosmin Dita, Vasile Gui, Franz Quint, Marius Otesteanu
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In automatic manufacturing and assembling of mechanical, electrical and electronic parts one needs to reliably identify the position of components and to extract the information of these components. Data Matrix Codes (DMC) are established by these days in many areas of industrial manufacturing thanks to their concentration of information on small spaces. In today’s usually order-related industry, where increased tracing requirements prevail, they offer further advantages over other identification systems. This underlines in an impressive way the necessity of a robust code reading system for detecting DMC on the components in factories. This paper compares two methods for estimating the angle of orientation of Data Matrix Codes: one method based on the Hough Transform and the other based on the Mean Shift Algorithm. We concentrate on Data Matrix Codes in industrial environment, punched, milled, lasered or etched on different materials in arbitrary orientation.
Keywords: Industrial data matrix code, Hough transform, mean shift.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13362878 Identifying Network Subgraph-Associated Essential Genes in Molecular Networks
Authors: Efendi Zaenudin, Chien-Hung Huang, Ka-Lok Ng
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Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.
Keywords: Biological molecular networks, essential genes, graph theory, network subgraphs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4952877 Confidence Intervals for the Coefficients of Variation with Bounded Parameters
Authors: Jeerapa Sappakitkamjorn, Sa-aat Niwitpong
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In many practical applications in various areas, such as engineering, science and social science, it is known that there exist bounds on the values of unknown parameters. For example, values of some measurements for controlling machines in an industrial process, weight or height of subjects, blood pressures of patients and retirement ages of public servants. When interval estimation is considered in a situation where the parameter to be estimated is bounded, it has been argued that the classical Neyman procedure for setting confidence intervals is unsatisfactory. This is due to the fact that the information regarding the restriction is simply ignored. It is, therefore, of significant interest to construct confidence intervals for the parameters that include the additional information on parameter values being bounded to enhance the accuracy of the interval estimation. Therefore in this paper, we propose a new confidence interval for the coefficient of variance where the population mean and standard deviation are bounded. The proposed interval is evaluated in terms of coverage probability and expected length via Monte Carlo simulation.
Keywords: Bounded parameters, coefficient of variation, confidence interval, Monte Carlo simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42272876 Relations of Progression in Cognitive Decline with Initial EEG Resting-State Functional Network in Mild Cognitive Impairment
Authors: Chia-Feng Lu, Yuh-Jen Wang, Yu-Te Wu, Sui-Hing Yan
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This study aimed at investigating whether the functional brain networks constructed using the initial EEG (obtained when patients first visited hospital) can be correlated with the progression of cognitive decline calculated as the changes of mini-mental state examination (MMSE) scores between the latest and initial examinations. We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions, and the network analysis based on graph theory to investigate the organization of functional networks in aMCI. Our finding suggested that higher integrated functional network with sufficient connection strengths, dense connection between local regions, and high network efficiency in processing information at the initial stage may result in a better prognosis of the subsequent cognitive functions for aMCI. In conclusion, the functional connectivity can be a useful biomarker to assist in prediction of cognitive declines in aMCI.
Keywords: Cognitive decline, functional connectivity, MCI, MMSE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24102875 The Impact of Information and Communication Technology in Education: Opportunities and Challenges
Authors: M. Nadeem, S. Nasir, K. A. Moazzam, R. Kashif
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The remarkable growth and evolution in information and communication technology (ICT) in the past few decades has transformed modern society in almost every aspect of life. The impact and application of ICT have been observed in almost all walks of life including science, arts, business, health, management, engineering, sports, and education. ICT in education is being used extensively for student learning, creativity, interaction, and knowledge sharing and as a valuable source of teaching instrument. Apart from the student’s perspective, it plays a vital role for teacher education, instructional methods and curriculum development. There is a significant difference in growth of ICT enabled education in developing countries compared to developed nations and according to research, this gap is widening. ICT gradually infiltrate in almost every aspect of life. It has a deep and profound impact on our social, economic, health, environment, development, work, learning, and education environments. ICT provides very effective and dominant tools for information and knowledge processing. It is firmly believed that the coming generation should be proficient and confident in the use of ICT to cope with the existing international standards. This is only possible if schools can provide basic ICT infrastructure to students and to develop an ICT-integrated curriculum which covers all aspects of learning and creativity in students. However, there is a digital divide and steps must be taken to reduce this digital divide considerably to have the profound impact of ICT in education all around the globe. This study is based on theoretical approach and an extensive literature review is being conducted to see the successful implementations of ICT integration in education and to identify technologies and models which have been used in education in developed countries. This paper deals with the modern applications of ICT in schools for both teachers and students to uplift the learning and creativity amongst the students. A brief history of technology in education is presented and discussed are some important ICT tools for both student and teacher’s perspective. Basic ICT-based infrastructure for academic institutions is presented. The overall conclusion leads to the positive impact of ICT in education by providing an interactive, collaborative and challenging environment to students and teachers for knowledge sharing, learning and critical thinking.Keywords: Information and communication technology, ICT, education, ICT infrastructure, teacher education.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38802874 Genetic Algorithms for Feature Generation in the Context of Audio Classification
Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes
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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.
Keywords: Feature generation, feature learning, genetic algorithm, music information retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10782873 Knowledge Representation and Inconsistency Reasoning of Class Diagram Maintenance in Big Data
Authors: Chi-Lun Liu
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Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.
Keywords: Knowledge representation, reasoning, ontology, class diagram, software engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10422872 The Integrated Management of Health Care Strategies and Differential Diagnosis by Expert System Technology: A Single-Dimensional Approach
Authors: A. B. Adehor, P. R. Burrell
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The Integrated Management of Child illnesses (IMCI) and the surveillance Health Information Systems (HIS) are related strategies that are designed to manage child illnesses and community practices of diseases. However, both strategies do not function well together because of classification incompatibilities and, as such, are difficult to use by health care personnel in rural areas where a majority of people lack the basic knowledge of interpreting disease classification from these methods. This paper discusses a single approach on how a stand-alone expert system can be used as a prompt diagnostic tool for all cases of illnesses presented. The system combines the action-oriented IMCI and the disease-oriented HIS approaches to diagnose malaria and typhoid fever in the rural areas of the Niger-delta region.
Keywords: Differential diagnosis, Health Information System(HIS), Integrated Management of Child Illnesses (IMCI), Malaria andTyphoid fever.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18682871 Allometric Models for Biomass Estimation in Savanna Woodland Area, Niger State, Nigeria
Authors: Abdullahi Jibrin, Aishetu Abdulkadir
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The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. F-test values for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.
Keywords: Allometriy, biomass, carbon stock, model, regression equation, woodland, inventory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27882870 Analysis of Lightweight Register Hardware Threat
Authors: Yang Luo, Beibei Wang
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In this paper, we present a design methodology of lightweight register transfer level (RTL) hardware threat implemented based on a MAX II FPGA platform. The dynamic power consumed by the toggling of the various bit of registers as well as the dynamic power consumed per unit of logic circuits were analyzed. The hardware threat was designed taking advantage of the differences in dynamic power consumed per unit of logic circuits to hide the transfer information. The experiment result shows that the register hardware threat was successfully implemented by using different dynamic power consumed per unit of logic circuits to hide the key information of DES encryption module. It needs more than 100000 sample curves to reduce the background noise by comparing the sample space when it completely meets the time alignment requirement. In additional, an external trigger signal is playing a very important role to detect the hardware threat in this experiment.
Keywords: Side-channel analysis, hardware threat, register transfer level, dynamic power.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9932869 Dynamic Fault Diagnosis for Semi-Batch Reactor under Closed-Loop Control via Independent Radial Basis Function Neural Network
Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm
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In this paper, a robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor, when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics, and using the weighted sum-squared prediction error as the residual. The Recursive Orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. Several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature, and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18352868 Filtering and Reconstruction System for Gray Forensic Images
Authors: Ahd Aljarf, Saad Amin
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Images are important source of information used as evidence during any investigation process. Their clarity and accuracy is essential and of the utmost importance for any investigation. Images are vulnerable to losing blocks and having noise added to them either after alteration or when the image was taken initially, therefore, having a high performance image processing system and it is implementation is very important in a forensic point of view. This paper focuses on improving the quality of the forensic images. For different reasons packets that store data can be affected, harmed or even lost because of noise. For example, sending the image through a wireless channel can cause loss of bits. These types of errors might give difficulties generally for the visual display quality of the forensic images. Two of the images problems: noise and losing blocks are covered. However, information which gets transmitted through any way of communication may suffer alteration from its original state or even lose important data due to the channel noise. Therefore, a developed system is introduced to improve the quality and clarity of the forensic images.
Keywords: Image Filtering, Image Reconstruction, Image Processing, Forensic Images.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22132867 Stock Price Forecast by Using Neuro-Fuzzy Inference System
Authors: Ebrahim Abbasi, Amir Abouec
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In this research, the researchers have managed to design a model to investigate the current trend of stock price of the "IRAN KHODRO corporation" at Tehran Stock Exchange by utilizing an Adaptive Neuro - Fuzzy Inference system. For the Longterm Period, a Neuro-Fuzzy with two Triangular membership functions and four independent Variables including trade volume, Dividend Per Share (DPS), Price to Earning Ratio (P/E), and also closing Price and Stock Price fluctuation as an dependent variable are selected as an optimal model. For the short-term Period, a neureo – fuzzy model with two triangular membership functions for the first quarter of a year, two trapezoidal membership functions for the Second quarter of a year, two Gaussian combination membership functions for the third quarter of a year and two trapezoidal membership functions for the fourth quarter of a year were selected as an optimal model for the stock price forecasting. In addition, three independent variables including trade volume, price to earning ratio, closing Stock Price and a dependent variable of stock price fluctuation were selected as an optimal model. The findings of the research demonstrate that the trend of stock price could be forecasted with the lower level of error.Keywords: Stock Price forecast, membership functions, Adaptive Neuro-Fuzzy Inference System, trade volume, P/E, DPS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26132866 Application of Advanced Remote Sensing Data in Mineral Exploration in the Vicinity of Heavy Dense Forest Cover Area of Jharkhand and Odisha State Mining Area
Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna
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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.
Keywords: Hyperion, hyperspectral, sensor, Landsat-8.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6222865 Momentum Accounting in Public Management: A Case Study in a Brazilian Navy-s Services Provider Military Organization
Authors: Rodrigo Barreiros Leal, Aracéli Cristina de Sousa Ferreira
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This study examines the possibility to apply the theory of multidimensional accounting (momentum accounting) in a Brazilian Navy-s Services Provider Military Organization (Organização Militar Prestadora de Serviços - OMPS). In general, the core of the said theory is the fact that Accounting does not recognize the inertia of transactions occurring in an entity, and that occur repeatedly in some cases, regardless of the implementation of new actions by its managers. The study evaluates the possibility of greater use of information recorded in the financial statements of the unit of analysis, within the strategic decisions of the organization. As a research strategy, we adopted the case study. The results infer that it is possible to use the theory in the context of a multidimensional OMPS, promoting useful information for decision-making and thereby contributing to the strengthening of the necessary alignment of its administration with the current desires of the Brazilian society.
Keywords: Multidimensional Accounting, Public Management, Decision Making.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28792864 Improving the Shunt Active Power Filter Performance Using Synchronous Reference Frame PI Based Controller with Anti-Windup Scheme
Authors: Consalva J. Msigwa, Beda J. Kundy, Bakari M. M. Mwinyiwiwa
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In this paper the reference current for Voltage Source Converter (VSC) of the Shunt Active Power Filter (SAPF) is generated using Synchronous Reference Frame method, incorporating the PI controller with anti-windup scheme. The proposed method improves the harmonic filtering by compensating the winding up phenomenon caused by the integral term of the PI controller. Using Reference Frame Transformation, the current is transformed from om a - b - c stationery frame to rotating 0 - d - q frame. Using the PI controller, the current in the 0 - d - q frame is controlled to get the desired reference signal. A controller with integral action combined with an actuator that becomes saturated can give some undesirable effects. If the control error is so large that the integrator saturates the actuator, the feedback path becomes ineffective because the actuator will remain saturated even if the process output changes. The integrator being an unstable system may then integrate to a very large value, the phenomenon known as integrator windup. Implementing the integrator anti-windup circuit turns off the integrator action when the actuator saturates, hence improving the performance of the SAPF and dynamically compensating harmonics in the power network. In this paper the system performance is examined with Shunt Active Power Filter simulation model.Keywords: Phase Locked Loop (PLL), Voltage SourceConverter (VSC), Shunt Active Power Filter (SAPF), PI, Pulse WidthModulation (PWM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15672863 Rapid Finite-Element Based Airport Pavement Moduli Solutions using Neural Networks
Authors: Kasthurirangan Gopalakrishnan, Marshall R. Thompson, Anshu Manik
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This paper describes the use of artificial neural networks (ANN) for predicting non-linear layer moduli of flexible airfield pavements subjected to new generation aircraft (NGA) loading, based on the deflection profiles obtained from Heavy Weight Deflectometer (HWD) test data. The HWD test is one of the most widely used tests for routinely assessing the structural integrity of airport pavements in a non-destructive manner. The elastic moduli of the individual pavement layers backcalculated from the HWD deflection profiles are effective indicators of layer condition and are used for estimating the pavement remaining life. HWD tests were periodically conducted at the Federal Aviation Administration-s (FAA-s) National Airport Pavement Test Facility (NAPTF) to monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test gear trafficking on the structural condition of flexible pavement sections. In this study, a multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD backcalculation function. The synthetic database generated using an advanced non-linear pavement finite-element program was used to train the ANN to overcome the limitations associated with conventional pavement moduli backcalculation. The changes in ANN-based backcalculated pavement moduli with trafficking were used to compare the relative severity effects of the aircraft landing gears on the NAPTF test pavements.Keywords: Airfield pavements, ANN, backcalculation, newgeneration aircraft
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21852862 Various Information Obtained from Acoustic Emissions Owing to Discharges in XLPE Cable
Authors: Tatsuya Sakoda, Yuta Nakamura, Junichiro Kitajima, Masaki Sugiura, Satoshi Kurihara, Kenji Baba, Koichiro Kaneko, Takayoshi Yarimitsu
Abstract:
An acoustic emission (AE) technique is useful for detection of partial discharges (PDs) at a joint and a terminal section of a cross-linked polyethylene (XLPE) cable. For AE technique, it is not difficult to detect a PD using AE sensors. However, it is difficult to grasp whether the detected AE signal is owing to a single discharge or not. Additionally, when an AE technique is applied at a terminal section of a XLPE cable in salt pollution district, for example, there is possibility of detection of AE signals owing to creeping discharges on the surface of electric power apparatus. In this study, we evaluated AE signals in order to grasp what kind of information we can get from detected AE signals. The results showed that envelop detection of AE signal and a period which some AE signals were continuously detected were good indexes for estimating state-of-discharge.Keywords: acoustic emission, creeping discharge, partial discharge, XLPE cable
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16442861 Users’ Information Disclosure Determinants in Social Networking Sites: A Systematic Literature Review
Authors: Wajdan Al Malwi, Karen Renaud, Lewis Mackenzie
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The privacy paradox describes a phenomenon whereby there is no connection between stated privacy concerns and privacy behaviours. We need to understand the underlying reasons for this paradox if we are to help users to preserve their privacy more effectively. In particular, the Social Networking System (SNS) domain offers a rich area of investigation due to the risks of unwise information disclosure decisions. Our study thus aims to untangle the complicated nature and underlying mechanisms of online privacy-related decisions in SNSs. In this paper, we report on the findings of a Systematic Literature Review (SLR) that revealed a number of factors that are likely to influence online privacy decisions. Our deductive analysis approach was informed by Communicative Privacy Management (CPM) theory. We uncovered a lack of clarity around privacy attitudes and their link to behaviours, which makes it challenging to design privacy-protecting SNS platforms and to craft legislation to ensure that users’ privacy is preserved.Keywords: Privacy paradox, self-disclosure, privacy attitude, privacy behaviour, social networking sites.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6212860 One-Class Support Vector Machines for Aerial Images Segmentation
Authors: Chih-Hung Wu, Chih-Chin Lai, Chun-Yen Chen, Yan-He Chen
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Interpretation of aerial images is an important task in various applications. Image segmentation can be viewed as the essential step for extracting information from aerial images. Among many developed segmentation methods, the technique of clustering has been extensively investigated and used. However, determining the number of clusters in an image is inherently a difficult problem, especially when a priori information on the aerial image is unavailable. This study proposes a support vector machine approach for clustering aerial images. Three cluster validity indices, distance-based index, Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative measures of the quality of clustering results. Comparisons on the effectiveness of these indices and various parameters settings on the proposed methods are conducted. Experimental results are provided to illustrate the feasibility of the proposed approach.Keywords: Aerial imaging, image segmentation, machine learning, support vector machine, cluster validity index
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19392859 Developing Online Bookstore to Facilitate Manual Process – UTP Case Study
Authors: Emelia Akashah P.A, Sharifah Nadiah S.A
Abstract:
Knowledge sharing enables the information or knowledge to be transmitted from one source to another. This paper demonstrates the needs of having the online book catalogue which can be used to facilitate disseminating information on textbook used in the university. This project is aimed to give access to the students and lecturers to the list of books in the bookstore and at the same time to allow book reviewing without having to visit the bookstore physically. Research is carried out according to the boundaries which accounts to current process of new book purchasing, current system used by the bookstore and current process the lecturers go through for reviewing textbooks. The questionnaire is used to gather the requirements and it is distributed to 100 students and 40 lecturers. This project has enabled the improvement of a manual process to be carried out automatically, through a web based platform. It is shown based on the user acceptance survey carried out that target groups found that this web service is feasible to be implemented in Universiti Teknologi PETRONAS (UTP), and they have shown positive signs of interest in utilizing it in the future.Keywords: bookstore, knowledge sharing, online bookcatalogue, textbook
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4250