Search results for: data safety.
5586 Digital Twin of Real Electrical Distribution System with Real Time Recursive Load Flow Calculation and State Estimation
Authors: Anosh Arshad Sundhu, Francesco Giordano, Giacomo Della Croce, Maurizio Arnone
Abstract:
Digital Twin (DT) is a technology that generates a virtual representation of a physical system or process, enabling real-time monitoring, analysis, and simulation. DT of an Electrical Distribution System (EDS) can perform online analysis by integrating the static and real-time data in order to show the current grid status and predictions about the future status to the Distribution System Operator (DSO), producers and consumers. DT technology for EDS also offers the opportunity to DSO to test hypothetical scenarios. This paper discusses the development of a DT of an EDS by Smart Grid Controller (SGC) application, which is developed using open-source libraries and languages. The developed application can be integrated with Supervisory Control and Data Acquisition System (SCADA) of any EDS for creating the DT. The paper shows the performance of developed tools inside the application, tested on real EDS for grid observability, Smart Recursive Load Flow (SRLF) calculation and state estimation of loads in MV feeders.
Keywords: Digital Twin, Distribution System Operator, Electrical Distribution System, Smart Grid Controller, Supervisory Control and Data Acquisition System, Smart Recursive Load Flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2145585 Estimation of Asphalt Pavement Surfaces Using Image Analysis Technique
Authors: Mohammad A. Khasawneh
Abstract:
Asphalt concrete pavements gradually lose their skid resistance causing safety problems especially under wet conditions and high driving speeds. In order to enact the actual field polishing and wearing process of asphalt pavement surfaces in a laboratory setting, several laboratory-scale accelerated polishing devices were developed by different agencies. To mimic the actual process, friction and texture measuring devices are needed to quantify surface deterioration at different polishing intervals that reflect different stages of the pavement life. The test could still be considered lengthy and to some extent labor-intensive. Therefore, there is a need to come up with another method that can assist in investigating the bituminous pavement surface characteristics in a practical and time-efficient test procedure.
The purpose of this paper is to utilize a well-developed image analysis technique to characterize asphalt pavement surfaces without the need to use conventional friction and texture measuring devices in an attempt to shorten and simplify the polishing procedure in the lab.
Promising findings showed the possibility of using image analysis in lieu of the labor-sensitive-variable-in-nature friction and texture measurements. It was found that the exposed aggregate surface area of asphalt specimens made from limestone and gravel aggregates produced solid evidence of the validity of this method in describing asphalt pavement surfaces. Image analysis results correlated well with the British Pendulum Numbers (BPN), Polish Values (PV) and Mean Texture Depth (MTD) values.
Keywords: Friction, Image Analysis, Polishing, Statistical Analysis, Texture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25465584 Assessment and Uncertainty Analysis of ROSA/LSTF Test on Pressurized Water Reactor 1.9% Vessel Upper Head Small-Break Loss-of-Coolant Accident
Authors: Takeshi Takeda
Abstract:
An experiment utilizing the ROSA/LSTF (rig of safety assessment/large-scale test facility) simulated a 1.9% vessel upper head small-break loss-of-coolant accident with an accident management (AM) measure under the total failure of high-pressure injection system of emergency core cooling system in a pressurized water reactor. Steam generator (SG) secondary-side depressurization on the AM measure was started by fully opening relief valves in both SGs when the maximum core exit temperature rose to 623 K. A large increase took place in the cladding surface temperature of simulated fuel rods on account of a late and slow response of core exit thermocouples during core boil-off. The author analyzed the LSTF test by reference to the matrix of an integral effect test for the validation of a thermal-hydraulic system code. Problems remained in predicting the primary coolant distribution and the core exit temperature with the RELAP5/MOD3.3 code. The uncertainty analysis results of the RELAP5 code confirmed that the sample size with respect to the order statistics influences the value of peak cladding temperature with a 95% probability at a 95% confidence level, and the Spearman’s rank correlation coefficient.
Keywords: LSTF, LOCA, uncertainty analysis, RELAP5.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7085583 Parametric Analysis on Information Technology Adoption and Organizational Efficiency in Northern Nigeria
Authors: A. Y. Dutse, S. I. Ningi
Abstract:
The adoption and diffusion of Information Technology (IT) is one of the fastest growing trends in organizations operating within Nigeria’s economy. Public and private organizations make huge capital investments in an attempt acquire and adopt the state-of-the-art IT for improving operational efficiency. In this study the level of IT adoption is considered the primary driver of efficiency witnessed by organizations. The research gathered data on the intensity of IT usage, and resultant efficiency increase in the organizations’ operations. The data was analyzed using multiple regression analysis and reveals that high level of IT usage has enhance efficiency of private and public organizations in Northern part of Nigeria with organizations having strategic intent on IT adoption indicating higher efficiency gains.
Keywords: IT Adoption, Nigeria, Organizational efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13615582 Mathematical Study for Traffic Flow and Traffic Density in Kigali Roads
Authors: Kayijuka Idrissa
Abstract:
This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.
Keywords: Statistical methods, Poisson distribution, car moving techniques, traffic flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18055581 Grid-based Supervised Clustering - GBSC
Authors: Pornpimol Bungkomkhun, Surapong Auwatanamongkol
Abstract:
This paper presents a supervised clustering algorithm, namely Grid-Based Supervised Clustering (GBSC), which is able to identify clusters of any shapes and sizes without presuming any canonical form for data distribution. The GBSC needs no prespecified number of clusters, is insensitive to the order of the input data objects, and is capable of handling outliers. Built on the combination of grid-based clustering and density-based clustering, under the assistance of the downward closure property of density used in bottom-up subspace clustering, the GBSC can notably reduce its search space to avoid the memory confinement situation during its execution. On two-dimension synthetic datasets, the GBSC can identify clusters with different shapes and sizes correctly. The GBSC also outperforms other five supervised clustering algorithms when the experiments are performed on some UCI datasets.Keywords: supervised clustering, grid-based clustering, subspace clustering
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15975580 Motor Gear Fault Diagnosis by Current, Noise and Vibration on AC Machine Considering Environment
Authors: Sun-Ki Hong, Ki-Seok Kim, Yong-Ho Cho
Abstract:
Lots of motors have been being used in industry. Therefore many researchers have studied about the failure diagnosis of motors. In this paper, the effect of measuring environment for diagnosis of gear fault connected to a motor shaft is studied. The fault diagnosis is executed through the comparison of normal gear and abnormal gear. The measured FFT data are compared with the normal data and analyzed for q-axis current, noise and vibration. For bad and good environment, the diagnosis results are compared. From these, it is shown that the bad measuring environment may not be able to detect exactly the motor gear fault. Therefore it is emphasized that the measuring environment should be carefully prepared.Keywords: Motor fault, Diagnosis, FFT, Vibration, Noise, q-axis current, measuring environment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24995579 SeCloudBPMN: A Lightweight Extension for BPMN Considering Security Threats in the Cloud
Authors: Somayeh Sobati Moghadam
Abstract:
Business processes are crucial for organizations and help businesses to evaluate and optimize their performance and processes against current and future-state business goals. Outsourcing business processes to the cloud becomes popular due to a wide varsity of benefits and cost-saving. However, cloud outsourcing raises enterprise data security concerns, which must be incorporated in Business Process Model and Notation (BPMN). This paper, presents SeCloudBPMN, a lightweight extension for BPMN which extends the BPMN to explicitly support the security threats in the cloud as an outsourcing environment. SeCloudBPMN helps business’s security experts to outsource business processes to the cloud considering different threats from inside and outside the cloud. In this way, appropriate security countermeasures could be considered to preserve data security in business processes outsourcing to the cloud.Keywords: BPMN, security threats, cloud computing, graphical representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7675578 Non-Parametric, Unconditional Quantile Estimation of Efficiency in Microfinance Institutions
Authors: Komlan Sedzro
Abstract:
We apply the non-parametric, unconditional, hyperbolic order-α quantile estimator to appraise the relative efficiency of Microfinance Institutions in Africa in terms of outreach. Our purpose is to verify if these institutions, which must constantly try to strike a compromise between their social role and financial sustainability are operationally efficient. Using data on African MFIs extracted from the Microfinance Information eXchange (MIX) database and covering the 2004 to 2006 periods, we find that more efficient MFIs are also the most profitable. This result is in line with the view that social performance is not in contradiction with the pursuit of excellent financial performance. Our results also show that large MFIs in terms of asset and those charging the highest fees are not necessarily the most efficient.Keywords: Data envelopment analysis, microfinance institutions, quantile estimation of efficiency, social and financial performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16695577 Fuel Economy and Stability Enhancement of the Hybrid Vehicles by Using Electrical Machines on Non-Driven Wheels
Authors: P. Naderi, S.M.T. Bathaee, R. Hoseinnezhad, R. Chini
Abstract:
Using electrical machine in conventional vehicles, also called hybrid vehicles, has become a promising control scheme that enables some manners for fuel economy and driver assist for better stability. In this paper, vehicle stability control, fuel economy and Driving/Regeneration braking for a 4WD hybrid vehicle is investigated by using an electrical machine on each non-driven wheels. In front wheels driven vehicles, fuel economy and regenerative braking can be obtained by summing torques applied on rear wheels. On the other hand, unequal torques applied to rear wheels provides enhanced safety and path correction in steering. In this paper, a model with fourteen degrees of freedom is considered for vehicle body, tires and, suspension systems. Thereafter, powertrain subsystems are modeled. Considering an electrical machine on each rear wheel, a fuzzy controller is designed for each driving, braking, and stability conditions. Another fuzzy controller recognizes the vehicle requirements between the driving/regeneration and stability modes. Intelligent vehicle control to multi objective operation and forward simulation are the paper advantages. For reaching to these aims, power management control and yaw moment control will be done by three fuzzy controllers. Also, the above mentioned goals are weighted by another fuzzy sub-controller base on vehicle dynamic. Finally, Simulations performed in MATLAB/SIMULINK environment show that the proposed structure can enhance the vehicle performance in different modes effectively.
Keywords: Hybrid, pitch, roll, regeneration, yaw.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18605576 A Comparative Study on the Dimensional Error of 3D CAD Model and SLS RP Model for Reconstruction of Cranial Defect
Authors: L. Siva Rama Krishna, Sriram Venkatesh, M. Sastish Kumar, M. Uma Maheswara Chary
Abstract:
Rapid Prototyping (RP) is a technology that produces models and prototype parts from 3D CAD model data, CT/MRI scan data, and model data created from 3D object digitizing systems. There are several RP process like Stereolithography (SLA), Solid Ground Curing (SGC), Selective Laser Sintering (SLS), Fused Deposition Modeling (FDM), 3D Printing (3DP) among them SLS and FDM RP processes are used to fabricate pattern of custom cranial implant. RP technology is useful in engineering and biomedical application. This is helpful in engineering for product design, tooling and manufacture etc. RP biomedical applications are design and development of medical devices, instruments, prosthetics and implantation; it is also helpful in planning complex surgical operation. The traditional approach limits the full appreciation of various bony structure movements and therefore the custom implants produced are difficult to measure the anatomy of parts and analyze the changes in facial appearances accurately. Cranioplasty surgery is a surgical correction of a defect in cranial bone by implanting a metal or plastic replacement to restore the missing part. This paper aims to do a comparative study on the dimensional error of CAD and SLS RP Models for reconstruction of cranial defect by comparing the virtual CAD with the physical RP model of a cranial defect.
Keywords: Rapid Prototyping, Selective Laser Sintering, Cranial defect, Dimensional Error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33495575 Enhancing Children’s English Vocabulary Acquisition through Digital Storytelling at Happy Kids Kindergarten, Palembang, Indonesia
Authors: Gaya Tridinanti
Abstract:
Enhanching English vocabulary in early childhood is the main problem often faced by teachers. Thus, the purpose of this study was to determine the enhancement of children’s English vocabulary acquisition by using digital storytelling. This type of research was an action research. It consisted of a series of four activities done in repeated cycles: planning, implementation, observation, and reflection. The subject of the study consisted of 30 students of B group (5-6 years old) attending Happy Kids Kindergarten Palembang, Indonesia. This research was conducted in three cycles. The methods used for data collection were observation and documentation. Descriptive qualitative and quantitative methods were also used to analyse the data. The research showed that the digital storytelling learning activities could enhance the children’s English vocabulary acquisition. It is based on the data in which the enhancement in pre-cycle was 37% and 51% in Cycle I. In Cycle II it was 71% and in Cycle III it was 89.3%. The results showed an enhancement of about 14% from the pre-cycle to Cycle I, 20% from Cycle I to Cycle II, and enhancement of about 18.3% from Cycle II to Cycle III. The conclusion of this study suggests that digital storytelling learning method could enhance the English vocabulary acquisition of B group children at the Happy Kids Kindergarten Palembang. Therefore, digital storytelling can be considered as an alternative to improve English language learning in the classroom.Keywords: Acquisition, enhancing, digital storytelling, English vocabulary.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16425574 Trust In Ad Media
Authors: Duygu Aydin
Abstract:
Advertising today has already become an integral part of human life as a building block of the consumer community. A component of the value chain of the media, advertising sector is struggling increasingly harder to find new methods to reach consumers. The tendency towards experimental marketing practices is increasing day by day, especially to divert consumers from the idea “They are selling something to me.” It is therefore considered a good idea to investigate the trust in ad media of consumers, who are today exposed to a great bulk of information from advertising sector. In this study, the current value of ad media for the young consumer will be investigated. Data on various ad media reliability will be comparatively analyzed and young consumers will be traced by including university students in the study. In this research, which will be performed on students studying at the Selçuk University (Turkey) by random sampling method, data will be obtained by survey technique and evaluated by a statistical analysis.Keywords: Trust in advertising, ad medium, media.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19285573 Movie Genre Preference Prediction Using Machine Learning for Customer-Based Information
Authors: Haifeng Wang, Haili Zhang
Abstract:
Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.Keywords: Computational social science, movie preference, machine learning, SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16355572 Fast Painting with Different Colors Using Cross Correlation in the Frequency Domain
Authors: Hazem M. El-Bakry
Abstract:
In this paper, a new technique for fast painting with different colors is presented. The idea of painting relies on applying masks with different colors to the background. Fast painting is achieved by applying these masks in the frequency domain instead of spatial (time) domain. New colors can be generated automatically as a result from the cross correlation operation. This idea was applied successfully for faster specific data (face, object, pattern, and code) detection using neural algorithms. Here, instead of performing cross correlation between the input input data (e.g., image, or a stream of sequential data) and the weights of neural networks, the cross correlation is performed between the colored masks and the background. Furthermore, this approach is developed to reduce the computation steps required by the painting operation. The principle of divide and conquer strategy is applied through background decomposition. Each background is divided into small in size subbackgrounds and then each sub-background is processed separately by using a single faster painting algorithm. Moreover, the fastest painting is achieved by using parallel processing techniques to paint the resulting sub-backgrounds using the same number of faster painting algorithms. In contrast to using only faster painting algorithm, the speed up ratio is increased with the size of the background when using faster painting algorithm and background decomposition. Simulation results show that painting in the frequency domain is faster than that in the spatial domain.Keywords: Fast Painting, Cross Correlation, Frequency Domain, Parallel Processing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17825571 Machine Learning Methods for Network Intrusion Detection
Authors: Mouhammad Alkasassbeh, Mohammad Almseidin
Abstract:
Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.
Keywords: IDS, DDoS, MLP, KDD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7175570 Selection of Best Band Combination for Soil Salinity Studies using ETM+ Satellite Images (A Case study: Nyshaboor Region,Iran)
Authors: Sanaeinejad, S. H.; A. Astaraei, . P. Mirhoseini.Mousavi, M. Ghaemi,
Abstract:
One of the main environmental problems which affect extensive areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Neyshaboor area, North East of Iran was selected as a field study of this research. Landsat satellite images for this area were used in order to prepare suitable learning samples for processing and classifying the images. 300 locations were selected randomly in the area to collect soil samples and finally 273 locations were reselected for further laboratory works and image processing analysis. Electrical conductivity of all samples was measured. Six reflective bands of ETM+ satellite images taken from the study area in 2002 were used for soil salinity classification. The classification was carried out using common algorithms based on the best composition bands. The results showed that the reflective bands 7, 3, 4 and 1 are the best band composition for preparing the color composite images. We also found out, that hybrid classification is a suitable method for identifying and delineation of different salinity classes in the area.
Keywords: Soil salinity, Remote sensing, Image processing, ETM+, Nyshaboor
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20105569 Bullies and Their Mothers: Who Influence Whom?
Authors: Kostas A. Fanti, Stelios Georgiou
Abstract:
Even though most researchers would agree that in symbiotic relationships, like the one between parent and child, influences become reciprocal over time, empirical evidence supporting this claim is limited. The aim of the current study was to develop and test a model describing the reciprocal influence between characteristics of the parent-child relationship, such as closeness and conflict, and the child-s bullying and victimization experiences at school. The study used data from the longitudinal Study of Early Child-Care, conducted by the National Institute of Child Health and Human Development. The participants were dyads of early adolescents (5th and 6th graders during the two data collection waves) and their mothers (N=1364). Supporting our hypothesis, the findings suggested a reciprocal association between bullying and positive parenting, although this association was only significant for boys. Victimization and positive parenting were not significantly interrelated.Keywords: bullying, parenting, reciprocal associations, victimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16295568 Expert System for Chose Material used Gears
Authors: E.V. Butilă, F. Gîrbacia
Abstract:
In order to give high expertise the computer aided design of mechanical systems involves specific activities focused on processing two type of information: knowledge and data. Expert rule based knowledge is generally processing qualitative information and involves searching for proper solutions and their combination into synthetic variant. Data processing is based on computational models and it is supposed to be inter-related with reasoning in the knowledge processing. In this paper an Intelligent Integrated System is proposed, for the objective of choosing the adequate material. The software is developed in Prolog – Flex software and takes into account various constraints that appear in the accurate operation of gears.Keywords: Expert System, computer aided design, gear boxdesign, chose material, Prolog, Flex
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16825567 Enhancement of Higher Order Thinking Skills among Teacher Trainers by Fun Game Learning Approach
Authors: Malathi Balakrishnan, Gananathan M. Nadarajah, Saraswathy Vellasamy, Evelyn Gnanam William George
Abstract:
The purpose of the study is to explore how the fun game-learning approach enhances teacher trainers’ higher order thinking skills. Two-day fun filled fun game learning-approach was introduced to teacher trainers as a Continuous Professional Development Program (CPD). 26 teacher trainers participated in this Transformation of Teaching and Learning Fun Way Program, organized by Institute of Teacher Education Malaysia. Qualitative research technique was adopted as the researchers observed the participants’ higher order thinking skills developed during the program. Data were collected from observational checklist; interview transcriptions of four participants and participants’ reflection notes. All the data were later analyzed with NVivo data analysis process. The finding of this study presented five main themes, which are critical thinking, hands on activities, creating, application and use of technology. The studies showed that the teacher trainers’ higher order thinking skills were enhanced after the two-day CPD program. Therefore, Institute of Teacher Education will have more success using the fun way game-learning approach to develop higher order thinking skills among its teacher trainers who can implement these skills to their trainee teachers in future. This study also added knowledge to Constructivism learning theory, which will further highlight the prominence of the fun way learning approach to enhance higher order thinking skills.
Keywords: Constructivism, game-learning approach, higher order thinking skill, teacher trainer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27905566 Free Fatty Acid Assessment of Crude Palm Oil Using a Non-Destructive Approach
Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak
Abstract:
Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.
Keywords: Palm oil, fatty acid, NIRS, regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43545565 Comanche – A Compiler-Driven I/O Management System
Authors: Wendy Zhang, Ernst L. Leiss, Huilin Ye
Abstract:
Most scientific programs have large input and output data sets that require out-of-core programming or use virtual memory management (VMM). Out-of-core programming is very error-prone and tedious; as a result, it is generally avoided. However, in many instance, VMM is not an effective approach because it often results in substantial performance reduction. In contrast, compiler driven I/O management will allow a program-s data sets to be retrieved in parts, called blocks or tiles. Comanche (COmpiler MANaged caCHE) is a compiler combined with a user level runtime system that can be used to replace standard VMM for out-of-core programs. We describe Comanche and demonstrate on a number of representative problems that it substantially out-performs VMM. Significantly our system does not require any special services from the operating system and does not require modification of the operating system kernel.Keywords: I/O Management, Out-of-core, Compiler, Tile mapping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13075564 A Knee Modular Orthosis Design Based on Kinematic Considerations
Authors: C. Copilusi, C. Ploscaru
Abstract:
This paper addresses attention to a research regarding the design of a knee orthosis in a modular form used on children walking rehabilitation. This research is focused on the human lower limb kinematic analysis which will be used as input data on virtual simulations and prototype validation. From this analysis, important data will be obtained and used as input for virtual simulations of the knee modular orthosis. Thus, a knee orthosis concept was obtained and validated through virtual simulations by using MSC Adams software. Based on the obtained results, the modular orthosis prototype will be manufactured and presented in this article.Keywords: Human lower limb, children orthoses, kinematic analysis, knee orthosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15945563 SVM Based Model as an Optimal Classifier for the Classification of Sonar Signals
Authors: Suresh S. Salankar, Balasaheb M. Patre
Abstract:
Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.
Keywords: Classification, MLP NN, backpropagation algorithm, SVM, Receiver Operating Characteristics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18115562 ANFIS Modeling of the Surface Roughness in Grinding Process
Authors: H. Baseri, G. Alinejad
Abstract:
The objective of this study is to design an adaptive neuro-fuzzy inference system (ANFIS) for estimation of surface roughness in grinding process. The Used data have been generated from experimental observations when the wheel has been dressed using a rotary diamond disc dresser. The input parameters of model are dressing speed ratio, dressing depth and dresser cross-feed rate and output parameter is surface roughness. In the experimental procedure the grinding conditions are constant and only the dressing conditions are varied. The comparison of the predicted values and the experimental data indicates that the ANFIS model has a better performance with respect to back-propagation neural network (BPNN) model which has been presented by the authors in previous work for estimation of the surface roughness.Keywords: Grinding, ANFIS, Neural network, Disc dressing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24075561 The Digital Filing Cabinet–A GIS Based Management Solution Tool for the Land Surveyor and Engineer
Authors: A. Giraldo, A. Lapatka, A. Namyslak, S. Pilny, J. B. Miima
Abstract:
This paper explains how the New Jersey Institute of Technology surveying student team members designed and created an interactive GIS map, the purpose of which is to be useful to the land surveyor and engineer for project management. This was achieved by building a research and storage database that can be easily integrated into any land surveyor’s current operations through the use of ArcGIS 10, Arc Catalog, and AutoCAD. This GIS database allows for visual representation and information querying for multiple job sites, and simple access to uploaded data, which is geospatially referenced to each individual job site or project. It can also be utilized by engineers to determine design criteria, or to store important files. This cost-effective approach to a surveying map not only saves time, but saves physical storage space and paper resources.
Keywords: Data Storage, GIS, Land Surveying, Mapping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18935560 Hepatoprotective Activity of Sharbat Deenar, against Carbon Tetrachloride-Induced Hepatotoxicity in Rats
Authors: Nazmul Huda, Ashik Mosaddik, Abdul Awal, Shafiqur Rahman, Rukhsana Shaheen, Mustofa Nabi
Abstract:
Polyherbal formulation Sharbat Deenar is a very popular unani medicine in Bangladesh. It is usually used for different kinds of liver disorders. In absence of reliable and inadequate hepatoprotective agents in conventional medicine, the herbal preparations are preferred for liver diseases. The present study was designed to evaluate the hepatoprotective activity of Sharbat Deenar on carbon tetrachloride (CCl4) induced hepatotoxicity in male Long-Evans albino rats. Group I served as normal control and received neither formulation nor carbon tetrachloride. Group II received only CCl4 1mL/kg body weight of rat intraperitoneally for consecutive 14 days. Group III received CCl4 1mL/kg body weight of rat intraperitoneally and Silymarin, in dose 50mg/kg body weight of rat orally. Group IV received CCl4 1mL/kg body weight of rat intraperitoneally and Sharbat Deenar 1mL/kg body weight of rat for the same 14 consecutive days. At the end of the study, hepatoprotective activity was evaluated by the levels of total bilirubin, alanine aminotransferase (ALT), aspartate aminotransferase (AST) and alkaline phosphatase (ALP). Histopathological study of rat liver was also carried out. The results showed that polyherbal formulation Sharbat Deenar exhibited a significant hepatoprotective effect. Such an outcome seems to be the synergistic effect of all ingredients of tested herbal formulation. Although this study suggests that Sharbat Deenar may be used to cure or minimize various liver diseases, it needs further study to attain the clarity of mechanism and safety.
Keywords: Carbon tetrachloride, Hepatoprotective, Sharbat Deenar, Silymarin.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8615559 A Sociocybernetics Data Analysis Using Causality in Tourism Networks
Authors: M. Lloret-Climent, J. Nescolarde-Selva
Abstract:
The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.
Keywords: Attractor, invariant set, orbits, tourist variables.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17385558 House Indoor Thermal and Health Conditions with Different Passive Designs
Authors: Bin Su
Abstract:
According to the Auckland climate, building passive design more focus on improving winter indoor thermal and health conditions. Based on field study data of indoor air temperature and relative humidity close to ceiling and floor of an insulated Auckland townhouse with and without a whole home mechanical ventilation system, this study is to analysis variation of indoor microclimate data of an Auckland townhouse using or not using the mechanical ventilation system to evaluate winter indoor thermal and health conditions for the future house design with a mechanical ventilation system.Keywords: House ventilation, indoor thermal condition, indoor health condition, passive design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15045557 A Novel Approach to Optimal Cutting Tool Replacement
Authors: Cem Karacal, Sohyung Cho, William Yu
Abstract:
In metal cutting industries, mathematical/statistical models are typically used to predict tool replacement time. These off-line methods usually result in less than optimum replacement time thereby either wasting resources or causing quality problems. The few online real-time methods proposed use indirect measurement techniques and are prone to similar errors. Our idea is based on identifying the optimal replacement time using an electronic nose to detect the airborne compounds released when the tool wear reaches to a chemical substrate doped into tool material during the fabrication. The study investigates the feasibility of the idea, possible doping materials and methods along with data stream mining techniques for detection and monitoring different phases of tool wear.Keywords: Tool condition monitoring, cutting tool replacement, data stream mining, e-Nose.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1872