Search results for: data validation
6879 Development of Cooling Load Demand Program for Building in Malaysia
Authors: Zamri Noranai, Dayang Siti Zainab Abang Bujang, Rosli Asmawi, Hamidon Salleh, Mohammad Zainal Md Yusof
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Air conditioning is mainly to be used as human comfort medium. It has been use more often in country in which the daily temperatures are high. In scientific, air conditioning is defined as a process of controlling the moisture, cooling, heating and cleaning air. Without proper estimation of cooling load, big amount of waste energy been used because of unsuitable of air conditioning system are not considering to overcoming heat gains from surrounding. This is due to the size of the room is too big and the air conditioning has to use more energy to cool the room and the air conditioning is too small for the room. The studies are basically to develop a program to calculate cooling load. Through this study it is easy to calculate cooling load estimation. Furthermore it-s help to compare the cooling load estimation by hourly and yearly. Base on the last study that been done, the developed software are not user-friendly. For individual without proper knowledge of calculating cooling load estimation might be problem. Easy excess and user-friendly should be the main objective to design something. This program will allow cooling load able be estimate by any users rather than estimation by using rule of thumb. Several of limitation of case study is judged to sure it-s meeting to Malaysia building specification. Finally validation is done by comparison manual calculation and by developed program.Keywords: Building, Energy and Coaling Load
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29466878 Using Data from Foursquare Web Service to Represent the Commercial Activity of a City
Authors: Taras Agryzkov, Almudena Nolasco-Cirugeda, Jos´e L. Oliver, Leticia Serrano-Estrada, Leandro Tortosa, Jos´e F. Vicent
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This paper aims to represent the commercial activity of a city taking as source data the social network Foursquare. The city of Murcia is selected as case study, and the location-based social network Foursquare is the main source of information. After carrying out a reorganisation of the user-generated data extracted from Foursquare, it is possible to graphically display on a map the various city spaces and venues especially those related to commercial, food and entertainment sector businesses. The obtained visualisation provides information about activity patterns in the city of Murcia according to the people‘s interests and preferences and, moreover, interesting facts about certain characteristics of the town itself.
Keywords: Social networks, Foursquare, spatial analysis, data visualization, geocomputation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26786877 Long-Range Dependence of Financial Time Series Data
Authors: Chatchai Pesee
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This paper examines long-range dependence or longmemory of financial time series on the exchange rate data by the fractional Brownian motion (fBm). The principle of spectral density function in Section 2 is used to find the range of Hurst parameter (H) of the fBm. If 0< H <1/2, then it has a short-range dependence (SRD). It simulates long-memory or long-range dependence (LRD) if 1/2< H <1. The curve of exchange rate data is fBm because of the specific appearance of the Hurst parameter (H). Furthermore, some of the definitions of the fBm, long-range dependence and selfsimilarity are reviewed in Section II as well. Our results indicate that there exists a long-memory or a long-range dependence (LRD) for the exchange rate data in section III. Long-range dependence of the exchange rate data and estimation of the Hurst parameter (H) are discussed in Section IV, while a conclusion is discussed in Section V.Keywords: Fractional Brownian motion, long-rangedependence, memory, short-range dependence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18846876 Meta Random Forests
Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti
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Leo Breimans Random Forests (RF) is a recent development in tree based classifiers and quickly proven to be one of the most important algorithms in the machine learning literature. It has shown robust and improved results of classifications on standard data sets. Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques to the random forests. We experiment the working of the ensembles of random forests on the standard data sets available in UCI data sets. We compare the original random forest algorithm with their ensemble counterparts and discuss the results.Keywords: Random Forests [RF], ensembles, UCI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27126875 A Cognitive Measurement of Complexity and Comprehension for Object-Oriented Code
Authors: Amit Kumar Jakhar, Kumar Rajnish
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Inherited complexity is one of the difficult tasks in software engineering field. Further, it is said that there is no physical laws or standard guidelines suit for designing different types of software. Hence, to make the software engineering as a matured engineering discipline like others, it is necessary that it has its own theoretical frameworks and laws. Software designing and development is a human effort which takes a lot of time and considers various parameters for successful completion of the software. The cognitive informatics plays an important role for understanding the essential characteristics of the software. The aim of this work is to consider the fundamental characteristics of the source code of Object-Oriented software i.e. complexity and understandability. The complexity of the programs is analyzed with the help of extracted important attributes of the source code, which is further utilized to evaluate the understandability factor. The aforementioned characteristics are analyzed on the basis of 16 C++ programs by distributing them to forty MCA students. They all tried to understand the source code of the given program and mean time is taken as the actual time needed to understand the program. For validation of this work, Briand’s framework is used and the presented metric is also evaluated comparatively with existing metric which proves its robustness.
Keywords: Software metrics, object-oriented, complexity, cognitive weight, understandability, basic control structures.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11236874 Time Series Regression with Meta-Clusters
Authors: Monika Chuchro
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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain subgroups of time series data with normal distribution from the inflow into wastewater treatment plant data, composed of several groups differing by mean value. Two simple algorithms, K-mean and EM, were chosen as a clustering method. The Rand index was used to measure the similarity. After simple meta-clustering, a regression model was performed for each subgroups. The final model was a sum of the subgroups models. The quality of the obtained model was compared with the regression model made using the same explanatory variables, but with no clustering of data. Results were compared using determination coefficient (R2), measure of prediction accuracy- mean absolute percentage error (MAPE) and comparison on a linear chart. Preliminary results allow us to foresee the potential of the presented technique.
Keywords: Clustering, Data analysis, Data mining, Predictive models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19516873 Studies on Determination of the Optimum Distance Between the Tmotes for Optimum Data Transfer in a Network with WLL Capability
Authors: N C Santhosh Kumar, N K Kishore
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Using mini modules of Tmotes, it is possible to automate a small personal area network. This idea can be extended to large networks too by implementing multi-hop routing. Linking the various Tmotes using Programming languages like Nesc, Java and having transmitter and receiver sections, a network can be monitored. It is foreseen that, depending on the application, a long range at a low data transfer rate or average throughput may be an acceptable trade-off. To reduce the overall costs involved, an optimum number of Tmotes to be used under various conditions (Indoor/Outdoor) is to be deduced. By analyzing the data rates or throughputs at various locations of Tmotes, it is possible to deduce an optimal number of Tmotes for a specific network. This paper deals with the determination of optimum distances to reduce the cost and increase the reliability of the entire sensor network with Wireless Local Loop (WLL) capability.
Keywords: Average throughput, data rate, multi-hop routing, optimum data transfer, throughput, Tmotes, wireless local loop.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13676872 Unified Structured Process for Health Analytics
Authors: Supunmali Ahangama, Danny Chiang Choon Poo
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Health analytics (HA) is used in healthcare systems for effective decision making, management and planning of healthcare and related activities. However, user resistances, unique position of medical data content and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. Success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose a HA process model with features from rational unified process (RUP) model and agile methodology.
Keywords: Agile methodology, health analytics, unified process model, UML.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23306871 Process Parameter Optimization in Resistance Spot Welding of Dissimilar Thickness Materials
Authors: Pradeep M., N. S. Mahesh, Raja Hussain
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Resistance spot welding (RSW) has been used widely to join sheet metals. It has been a challenge to get required weld quality in spot welding of dissimilar thickness materials. Weld parameters are not generally available in standards for thickness beyond 4mm. This paper presents the welding process design and parameter optimization of RSW used in joining of low carbon steel sheet of thickness 0.8 mm and metal strips of cross section 10 x 5mm for electrical motor applications. Taguchi quality design was adopted for weld current and time optimization using L9 orthogonal array. Optimum process parameters (current- 3.5kA and time- 10 cycles) were obtained from the Taguchi analysis and shear test results. Confirmation experiment result revealed that the weld quality was within acceptable interval. Further, numerical simulation of RSW process was carried out with selected weld parameters to quantify the temperature at faying surface and check for formation of appropriate nugget. The nugget geometry measured after peel test and predicted from numerical validation method were similar and in accordance with the standards.
Keywords: Resistance spot welding, dissimilar thickness, weld parameters, Taguchi method, numerical modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 51896870 Passive Flow Control in Twin Air-Intakes
Authors: Akshoy R. Paul, Pritanshu Ranjan, Ravi R. Upadhyay, Anuj Jain
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Aircraft propulsion systems often use Y-shaped subsonic diffusing ducts as twin air-intakes to supply the ambient air into the engine compressor for thrust generation. Due to space constraint, the diffusers need to be curved, which causes severe flow non-uniformity at the engine face. The present study attempt to control flow in a mild-curved Y-duct diffuser using trapezoidalshaped vortex generators (VG) attached on either both the sidewalls or top and bottom walls of the diffuser at the inflexion plane. A commercial computational fluid dynamics (CFD) code is modified and is used to simulate the effects of SVG in flow of a Y-duct diffuser. A few experiments are conducted for CFD code validation, while the rest are done computationally. The best combination of Yduct diffuser is found with VG-2 arranged in co-rotating sequence and attached to both the sidewalls, which ensures highest static pressure recovery, lowest total pressure loss, minimum flow distortion and less flow separation in Y-duct diffuser. The decrease in VG height while attached to top and bottom walls further improves axial flow uniformity at the diffuser outlet by a great margin as compared to the bare duct.Keywords: Twin air-intake, Vortex generator (VG), Turbulence model, Pressure recovery, Distortion coefficient
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21316869 The Classification Model for Hard Disk Drive Functional Tests under Sparse Data Conditions
Authors: S. Pattanapairoj, D. Chetchotsak
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This paper proposed classification models that would be used as a proxy for hard disk drive (HDD) functional test equitant which required approximately more than two weeks to perform the HDD status classification in either “Pass" or “Fail". These models were constructed by using committee network which consisted of a number of single neural networks. This paper also included the method to solve the problem of sparseness data in failed part, which was called “enforce learning method". Our results reveal that the constructed classification models with the proposed method could perform well in the sparse data conditions and thus the models, which used a few seconds for HDD classification, could be used to substitute the HDD functional tests.Keywords: Sparse data, Classifications, Committee network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17366868 Accurate Position Electromagnetic Sensor Using Data Acquisition System
Authors: Z. Ezzouine, A. Nakheli
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This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.
Keywords: Electromagnetic sensor, data acquisition, accurately, position measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9616867 Optimization of Element Type for FE Model and Verification of Analyses with Physical Tests
Authors: M. Tufekci, C. Guven
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In Automotive Industry, sliding door systems that are also used as body closures are safety members. Extreme product tests are realized to prevent failures in design process, but these tests realized experimentally result in high costs. Finite element analysis is an effective tool used for design process. These analyses are used before production of prototype for validation of design according to customer requirement. In result of this, substantial amount of time and cost is saved. Finite element model is created for geometries that are designed in 3D CAD programs. Different element types as bar, shell and solid, can be used for creating mesh model. Cheaper model can be created by selection of element type, but combination of element type that was used in model, number and geometry of element and degrees of freedom affects the analysis result. Sliding door system is a good example which used these methods for this study. Structural analysis was realized for sliding door mechanism by using FE models. As well, physical tests that have same boundary conditions with FE models were realized. Comparison study for these element types, were done regarding test and analyses results then optimum combination was achieved.Keywords: Finite Element Analysis, Sliding Door Mechanism, Element Type, Structural Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19656866 Calculus Logarithmic Function for Image Encryption
Authors: Adil AL-Rammahi
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When we prefer to make the data secure from various attacks and fore integrity of data, we must encrypt the data before it is transmitted or stored. This paper introduces a new effective and lossless image encryption algorithm using a natural logarithmic function. The new algorithm encrypts an image through a three stage process. In the first stage, a reference natural logarithmic function is generated as the foundation for the encryption image. The image numeral matrix is then analyzed to five integer numbers, and then the numbers’ positions are transformed to matrices. The advantages of this method is useful for efficiently encrypting a variety of digital images, such as binary images, gray images, and RGB images without any quality loss. The principles of the presented scheme could be applied to provide complexity and then security for a variety of data systems such as image and others.
Keywords: Linear Systems, Image Encryption, Calculus.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24016865 Intelligent BRT in Tehran
Authors: P. Parvizi, S. Mohammadi
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an intelligent BRT system is necessary when communities looking for new ways to use high capacity rapid transit at a reduced cost.This paper will describe the intelligent control system that works with Datacenter. With the help of GPS system, the data center can monitor the situation of each bus and bus station. Through RFID technology, bus station and traffic light can transfer data with bus and by Wimax communication technology all of parts can talk together; data center learns all information about the location of bus, the arrival of bus in each station and the number of passengers in station and bus.Finally, the paper presents the case study of those theories in Tehran BRT.Keywords: TehranBRT, RFID, Intelligent Transportation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24516864 Spread Spectrum Image Watermarking for Secured Multimedia Data Communication
Authors: Tirtha S. Das, Ayan K. Sau, Subir K. Sarkar
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Digital watermarking is a way to provide the facility of secure multimedia data communication besides its copyright protection approach. The Spread Spectrum modulation principle is widely used in digital watermarking to satisfy the robustness of multimedia signals against various signal-processing operations. Several SS watermarking algorithms have been proposed for multimedia signals but very few works have discussed on the issues responsible for secure data communication and its robustness improvement. The current paper has critically analyzed few such factors namely properties of spreading codes, proper signal decomposition suitable for data embedding, security provided by the key, successive bit cancellation method applied at decoder which have greater impact on the detection reliability, secure communication of significant signal under camouflage of insignificant signals etc. Based on the analysis, robust SS watermarking scheme for secure data communication is proposed in wavelet domain and improvement in secure communication and robustness performance is reported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data.
Keywords: Spread spectrum modulation, spreading code, signaldecomposition, security, successive bit cancellation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27816863 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 13366862 An Intelligent Human-Computer Interaction System for Decision Support
Authors: Chee Siong Teh, Chee Peng Lim
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This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.
Keywords: Interactive evolutionary computation, multivariate data projection, pattern classification, topographic map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14546861 Implementation of Security Algorithms for u-Health Monitoring System
Authors: Jiho Park, Yong-Gyu Lee, Gilwon Yoon
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Data security in u-Health system can be an important issue because wireless network is vulnerable to hacking. However, it is not easy to implement a proper security algorithm in an embedded u-health monitoring because of hardware constraints such as low performance, power consumption and limited memory size and etc. To secure data that contain personal and biosignal information, we implemented several security algorithms such as Blowfish, data encryption standard (DES), advanced encryption standard (AES) and Rivest Cipher 4 (RC4) for our u-Health monitoring system and the results were successful. Under the same experimental conditions, we compared these algorithms. RC4 had the fastest execution time. Memory usage was the most efficient for DES. However, considering performance and safety capability, however, we concluded that AES was the most appropriate algorithm for a personal u-Health monitoring system.Keywords: biosignal, data encryption, security measures, u-health
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21306860 A Symbol by Symbol Clustering Based Blind Equalizer
Authors: Kristina Georgoulakis
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A new blind symbol by symbol equalizer is proposed. The operation of the proposed equalizer is based on the geometric properties of the two dimensional data constellation. An unsupervised clustering technique is used to locate the clusters formed by the received data. The symmetric properties of the clusters labels are subsequently utilized in order to label the clusters. Following this step, the received data are compared to clusters and decisions are made on a symbol by symbol basis, by assigning to each data the label of the nearest cluster. The operation of the equalizer is investigated both in linear and nonlinear channels. The performance of the proposed equalizer is compared to the performance of a CMAbased blind equalizer.Keywords: Blind equalization, channel equalization, cluster based equalisers
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14356859 Attention Based Fully Convolutional Neural Network for Simultaneous Detection and Segmentation of Optic Disc in Retinal Fundus Images
Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara
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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.Keywords: Ocular diseases, retinal fundus image, optic disc detection and segmentation, fully convolutional network, overlap measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7816858 Zero Inflated Models for Overdispersed Count Data
Authors: Y. N. Phang, E. F. Loh
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The zero inflated models are usually used in modeling count data with excess zeros where the existence of the excess zeros could be structural zeros or zeros which occur by chance. These type of data are commonly found in various disciplines such as finance, insurance, biomedical, econometrical, ecology, and health sciences which involve sex and health dental epidemiology. The most popular zero inflated models used by many researchers are zero inflated Poisson and zero inflated negative binomial models. In addition, zero inflated generalized Poisson and zero inflated double Poisson models are also discussed and found in some literature. Recently zero inflated inverse trinomial model and zero inflated strict arcsine models are advocated and proven to serve as alternative models in modeling overdispersed count data caused by excessive zeros and unobserved heterogeneity. The purpose of this paper is to review some related literature and provide a variety of examples from different disciplines in the application of zero inflated models. Different model selection methods used in model comparison are discussed.
Keywords: Overdispersed count data, model selection methods, likelihood ratio, AIC, BIC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 45326857 Formalizing a Procedure for Generating Uncertain Resource Availability Assumptions Based On Real Time Logistic Data Capturing with Auto-ID Systems for Reactive Scheduling
Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König
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As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focusses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.
Keywords: Auto-ID, Construction Logistic, Fuzzy, Monitoring, RFID, Scheduling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17786856 Nuclear Data Evaluation for 217Po
Authors: Sherif S. Nafee, Amir K. Al-Ramady, Salem S. Shaheen
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Evaluated nuclear decay data for the 217Po nuclide is presented in the present work. These data include recommended values for the half-life T1/2, α-, β-- and γ-ray emission energies and probabilities. Decay data from 221Rn α and 217Bi β—decays are presented. Q(α) has been updated based on the recent published work of the Atomic Mass Evaluation AME2012. In addition, the logft values were calculated using the Logft program from the ENSDF evaluation package. Moreover, the total internal conversion electrons and the K-shell to L-shell and L-shell to M-shell and to N-shell conversion electrons ratios K/L, L/M and L/N have been calculated using Bricc program. Meanwhile, recommendation values or the multi-polarities have been assigned based on recently measurement yield a better intensity balance at the 254 keV and 264 keV gamma transitions.
Keywords: Atomic Mass Evaluation, Nuclear Data Evaluation, Total Electron Conversion Electrons.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22556855 Detection of Keypoint in Press-Fit Curve Based on Convolutional Neural Network
Authors: Shoujia Fang, Guoqing Ding, Xin Chen
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The quality of press-fit assembly is closely related to reliability and safety of product. The paper proposed a keypoint detection method based on convolutional neural network to improve the accuracy of keypoint detection in press-fit curve. It would provide an auxiliary basis for judging quality of press-fit assembly. The press-fit curve is a curve of press-fit force and displacement. Both force data and distance data are time-series data. Therefore, one-dimensional convolutional neural network is used to process the press-fit curve. After the obtained press-fit data is filtered, the multi-layer one-dimensional convolutional neural network is used to perform the automatic learning of press-fit curve features, and then sent to the multi-layer perceptron to finally output keypoint of the curve. We used the data of press-fit assembly equipment in the actual production process to train CNN model, and we used different data from the same equipment to evaluate the performance of detection. Compared with the existing research result, the performance of detection was significantly improved. This method can provide a reliable basis for the judgment of press-fit quality.Keywords: Keypoint detection, curve feature, convolutional neural network, press-fit assembly.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9416854 Proposal to Increase the Efficiency, Reliability and Safety of the Centre of Data Collection Management and Their Evaluation Using Cluster Solutions
Authors: Martin Juhas, Bohuslava Juhasova, Igor Halenar, Andrej Elias
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This article deals with the possibility of increasing efficiency, reliability and safety of the system for teledosimetric data collection management and their evaluation as a part of complex study for activity “Research of data collection, their measurement and evaluation with mobile and autonomous units” within project “Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants”. Possible weaknesses in existing system are identified. A study of available cluster solutions with possibility of their deploying to analysed system is presented
Keywords: Teledosimetric data, efficiency, reliability, safety, cluster solution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15586853 Clustering Categorical Data Using Hierarchies (CLUCDUH)
Authors: Gökhan Silahtaroğlu
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Clustering large populations is an important problem when the data contain noise and different shapes. A good clustering algorithm or approach should be efficient enough to detect clusters sensitively. Besides space complexity, time complexity also gains importance as the size grows. Using hierarchies we developed a new algorithm to split attributes according to the values they have and choosing the dimension for splitting so as to divide the database roughly into equal parts as much as possible. At each node we calculate some certain descriptive statistical features of the data which reside and by pruning we generate the natural clusters with a complexity of O(n).Keywords: Clustering, tree, split, pruning, entropy, gini.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15566852 Analysis of Users’ Behavior on Book Loan Log Based On Association Rule Mining
Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong
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This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, Apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.
Keywords: Behavior, data mining technique, Apriori algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23066851 Data Integrity: Challenges in Health Information Systems in South Africa
Authors: T. Thulare, M. Herselman, A. Botha
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Poor system use, including inappropriate design of health information systems, causes difficulties in communication with patients and increased time spent by healthcare professionals in recording the necessary health information for medical records. System features like pop-up reminders, complex menus, and poor user interfaces can make medical records far more time consuming than paper cards as well as affect decision-making processes. Although errors associated with health information and their real and likely effect on the quality of care and patient safety have been documented for many years, more research is needed to measure the occurrence of these errors and determine the causes to implement solutions. Therefore, the purpose of this paper is to identify data integrity challenges in hospital information systems through a scoping review and based on the results provide recommendations on how to manage these. Only 34 papers were found to be most suitable out of 297 publications initially identified in the field. The results indicated that human and computerized systems are the most common challenges associated with data integrity and factors such as policy, environment, health workforce, and lack of awareness attribute to these challenges but if measures are taken the data integrity challenges can be managed.
Keywords: Data integrity, data integrity challenges, hospital information systems, South Africa.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13786850 Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks
Authors: Sean Paulsen, Michael Casey
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In this work, we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.
Keywords: Transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 153